From Ottawa to Orbit: Two Views on Canada’s Big Day

SPEAKERS

Colonel Jeremy Hansen, Michael Sabia, John Stackhouse

John Stackhouse 00:00:09

Hi, it’s John here. As we wrap up this season, I want to share a couple of conversations with you that I thought captured a couple of the big ideas we heard over and over again this season. One is on moonshots, the other is on big ambitions.

The first is with Jeremy Hansen, who is now the Canadian authority on moonshots because he’s been to the moon and back. He’ll share insights from the journey, the voyage, and what it taught him about leadership and about humanity. We’ll also hear from someone who may be a little less celebrated than Colonel Hansen, but is hugely important to all the moonshots that Canada is trying to undertake this decade.

Michael Sabia runs the Canadian public service and is Prime Minister Carney’s right hand for pretty much everything major that is going on in the country. He’s also one of Canada’s most respected business thinkers and business leaders. Having run Hydro-Quebec, the Quebec Pension Fund and Bell Canada, he knows a thing or two about disruption and is on the front lines of all the disruptions that Canada is up against.

Both conversations were recorded live at the recent RBC Eurasia Group Canada US Summit held here in Toronto. One of my takeaways from that summit is that we’re going to face a long, hot summer when it comes to trade negotiations and everything else that’s on the table between Canada and the US. But there’s also a huge amount of opportunity, especially if we stay grounded but reach towards the stars. That’s the formula of every great moonshot.

Here he is, fresh from Halifax, Colonel Jeremy Hansen. So he literally flew from Halifax to get here this morning, but of course has also returned from another trip. He’s been to the moon and back. For those of you who don’t know Jeremy’s story, born in London, Ontario, educated at the Royal Military College and spent 17 years in Houston living, working, training with the American astronauts, but always wearing that Canadian flag on your shoulder there. So we’re going to talk about space, but we’re also going to talk about Canada and what lies ahead. But thank you. A lot of people are wanting to spend time with you right now and it’s wonderful for you to be part of this conversation.

Colonel Jeremy Hansen 00:02:35

Yeah, I appreciate that. And I actually appreciate the opportunity just to be with you, thought leaders. These types of conversations and leaders like you that put Canada in the position to collaborate with the United States, that Canada became the second country to send a human in a deep space because of that collaboration. So I’m excited to be here with you. It was worth the flight.

John Stackhouse 00:02:53

Well, we’re going to talk about– it was worth the flight–we’re going to talk about all that’s going on down here, but let’s start up there because the summit has been very much about the ground level, but you’re, I think, the only one in this room who has seen our beautiful continent from afar, very, very far away. What went through your mind as you were whipping around the moon there and got to look down on our little rock here and our little piece of that rock?

Colonel Jeremy Hansen 00:03:19

Pretty extraordinary journey. I would highlight, I flew with Reid, Victor and Christina and they had all spent at least six months, Christina closer to a year, aboard the International Space Station. And in the beginning, when you ride the rocket to space and you get out to, we went out to about 2,000 kilometers on our first orbit. I did get to see the continent, all of Canada, all of the United States all at once, but it wasn’t very long until all of that started to disappear and you couldn’t make out continents anymore. You saw a lot of blue, you saw a lot of white clouds. You’d see strange shapes of the terrain, but it was hard with the cloud cover to really make out what you’re looking at. And very soon you just started to connect with what we termed “tiny earth.”

And you couldn’t always see earth out the window, it depended on the orientation of the spacecraft. And so whenever the spacecraft would turn for thermal reasons and we would catch earth out the window, someone would just say, “Oh, there’s tiny earth.” And we would all float over and admire tiny earth. But I think it was interesting that I stopped connecting with a country, I started connecting with a planet. And I didn’t really think about that until I had some time off last week and I was like, “Gosh, yeah, it’s really true.” I just naturally stopped connecting with a country. But I will say, when I do think about our collaboration, something that really jumps out at me and when I looked at it from space is, for a thriving North America, you have to have a thriving Canada and you have to have a thriving United States. There’s just no other way to see it from space.

And that does mean two things. In the Astronaut Corps, we have these expeditionary skills, we call them, but two of the five are self-care and team care. And in order to be a good team player in a crew, you have to have good self-care. And so understanding how each of us take care of ourselves and our thriving as individuals is what allows the conversation to figure out how do we collaborate while still accomplishing that.

John Stackhouse 00:05:13

It’s a bit of a message for Canada and the US that we have to take care of ourselves but also be part of the team.

Colonel Jeremy Hansen 00:05:19

When you decide to go on a trip, try and send yourself around the moon, you do need a team. You need mission control, you need the engineering teams and of course you need the team that’s in the capsule and you don’t pick that team lightly. And so our currency is competency and collaboration. Those are the two things we have to have, otherwise, it falls apart. And we demand that. There’s no free rides in space exploration. Everybody has to be in it fully, has to be digging in and bringing real meaningful contribution. And that’s what I see here when I look at this room. You guys are all spending time here because you see that it’s valuable to lean into how can we get our two countries working together and firing in all cylinders to bring that collaboration.

John Stackhouse 00:06:09

Give us a sense of the collaboration up there because there’s no more challenging or risky environment.

Colonel Jeremy Hansen 00:06:15

Yeah. So Reid was our commander and the commander is always the commander, but a good commander will lift up their crew and utilize them to their full capability. And so Reid was very intentional about finding meaningful roles for all of us in the capsule and dividing the tasks through the mission. And so for launch and entry, Reid and Victor were in the seats with the controls and those were their primary areas. For all of the other trajectory burns that we did to navigate around the moon and back and get up to 39 times the speed of sound, that was Christina and I who were responsible for those. We’d built a lot of trust and we had worked through a lot of tensions.

In the beginning, we committed time in saying we want to get to be the highest functioning team that we can be. And then eventually when we came to understand that we would need to understand each other better. And so with that time we started to dig deeper and then we started to build a muscle that we would communicate when things, anytime there was a small friction, we would start to communicate about it. And that is the muscle we built so that we would eventually become this team that just wouldn’t let something fester.

John Stackhouse 00:07:23

So a team, but you’re also an individual. What did you learn about yourself on the mission?

Colonel Jeremy Hansen 00:07:29

I really found myself moved in gratitude for the opportunity and for what we have. There is an innate human joy in accomplishing tough things, taking on big challenges, leaning into help, helping others. What it reinforced for me coming back here is that it is very much worth continuing to dig into the challenging and hard things that we have in front of us. This Canada-US relationship for one, how we leverage space. There’s a list as long as my arm of things that we could do that are the right things to do for our country and the right things to do for our international collaboration on space. I guess I know with concrete certainty that there’s value in pursuing that.

John Stackhouse 00:08:22

So let’s get into some of those challenges and opportunities. We’re all more excited about space today, I’d suggest. How do we seize on that excitement and what should we as a country, as Canada, but also as neighbors, Canadians and Americans be doing?

Colonel Jeremy Hansen 00:08:37

Something that I’ve said often that I think is worth highlighting here is, why was there a Canadian on Artemis II? And it’s because Canada partnered with the United States decades ago. Canadians held a vision over decades, thousands of people participated in this, but also because the United States carved out space for a country to bring their gifts and actually bring real value to the collaboration. And so when we committed to developing a third generation of space robotics, Canada earned its way onto the Artemis II flight and that’s a really incredible example. And so what I would suggest out of that is as we look at our relationship, we really need to ensure that we are guiding the masses, that collaboration is our stated objective.

Actually getting stuff done and working together in a way that is mutually beneficial has to be our stated objective. And so if you’re going to lead thousands of people who are going to make millions of decisions in order to make this the thriving collaboration it could be, then you need that stated commander’s intent, that overriding commander’s intent. And it does not need to be complicated, but it has to be simple in that collaboration is the desired outcome and that at the end of the day, it should be mutually beneficial for both parties.

John Stackhouse 00:10:01

I wonder, Jeremy, if you can leave us with some of the insights you’ve brought back from space on what we can all take away in terms of how to go about our own days, but also how our two countries can work together in the years ahead.

Colonel Jeremy Hansen 00:10:14

Well, pretty much every night that we’re sleeping on board the spacecraft, the caution and warning system went off and woke us up. And every time the caution warning system goes off, it might be a false alarm, but you don’t treat it like that. You float out of your sleeping bag and you float the displays and you start trying to figure out what is going on and why that happened. And then you talk to mission control and you work through it. And I think what is maybe useful for us as humans is, especially with our cancel culture and our culture that just is constantly pointing out what’s wrong, we as leaders can’t accept that. That’s not good enough. People who can point out what’s broken and stop there is not acceptable in our space culture. We do not allow a flight control or a mission control to pass or to participate in our program if that’s all they can do is point out the problems.

We have an expectation that they will, yes, identify the problem, but then they will identify a workaround or a solution, or at the very least, a path forward to find a solution and who they need help with. And we as leaders right now need to demand of the people in this conversation that they either get the depth of understanding to understand all sides of the problem and an actual solution, or we just don’t need to hear from them yet.

John Stackhouse 00:11:43

I can’t think of a better message to end on Colonel Hansen, Jeremy. Thank you, thank you. On behalf of the audience, on behalf of the US-Canada Summit, thank you for this conversation, but also all that you’re doing for Canada and the world.

Colonel Jeremy Hansen 00:11:56

Thanks everyone. Have a great day.

John Stackhouse 00:12:03

Jeremy Hansen went to the moon and came back with something more than data. It was a new way of seeing. From that distance, borders disappear. What’s left is the relationship.

Canada’s top public servant has kind of been doing the same but from a very different vantage point. Here’s Michael Sabia. What a great way to end the day. Michael is one of the most thoughtful people I’ve known. You are.

Michael Sabia 00:12:32

You’re jumping to conclusions.

John Stackhouse 00:12:34

See what I say at the end of the conversation. No, let’s get right into the relationship because you’ve been clerk for close to a year, probably feels a lot longer.

Michael Sabia 00:12:44

It does.

John Stackhouse 00:12:44

But you’re not quite at the one year mark. And you’ve in various jobs dealt with Americans, worked with Americans. Curious what, in this position, what you’ve seen that maybe the rest of us don’t see or understand about the relationship?

Michael Sabia 00:13:00

I don’t think that I see anything in particular that others don’t see. I mean, at the end of the day, this relationship between Canada and the United States, this is not ultimately about a relationship between two governments. Obviously, governments matter. I mean, that’s the statement of the obvious, but the relationship is so much deeper and so much more highly distributed. Here I’m thinking about governors, chambers of commerce, CEOs, investors, firms, families. I mean, that’s the bedrock of this relationship between Canada and the United States. And I think those people on both sides of the border understand that by working together, we are collectively stronger and it creates strength on both sides. That’s the essence of it. And as Canadians, I think we have to be and we are trying now to invest a lot more in the strengthening of those relationships and taking our case to a broad spectrum of Americans beyond just the administration in Washington.

So if you asked me kind of what did I learn in this period, I guess it’s a bit paradoxical and I think I’d say, on the one hand, this is a relationship of great strength because of its depth, because of how highly distributed it is, but at the same time, paradoxically, it’s also fragile. Fragile because at this time in such a contested world, the strength doesn’t necessarily manifest itself in resilience on either side of the border. So for us, I mean, the lesson I draw from that is we have to continue and really redouble our efforts at working with that broad spectrum of opinion in the United States.

John Stackhouse 00:14:47

The Carney government is clearly focused on diversification but not decoupling. Help us understand how you walk that fine line between trying to diversify Canada’s relationships, not just through trade, without alienating our principle partner or antagonizing.

Michael Sabia 00:15:03

I actually don’t think there’s a tension here because you’re absolutely right. We are not decoupling. Yes, we are diversifying, but look at Canada’s economic policy and split it geographically. I mean, two basic pieces, there’s the United States piece and there’s the rest of the world piece. I don’t think there’s a strategic conflict between those two things. I think actually those two things are mutually reinforcing. That’s the essence of it. So take the US side, clearly proximity brings with it some economic gravity. I mean, that’s an inevitability. And therefore, does Canada need a well-functioning economic relationship with the United States? Absolutely we do. And that’s why the Prime Minister a couple of weeks ago in New York called for a new economic partnership between Canada and the United States. Now that starts with the work we’re doing on the CUSMA negotiations. It starts in addition to CUSMA with working to get to a trade arrangement for some of the heavily impacted sectors, whether it’s aluminum, steel, autos, et cetera.

But what’s really important to understand here is all of that rests on, in our view, a foundation of a stronger Canada. And that stronger Canada is the result of the work that we’re doing to invest in the country, to yes, diversify our economy, to use our natural resources as the coin that will allow us to diversify more broadly. It’s about doubling the electricity production of our country, which we are going to do. It’s about AI and the things that Canada is an intellectual leader in AI, we need to start using that for commercial purposes. It’s about all these other things that we’re going to do to make Canada a stronger economic presence and a stronger economic partner to the United States, which is why not decoupling, yes, we’re going to strengthen Canada, but by strengthening Canada, we think we can strengthen the relationship with the United States and that’s the frame of mind that we have.

John Stackhouse 00:17:09

Let’s shift to defense strategy. It’s been a focus of this summit. The government is clearly increasing, quite significantly, defense spending, but defense spending has become key to economic and trade policy as well, which is a big shift. How are you thinking through balancing the efficiencies as well as the requirements of defense spending, ultimately protecting the country while also stimulating economic growth, adding to the Canada Strong agenda and being used, if I can put it this way, as a trade lever.

Michael Sabia 00:17:39

Yeah. So national security and economic security, though those two things are mutually reinforcing and that’s pretty fundamental to how we think about defense. I think the issue’s a lot broader than procurement though. I mean, this is ultimately, on the defense side, this is ultimately about a few things. One, it’s Canada stepping up to take care of ourselves, which we need to do. It’s Canada stepping up to be a good ally in a context of NATO or whatever. And it’s Canada thinking creatively about how we can use defense dollars to accomplish two objectives at the same time, to strengthen national security on the one hand, but at the same time to promote economic development. In other words, by creating more defense industries, by creating a more dynamic environment in the Arctic with the investments that we will make there. So it’s a really good example of how the kind of policies that we’re pursuing and the diversification that we’re pursuing is not at odds with America’s interests.

Why do I say that? Look at the Arctic. There, we are working in a diversified environment. We are working with the Nordic Five. We are asserting our presence in the North, both for economic reasons and for military reasons. And I think actually that’s exactly consistent with what the Americans would like to see. They would like to see Canada stepping up, doing what we need to do a little bit more, well, more aggressively, not a little bit more, more aggressively from a defense spending and a defense presence point of view. But that diversity that we’re pursuing, that diversification we’re pursuing with the Nordic five is a great example of how our cooperation with other countries can frankly take some of the pressure off the United States. And when I stand back, John, and I think about, I just look at the hand we have to play and I compare that to other hands of other countries in the world.

We have huge reserves of low carbon, low cost gas, and the world’s going to need gas. We have foods and fertilizers for a hungry world. We have natural resources and especially critical minerals and in the fall, you’re going to see a package of regulatory reforms that are going to allow us to speed up and to speed up in a dramatic way. We now have a plan to move forward on using AI and adopting AI. As I said, we’ve been an intellectual leader, but now we need to integrate it into our economy and deal with some of our productivity issues. By the end of the year, we’ll be the only country in the world that has access to three billion consumers through free trade agreements, the only country in the world that can say that. We’re changing the way the country operates so that it’s not just a Montreal to Toronto corridor that dictates what happens in Canada, but that all of the regions of the country, because of their importance from an economic development point of view, that they’re part of the game as well.

One other thing, we also have one other asset that sadly is pretty rare in the world today and that’s a sad thing and that is a simple word, the word is trust. People trust us. They trust us because of our values. They trust us because of our history. So when I look at all of that, the conclusion I draw from that is, this is not a time for national anxiety about a relationship between two governments. This is a time for confidence because we have a hand that, played properly, played in a skillful way, can lead to really a new chapter in Canada’s history and a new chapter in the relationship between Canada and the United States, which we acknowledge is very important and an important foundation for the future prosperity of the country.

John Stackhouse 00:21:27

What a great note to end on. In fact, that’s the note we began on this morning. Dave mentioned its risk in Canada. We’re hearing that from around the world. Lots of smart people are seeing that hand. We are playing it, but we’ve got to play it even more ambitiously in the US.

Michael Sabia 00:21:41

Ambition. Now there’s an important word. That’s exactly what we need. Confidence, ambition. Those are the characteristics that are going to build the future of the country and build an enduring and good relationship with the United States.

John Stackhouse 00:21:53

Let’s do it.

Michael Sabia 00:21:54

Let’s do it.

John Stackhouse 00:21:55

All right. Great note to end on. Michael, thank you.

Michael Sabia 00:21:57

Thank you.

John Stackhouse 00:21:57

Thank you. Thank you.

Michael Sabia 00:21:58

Thank you.

John Stackhouse 00:22:04

Two conversations, one from orbit, one from the room where policy gets made, but both pointing in the same direction, which can be incredibly positive for Canada. From all of us at Disruptors, that’s season 10 and what a season it’s been. This season Disruptors won a Webby Award and that genuinely would not have happened without you. To everyone who listened, who shared the show and who voted, thank you. It means a lot to our whole team here at RBC. We’ll be back in the fall with more conversations at the edge of what’s changing Canada and the world. Until then, have a safe and happy summer. And if you’re listening along the way, be sure to check out some of the episodes from years past that we will re-release through July and August.

Be sure to like, follow, and subscribe to Disruptors wherever you get your podcasts. And if you want to explore more of RBC’s thinking on all the issues that we cover, head to rbc. com/thoughtleadership or follow us on social media. And if you can, be sure to like, follow, and subscribe to Disruptors wherever you get your podcasts. I’m John Stackhouse and this is Disruptors, an RBC podcast. Thanks for listening and we’ll see you in September.

Own The Stack: Canada’s Data Sovereignty Test

SPEAKERS

Sahar Kayhani, Warren Roy, John Stackhouse

John Stackhouse 00:00:09

Hi, it’s John here and welcome to a special episode of Disruptors. I’m in North Vancouver standing outside the nondescript building on the North Shore of Burrard Inlet. It’s a data centre. Those are two words that you may not have used a lot a few years ago and now it’s hard to pass a day without hearing a lot and some of it controversial. Data centres are front and centre in every economic conversation and a lot of political conversations because they are so important to what’s going on in our society. The new AI strategy from the federal government speaks directly to that. Canada needs to develop more capacity and more sovereignty around all sorts of things, but data is one of them and we may need more data centres to ensure that.

Right now, there are roughly 300 data centres in Canada, including this one owned, operated and built by Global Relay, a Canadian company. 300 may seem like a lot, but that doesn’t stack up too much next to the United States where there are 5,000 data centres and that number is growing rapidly. Globally, the world has about 11,000 data centres right now and there’s a real arms race underway to build more data centres as well as the infrastructure, including energy and water required to power, cool, and operate them. This global relay centre was designed to minimize the carbon footprint, not just of the building but of the processing of all the data, which frankly is more than any of us could ever count.

I’m being greeted now by Sahar Kayhani. She’s the chief product officer at Global Relay, a facility that stores communications data for 22 of the world’s 25 largest banks. And while I’ve got a lot of questions, we’ll be sure to delve into one very big one. When it comes to digital sovereignty, what can Canada learn from a company that has spent years making it operational? Sahar, welcome to Disruptors.

Sahar Kayhani 00:02:19

Thank you, John. It’s great to be here.

John Stackhouse 00:02:21

Well, it’s especially great to be here on a gorgeous day in Vancouver. The sun is shining, the gentle wind is blowing. Before we get going Sahar, tell us a bit about your own journey and how you got to Global Relay.

Sahar Kayhani 00:02:34

I graduated in computer science a while ago. When I joined the company in 2014, I think we had about a little shy of 300 employees or around that number and since then we grew to 1,800 or a little over 1,800 now. And as a woman in technology, it was a very welcoming journey in Global Relay. We have many senior leadership of the company that are women here. So it’s been a fantastic journey so far.

John Stackhouse 00:03:06

Sahar, we’re still outside the building and it’s fascinating to see the design and the architecture, which as I understand it, is designed for security to keep the data centre from outside attacks, if I can put it that way.

Sahar Kayhani 00:03:20

Yeah, there are some elevated walls that basically are designed to make sure that the data centre is physically secure from outside the vehicles as well. We obviously, when we go inside there is various other elements of physical security that is built into this data centre.

John Stackhouse 00:03:42

So we’re inside the compound now, Sahar, and one of the aspects of your location here in Vancouver and specifically North Van that I hadn’t appreciated was the free flow of cooler marine air coming off Burrard Inlet. We’re staring now at three stories of intake devices for that air, they look kind of like louvre blinds.

Sahar Kayhani 00:04:05

Yeah. The cool air goes into the facility and makes the cooling very efficient basically from a power perspective.

John Stackhouse 00:04:13

And I guess another advantage there is it doesn’t look like you have air conditioners around here and that’s one of the functions of the bigger data centres, especially in hotter places like the Southern United States. They need massive air conditioning, which takes up space, it also takes up a lot of energy.

Sahar Kayhani 00:04:30

Yes. This allows us to not use any traditional air conditioning and just rely on the air from the marine to basically control the temperature of the facility.

John Stackhouse 00:04:41

And that’s one of the reasons you call this a green data centre.

Sahar Kayhani 00:04:44

Yep.

John Stackhouse 00:04:45

Let’s go further inside. We’re now inside the electrical room. It’s loud. Around me are six UPSs. That stands for uninterruptible power supply and that is the engine right literally of any data centre. Inside each of these six big boxes, it’s really interesting to see one opened up and underneath are these giant wheels that spin at 7,000 RPMs. So there’s a lot of power that goes into making more power for the data centre.

Sahar, we’ve moved to the second floor and are now inside a data hall. You can get in here only with biometric access and once in here it feels to me a bit like the data economy equivalent of an old bank vault. We used to store gold bars underground, now we store data in these giant racks on the second floor of a data centre.

Sahar Kayhani 00:05:48

So there is a few aspects related to storing data and the security of it. The first one is obviously redundancy does matter and the second one from various different regulatory perspective or generally data management, aspect that no one can tamper with the copy also matters. So this hall that we see here, we saw all these tapes as backups.

John Stackhouse 00:06:12

I’m holding an LTO now. This is like a big old disc that has 10 terabytes of data on it and we’re staring at racks with hundreds of these discs on and it’s all operated by robots. And the purpose of this room is essentially a backup for all the data that is out there on servers.

Sahar Kayhani 00:06:33

The robots help manage the whole system of which data is stored in which tape and moving them around for efficiency purposes. The servers that we’re going to se next are where basically the live data and the live product and application runs, but this stores the non-tamperable, non-deletable copy of the data. It’s basically the last copy of the data.

John Stackhouse 00:06:57

Let’s go. We’re now inside the main data hall. It’s frankly a little cool in here. I think it’s 13 or 14 degrees Celsius. All that cool air that we described earlier being sucked into the building is being cranked through this room by giant fans to cool the data racks and servers and we’re looking at rows and rows of them, Sahar in front of us, each is built on top of these fascinating little devices to create some resistance in case there’s an earthquake because we’re here on the West Coast and there are earthquakes and tremors. And if you’re operating a data centre, you have to be very mindful that every little shift or bend beneath the surface can affect your data. Sahar, tell us a bit about what’s going on inside these racks and servers.

Sahar Kayhani 00:07:53

We have a few of these data halls within the data centre. We manage tens of petabytes of data for our customers and financial services and other highly regulated industries. So what these server racks do, is they store all this data with the aspects of security and encryption. They also run the services on top of this data that our customers need. Basically what we do with this data or what our customers do with this data, they keep it as business records. So as you can imagine, over the last few years of social media, AI, the data is only growing and that’s why we have the efficiency in the data centre to be able to grow with the customers and their data needs.

John Stackhouse 00:08:43

I’m standing next to an incredibly loud rack that is designed entirely for AI. I’ll step into the next room to learn a bit more about why AI is so loud.

Sahar Kayhani 00:08:57

It does go back to the energy. So those GPUs consume a lot more energy than the other server room and the data hall we were at, then that’s why the noise, in addition to the air cooling noise, you hear a lot more noise from the GPUs than the other rooms.

John Stackhouse 00:09:15

So the next time I have a question for Claude, I’ll ask it to respond a little more softly.

Sahar Kayhani 00:09:21

The concept of peace and quiet doesn’t match a data centre because I think quiet translates to something that’s not peaceful at all, something going down.

John Stackhouse 00:09:34

That was a fascinating tour into the engine room quite literally of the data economy and what Global Relay is doing to make more advances. We’re now going to hear from Warren Roy. He’s the CEO and founder of Global Relay. Warren, welcome to Disruptors.

Sahar Kayhani 00:09:54

It’s a pleasure to be here, John. Thanks for making the time for me today.

John Stackhouse 00:09:58

I want to pause here and go back in time to the origins of Global Relay and then we’ll get into some of the here and now. But you founded the company way back in 1999. There was an internet back then, but it was a very different digital world. What inspired you to create Global Relay?

Warren Roy 00:10:16

Well, the inspiration came from a very simple concept, which was really founded around people and companies transitioning from paper-based communications to electronic communications being email. And the principle of the business was never lose email again. We sat down and we designed the fundamentals of the business to achieve that objective.

John Stackhouse 00:10:40

Here we are more than a quarter century later, you’re in 90 countries, I think it is. What accelerated the global relay story to get you to where you are today?

Warren Roy 00:10:49

We really strove to have a niche focus and the focus itself was record keeping, but it materialized initially after about four years in the financial sector as a result of Enron, Arthur Andersen, WorldCom all going bust and the SEC, the Securities and Exchange Commission in the United States coming down with a rule called 17A4, which was a record keeping rule. And we had developed recordkeeping technology.

So there’s an element of luck as every entrepreneur will tell you in that a market presented itself based on a technology that we had developed. And the interesting part about that is that rule from the SEC obviously spawned many other companies getting into the same business, but we had a significant headstart on them. The other aspect of the rule is that virtually every Western country adopted a derivative of it, record keeping for the financial sector. And we were able to really aggressively get after those countries by getting in planes and flying around the world over and over and over again until we built up a reasonable amount of momentum, literally knocking on doors.

John Stackhouse 00:12:06

Here we are in a very different environment. How are you seeing tech sovereignty and what do you think is really driving it as a preeminent concern right now?

Warren Roy 00:12:16

Well, tech sovereignty and the whole sovereignty eye discussion is really quite new. It started to appear about two years ago. And if you boil it down, it’s two things, it’s about control and security. Every business wants to be in control of its destiny. Every government wants to be in control of the data that it uses that’s largely private in nature to conduct its day-to-day operations. So sovereignty is incredibly important and the way the technology world is unfolded, there is an enormous amount of power in very few hands and it’s recently made a lot of countries uncomfortable and resulted in them taking a look at what levers they can pull to have better control over their data, maybe not absolute control, but better control.

John Stackhouse 00:13:05

It’s interesting that you say tech sovereignty’s been around for only a couple of years. I suspect you’re right. I certainly don’t remember people talking about tech sovereignty a decade ago, but you were onto the issue a decade or more ago in terms of building infrastructure that would allow your customers and clients to develop optionality and therefore sovereignty. What did you see back then when the world was rushing to the what are now known as hyperscalers, but the big cloud companies? What did you see back then that perhaps others missed?

Warren Roy 00:13:42

We built the company from the standpoint of having top to bottom control over all aspects of the service. And that comes from lessons learned, John. We had a data centre early on that we occupied on the West Coast that had a catastrophic failure and we lost a lot of systems. We did fully recover, but the lesson we learned from it is that we didn’t want to depend on anybody going forward and it really changed our strategy at the time. And in 2012, we went down a road of developing our entire technology stack. In other words, we have no dependency on cloud vendors.

If you think about it objectively, we are our own cloud. We have always been our own cloud and that capability that governments and large organizations are looking for today. It’s really control over your ability to resolve issues when they occur, specifically not having dependencies where you cannot resolve issues.

John Stackhouse 00:14:41

Data location is an important part of sovereignty. I wonder if you can walk us through some of the nuances there, because a lot of us might assume that, hey, if a data centre is in a jurisdiction in Canada, the data’s safe, it’s not that simple. Walk us through how we should be understanding location versus data sovereignty.

Warren Roy 00:15:01

Yeah. The three areas we speak about most commonly with global companies is privacy and privacy is really about the country that your employees reside in. And when you’re dealing with a multinational, you have to resolve the privacy issues or meet the privacy issues of every one of those countries. Underneath that layer, you have the regulatory framework that’s in place and not all industries are regulated, but all significant industries are regulated. And the regulatory framework, there’s no global standards for it. So it’s different in every country that you operate in. And then a layer underneath that is law enforcement and different countries have different level, I would just call it of aggression when it comes to their law enforcement. You need to understand privacy, regulatory environments and law enforcement to be able to put any solution in place. And historically, if you all just give you an example, the United Kingdom names Canada in their Data Protection Act and it says any business residing in the UK can hold its data in Canada. And most countries have similar laws. That’s just an example.

So you really want to understand what countries you can do business with given where the corporation resides or cloud service resides. From a Global Relay perspective, we’ve been able to achieve what we just internally call data visas so the permissions of a regulator in any given country to hold that country’s data in Canada. And we operate data centres in Canada and in the US and they’re used for different purposes by different customers. But to date, we’ve been able to achieve data visas in almost every country in the world. So there’s been, yes, a benefit to having an operation in Canada, but it’s more about setting the business up strategically to capitalize on whatever your objective is and ours was to manage data. So we became subject matter experts in privacy, regulatory laws, and obviously deal with law enforcement on a routine basis.

John Stackhouse 00:17:09

Walk us through a bit more of how AI is changing the relationship with data. I think you’ve said that data is the DNA of an organization, but that DNA is evolving with AI. How should we be thinking about that?

Warren Roy 00:17:23

In a regulated organization, your record keeping applies generally to your voice data, to your social media data, and to all your electronic communications. And when we use the phrase data as the DNA of your organization, what we’re trying to say is that everything that you are is in that data. It has your strategy, it has your customer communications, it has your contracts, it has your marketing, it has most importantly, your relationships. And the relationships in business are what drive business forward in terms of winning prospects and so forth. So organizations, they want AI to be able to capitalize on that data. A record keeping company, as we are, has very structured data and structured data equals quality, accurate, and complete data. And those three words I use commonly because they’re the three words that you see in every subpoena that gets delivered. And our whole organization has been based on preserving quality, accurate, and complete data sets.

And I don’t want to dive into the technology, John, but if you can vectorize all of that data, which is what AI reads, if you can have an LLM interpret your natural language inputs commonly called a prompt and have a feedback loop of a couple of seconds, you can get to the point where you can have a natural language conversation literally verbally with your company. “Tell me how we did today. Who are the top performers? Are there any risks that I should be concerned about?” And when you start to understand these pieces and how they go together, you can see how one, it’s a very exciting business and two, that there’s a huge upside for the companies that capitalize on AI sooner than later.

John Stackhouse 00:19:12

So we’ve got a number of forces swirling together in the world, but probably two of the most powerful are AI as you mentioned and also the longer reach of the most powerful nations in the world as we become even more borderless in digital realms accelerated by AI. How should we be thinking about borders here in Canada but elsewhere when it comes to data and digital sovereignty?

Warren Roy 00:19:40

When I look at the world, you certainly have the two major powers putting everything they have into AI. It’s still done privately through private corporations, but the investments and the efforts are super human. You can choose to compete against that. It’s very tough. But to me, when I think about what’s going on, you need to be in the AI game. You want as a country to be in control of your data and you could boil it down to one thing. One of the key things with any government is to put a framework in place to allow businesses to be successful and at the same time boost the standard of living. And those two things encompass many different controls, but that’s really how you have to think about it. I think there’s huge opportunities in Canada for AI and just generally cloud services where we can have the autonomy we want and at the same time achieve the control and privacy that we need.

John Stackhouse 00:20:37

You’ve deliberately stayed in Canada, but you’ve also said that Canada is at risk of exporting our upside. Tell us what you mean by that.

Warren Roy 00:20:47

People think far too narrowly. It seems to me that success today in business is based on selling your company and measuring your win based on the value of the sale. I think it’s unfortunate that people think that way. I really feel that, John. And for us as an organization, I’ve always been focused on just trying to build the best business I could. Our largest customers are in the UK and France. So we’re well positioned globally to serve customers. And I think it’s also important to realize what is a global company and really the definition of that is that you can serve companies well around the world, which means 24 hours a day. So you really have to think through a strategy, defining success in your own mind and taking on partners which usually come in the form of outside capital that are aligned with your long-term vision.

And one of the really tough things that I see every day in the tech sector in most countries is they’re just all sold out to the top private equity firms typically where they are then taken and capitalized on. That is not a winning formula. And whether you address that through taxes or through other mechanisms, people need to think differently. The government needs to think differently. We need to support businesses that grew up in our country. I think that spells success for a far broader group of people than you could ever define by selling a business where simply a few capitalize.

John Stackhouse 00:22:21

You’ve had more success arguably outside of Canada than within, and maybe that’s good. That’s why you’re a global company. You’ve put the global into global relay, but you said that the UK and France are your two top markets. Now they’re bigger than Canada, so there’s some simple math there at play. But why have you done better in those European markets than in Canada?

Warren Roy 00:22:43

Well, when I look back over the past 25 years, it was only after we became quite successful outside of Canada that we did any significant business inside of Canada. And I think Canadians are just gun shy. They’re very conservative. But I also think at the same time, we have had a massive wake-up call in the past 12 months where we need to start looking within and capitalizing on our capabilities because I will tell you on the world stage, Canadians are very capable in almost any area in business and running a global company has a huge benefit to the country that is its origin. And I really would like to see more Canadians going abroad to drive their revenues.

The global markets are just simply huge, but today we have had some really good support from Canadian business, especially the Canadian banks and that’s great to see. It is hard as a startup to walk into government or a major bank and say, “Hey, could you buy my product?” Because there’s a big gap between your ability and their expectations. But in reality, when companies do start to become successful, you do need to support them.

John Stackhouse 00:23:59

What does Ottawa need to really come to grips with, both as a customer, as a regulator and through industrial strategy?

Warren Roy 00:24:08

Well, they have some tough decisions to make. You have our provinces and our federal government that are hardwired into US and other foreign technologies. There are successful Canadian companies, but there’s very little implemented when you look at the percentage of expenses that is pushed out into the technology sector. The vast majority of all of it is provided by foreign nations. Tech is complicated. It’s a big bet. And from a Canadian government perspective, you need to be able to reason your way through the right bets. And that doesn’t mean betting on everybody and that doesn’t mean throwing money at everything. It means choosing smartly, reducing the risk of your mistakes and partnering with some key critical companies that can really change the game, have proven that they can change the game on the world stage.

I have spent a fair bit of time in Ottawa in the last year, we’ve really put forward our case that we can deal with the scale of the federal government because we manage the data for some of the largest organizations in the world, but I’m sure there are a hundred plus companies like Global Relay in Canada that should be considered by the federal and provincial governments that currently aren’t. And part of it is you need to find champions within the government. It is full of people that are interested in doing the right thing that have the ability to do the right thing, but the bureaucracy itself is a challenge for everybody, whether you’re working within it or you’re trying to provide a service to it.

John Stackhouse 00:25:48

If we tackle those challenges, if we get it right 10 years from now, what do you think Canada looks like in the digital world?

Warren Roy 00:25:54

It is all about automation and efficiency. Canadians want a better standard of living and you can only achieve that if you can boost productivity. So from my perspective, I think the government and corporations can do far better at providing more efficient services if they can focus on automation and automation is really driven solely by AI. And with that automation, you should be able to downsize the government itself, reduce its overall expenses, and ultimately provide a far better service to Canadians.

John Stackhouse 00:26:32

Warren, it’s so impressive what you’ve built at Global Relay. Congratulations on that and thank you for being on Disruptors.

Warren Roy 00:26:39

Oh, it’s been a pleasure, John.

John Stackhouse 00:26:43

Data is quite literally the most valuable intangible in any organization and right across the economy. But when you go through a data centre, you certainly see the tangible side of what’s at stake. It’s not only the incredible machinery and all the power generation and cooling that’s required to make it run sustainably. It’s the growing requirements for security and redundancy in an increasingly complex and volatile world.

If you want to know more about these issues or hear more of these conversations, go to rbc.com/thoughtleadership or follow us on social media. And if you like this episode of Disruptors, please be sure to subscribe wherever you get your podcasts and give us a rating or a review that will help others find this conversation and share it.

This is Disruptors, an RBC podcast. I’m John Stackhouse. Thanks for listening.

Can AI fix ER wait times?

SPEAKERS

Mara Lederman, Amol Verma, Fahad Razak, John Stackhouse

John Stackhouse 00:00:09

Hi, it’s John here. If I ask you about Canada’s healthcare system, you probably don’t have to think too long about the answer. You might be grateful and, sure, you’re probably appreciative, but you probably also have a fair number of frustrations. This is a pretty familiar Canadian experience. We value our public healthcare system, we cherish the promise behind it, but healthcare in Canada involves a lot of waiting.

Earlier this spring, I had one of those experiences myself. A family emergency led to a long wait in a hospital emergency department. Now, everything worked out in the end, but I kept thinking about how common that experience has become. In that particular hospital, the first thing we saw when we entered the emergency department was an electronic board telling patients the expected wait time was seven hours and 32 minutes. Where else can you go where the wait time is advertised that boldly with no apologies?

Nearby, another sign asked patients to speak up if they did not want AI used during their visit. This May, the federal government released Canada’s national AI strategy and healthcare was the central priority. If you saw Prime Minister Carney roll out the policy, you’d have noticed by no coincidence he made the announcement in a hospital. And why not? Canada has a public healthcare system, world-class research talent, and hospitals generating hundreds of thousands of data points for every admitted patient. All that can help us develop better AI systems that can lead to better healthcare. But none of it, of course, is easy.

So on this episode of Disruptors, we look at the challenges from two sides. First, we’ll hear from Mara Lederman, an economist by training, and co-founder and Chief Operating Officer of Signal 1. It’s a Canadian health AI company working with hospitals in Canada and the US. Mara helps frame the pressure inside the system, rising demand, constrained supply, and the practical ways AI and technology can reduce wasted capacity.

Then we’ll hear from Dr. Amol Verma and Dr. Fahad Razak, two physician researchers connected to Unity Health Toronto. That’s the healthcare system built around St. Mike’s Hospital in downtown Toronto. They’ve built an AI infrastructure platform called GEMINI and are now helping lead VITAL, a more robust data infrastructure platform that aims to connect healthcare innovators across the country. VITAL just received a landmark federal investment of $100 million as part of a combined $200 million commitment that is the largest data innovation investment in Canadian history. Together, these platforms are aiming to reduce those horrible wait times that so many of us experience.

The opportunities here are twofold. There’s the operational challenges of wait times and then there’s the research that can lead to medical discoveries that life itself depends on. On both counts, Canadians want to be the world leader and here’s our shot to do just that. Here’s Mara Lederman. Mara, welcome to Disruptors.

Mara Lederman 00:03:19

Thanks, John. Good to be here.

John Stackhouse 00:03:21

I want to say actually, welcome back because we’ve had you on before and I want to kick off with that, Mara, because I actually can’t remember how many years it’s been, but we’re kind of talking about the same challenge. What’s going on in our hospitals that continues to lead to the levels of frustration that I think we all recognize across the country, even though we’ve all spent a lot on digital technologies over the last many years to ease those pressures?

Mara Lederman 00:03:49

I think we take a lot of pride in our healthcare system and our universal healthcare system. And then when you ask people if they feel like they’re getting good care, they’re not. And that’s not because we don’t have great research or great hospitals. I think if you ask any Canadian, they’re going to report being dissatisfied. Our ability to kind of give the average Canadian high quality care seems to be diminishing. We have a complete mismatch of supply and demand. We have incredible demand for healthcare. We have an aging population. They’re living longer with more ailments and more chronic disease. And so the need for healthcare, the demand for healthcare is growing. It’s effectively unpriced and we have a very constrained supply. And the simplest way to think about that is just sort of the number of hospital beds, the number of surgical spots, the number of procedure spots, and the number of clinical staff.

You go to an emergency department, you wait five to 10 hours. You need to see a specialist, people get booked six to nine months later. You need a quote, unquote elective, which is not really an elective procedure, but a non-emergency. You often have to wait months. And the way we’re going to do it is not just going to be by building more hospitals, staffing more beds because we simply can’t afford to do that.

John Stackhouse 00:04:54

And yet we are building more hospitals and trying to hire more doctors and nurses and there’s a logic to that. Why hasn’t digital technology particularly not made a greater difference over the last decade?

Mara Lederman 00:05:08

One of the benefits of adopting technology is it is supposed to make us more productive. What does it mean to be more productive? It means we can kind of generate more outputs with the same inputs, right? So in healthcare, you’d like to ask, how do the same sort of resources, when armed with technology, allow us to create more units of care? Probably the biggest digital technology to hit healthcare is the electronic medical record. The EMR is basically a system of record. It’s not a system of action. So there aren’t a ton of examples where you are busy clinical teams with another piece of technology often on top of the EMR and find that they can just do so much more.

John Stackhouse 00:05:48

That’s the pressure point. Demands keep rising. Supply can’t expand quickly enough and a decade of digital investment just hasn’t made the system move fast enough. At the same time, healthcare is generating more data than ever before. The problem is that too much of that data stays trapped inside hospitals, inside provinces, inside systems that were not built to learn from one another. That’s where VITAL enters the story. Amol and Fahad, welcome to Disruptors.

Amol Verma 00:06:16

Thanks for having us.

Fahad Razak 00:06:17

Great to be with you, John.

John Stackhouse 00:06:18

You’ve had an incredible busy couple of weeks now that you’re center stage in AI in the country in a very positive way. I want to start with a better understanding of VITAL. Amol, let me start with you. Take us through the VITAL story.

Amol Verma 00:06:34

The heart and the core insight and focus of our work is that healthcare does not use data very well. We don’t connect data across our healthcare organizations, and we don’t use it to inform good decisions, to develop solutions that can improve the way healthcare is delivered, and to use it to enable large-scale cutting-edge research and innovation. And so we’ve been working for about 10 years in Ontario on a hospital research network that we named GEMINI before Google showed up on the AI scene with their Gemini model and that connects hospital data now from about 45 hospitals, that’s about 60 to 70% of the patients in Ontario and makes that available for all of those different applications, quality measurement, research, innovation in healthcare. And what VITAL is doing is taking the work that we’ve built with GEMINI and really accelerating it and scaling it larger. So essentially saying we can connect hospital data at large scale across Canada and we can make it much more timely, and make that available so that we can support research and innovation to bring new solutions, new technologies, new investments into healthcare.

John Stackhouse 00:07:41

Walk us through GEMINI and how that connects with  VITAL.

Fahad Razak 00:07:44

So GEMINI was started roughly 10 years ago and the digitization of data, very different state than what it is today. So most of the chart of a patient admitted to hospital was handwritten, printed. It was in binders in the nursing station. 10 years later, almost all of information that’s relevant is now digital. So GEMINI was capturing that progressive digitization over that 10-year period. When we started to look at the world though the last couple of years, we saw that even though GEMINI was at best in Canada capacity, it really wasn’t competitive. What we were seeing in the Nordics, a place like Denmark as I think is the exemplar, the United Kingdom in terms of their ability to harness that kind of digital data at scale and use it for trials for artificial intelligence.

And just to put this in context, we’re both practicing physicians. Every patient that we admit to hospital now, we are generating hundreds of thousands if not millions of data points just to provide care. So it’s the lab tests, it’s the MRIs, it’s the digital vital signs. That data is extraordinarily important for artificial intelligence and for clinical trials and we were seeing these other countries developing population-wide capacity essentially to get that data, to use it very quickly under really good governance, legal protections for broad innovation use cases. And that was not possible with the GEMINI model. And so VITAL was a proposal to kind of leapfrog to push forward to say, “We need this at scale for the country. We need to be as competitive or better with the best-in-class we’re seeing globally.”

John Stackhouse 00:09:13

So that gives us a good sense of the infrastructure and the data. So taking us into 2026. One of the many challenges here in Canada is that healthcare is provincial. And I think you were just with deputy ministers from the provinces walking through what this new national infrastructure can do. Great in theory, but we all know the challenges of getting anything across provincial borders, including data, including doctors, including other aspects of healthcare.

Fahad Razak 00:09:42

Yeah. So I mean, let me start with your first point, John, which is the governance and political structure of Canada has made this kind of collaboration difficult. So a reasonable question is why is today any different? And I think today is different for two key reasons. The first is that we are under enormous geopolitical pressure. The use of this kind of data at scale for the country is an important value proposition where Canada can be truly competitive. We have to harness as close as possible the data of 42 million people, again, responsibly with the highest levels of privacy protection, but at that scale. If we are able to do that, there is a competitive advantage that we have at scale and that is that we are a single-payer system from coast to coast. So we don’t lose people like the United States does who don’t have insurance in their datasets.

And we are the most diverse high income society on earth. And that means that if you do your science here, if you do your AI algorithm here, your clinical trial, it’s intrinsically better than if you do it in a homogeneous population than Denmark, for example. We look more like the world than any other country. So the algorithms are just fundamentally better if done here. The second important advance is what’s been the rise of federated analytics. The data of Alberta today and five years ago, we can’t just move that data into Ontario. That’s not allowed. That had been a barrier five years ago to doing this kind of analytics, let’s say developing an AI algorithm or running a clinical trial, but we have the analytic structures that can run and develop an AI algorithm across these provinces and territories without actually moving their data. The algorithm optimizes in each jurisdiction and it keeps optimizing and rotating until it converges, as an example.

So you have a technology solution, you have the geopolitical pressures, you have the recognition that no single jurisdiction is big enough to really be competitive and that you’re seeing the offshore of the opportunity. So what is physically left Canada? An early cancer screening trial has gone to the United Kingdom. The best new vaccine trials are going to Denmark. And I think over the next three to five years, you will see some of those trials and AI developments come back into Canada because the combination of the structure that VITAL offers and the competitive advantage of our population, population dataset, size, diversity means we become a best-in-class jurisdiction to do work.

John Stackhouse 00:11:56

That’s the national infrastructure story. Connect what has been fragmented, protect the data, and turn Canada’s health system into a platform for better care, faster research, and better tested AI. But for patients who are still waiting, the question may be more immediate. What can AI actually do for me right now? Mara Lederman points to one simple example.

Mara Lederman 00:12:18

With the rise of GenAI and agentic AI, we’re seeing a whole nother set of applications, many of which aren’t yet patient facing and many of which aren’t even physician facing that are leading to efficiencies. Many of your viewers, if any of them are over 50, have had a colonoscopy, right? It’s an unpleasant experience. We all know that. And if you’ve gone through it, you know that there’s a whole round of prep you need to do in the days leading up to your procedure. You get detailed instructions about various medications and foods you need to stop eating or taking up to a week before. If someone doesn’t follow their preparation, what happens? They show up at their appointment, they get asked if they did the preparation or if they stop their iron pills, they say, “Oops, I forgot to do that.” They get canceled, no one gets a scope, you don’t get anyone off the wait list and it’s just a wasted opportunity.

So one of the health systems in the US has built an AI agent that automates these pre-procedure phone calls. And what it does is it calls everybody a week before, it goes into their medical chart, it pulls their list of medications. It says, “Here are all the medications you’re on. These are the ones you need to stop. Here’s a reminder about your prep. Here’s a reminder about when you need to come.” And it can do this for everybody. And then after these phone calls happen, a different AI reads the transcripts and flags any that feel they need to be redone by an actual nurse and the data shows more people come prepared, fewer scopes are canceled, fewer unused opportunities. So from a quality perspective, it’s better for patients, from a staff perspective, they’re not standing there with no patient and from an access, you’re not wasting opportunities to move someone off the list. So simple example, and it’s not that high risk.

John Stackhouse 00:13:57

That example shows what AI could do at the edge of care. Fewer wasted appointments, better follow up, fewer avoidable returns to the emergency department, and more support after a patient leaves hospital. But in healthcare, promising is not enough. We need to know whether these tools actually work and whether they work for Canadian patients in Canadian hospitals across Canadian communities. That brings us back to VITAL.

Amol Verma 00:14:22

AI is at an exciting point in its inflection. We need to run clinical trials on AI tools and we need a capability to do that. And the capability required to do that is an integrated digital infrastructure because unlike a medication where you work through a pharmacy, you dispense the medication, there’s a structure and infrastructure already in place for all of that. What we don’t really have the infrastructure in place for is the digital dissemination of these AI technologies. The second important application of AI in the context of clinical trials is AI can make it much more efficient to run other kinds of clinical trials. Large scale clinical trials historically have been a very expensive proposition. The average cost of a phase three clinical trial, which is what you need to get regulatory approval to bring a new drug to market is 21 million US dollars for a clinical trial.

If we can make that more efficient, we can create an extraordinary opportunity to bring new technologies faster to Canadians and make these kinds of technologies available to more people and AI can help us do that. It can help us do that by one, making it easier to collect the data you need to tell if a clinical trial was effective or not. A lot of that data is already gathered in our healthcare system. So rather than phoning up a patient and saying, “Did you end up back in the hospital?” We can just gather that information routinely to measure the outcomes you need to, to study a clinical trial.

The second piece is it can make it easier to identify which patients are eligible for clinical trials. So a big cost in clinical trials is identifying eligible participants, recruiting them into a clinical trial. AI can help us look at all of the health record data and identify which patients might be eligible and then we can work through typical processes with patients, care teams, and otherwise to try to make those trials more available to people. So lots of opportunities for AI to improve clinical trials and for clinical trials to improve AI.

John Stackhouse 00:16:12

Trust underpins all of this. And as we were discussing earlier, trust generally has declined when it comes to AI, especially here in Canada as well as the United States. How are you thinking through the trust barrier in rolling this out?

Fahad Razak 00:16:27

Yeah, I think it’s a problem that Canada is actually in quite a deep deficit around, as you said, John. So we know from surveys that in fact, the Canadian population’s trust of AI and worry about AI is actually higher than many other countries. And I would say the first point to make is that there are good reasons to be worried about AI. And so I do think that we have to be very cognizant and respectful of these worries and say, what is our solutions? What are we specifically doing? So let me talk about a couple of them. The first is whose data is being used under what permissions? We have a precedent in this country. The kind of data that we are talking about has already been used for generations really in this country in highly respectful protected ways that protect individual rights that allow opt-outs if people don’t want to be part of these innovations, that have layers of protection to anonymize around who an individual is.

We’re talking about using these aggregated parameters to develop an AI algorithm in a way that is consistent with the historical accepted pattern of the use of this kind of data in the country. However, there are some particular nuances around AI. There are ways that AI can develop an algorithm that can unmask an identifier. I think we need to be upfront about recognizing what those algorithms potentially can do, making sure that those edge use cases, not the majority of AI, but those edge use cases are ones that we are particularly careful around because I do think that we’re starting with a very understandable level of distrust and we can’t allow that deficit to worsen. So the second is that again, we are the most diverse high-income society on earth. We know from other AI deployments that these algorithms will anchor and tailor and optimize very tightly to the population they’re developed in.

So if you have an AI algorithm developed in a Nordic country, which is 95% homogeneous and you try and deploy it in Brampton, Ontario, or in Northern Ontario, or in the none of it, the chance that it’s going to work as well or even approximate as well as what they initially claimed is probably pretty low and people will pick up on that. And I think we need to be very careful to ensure that these algorithms are being deployed in our population in a way that is fair, and unbiased, and actually shows benefit.

And the third important thing is I was quite struck that the government decided to lead their AI strategy with health. Even a year ago, health may not have been one of the main pillars of an AI strategy for the country. I think it is more than just symbolism. If you speak to the Geoff Hintons and the Richard Suttons and others, they will say that of all the areas where they are worried about AI, health is probably the most important sector where they think the benefit can far exceed the risk.

The ability to detect disease early, to provide more nuanced diagnosis, that is things that people can appreciate day-to-day in their lives. I had a cancer diagnosis detected before I otherwise would’ve because of an AI algorithm that was able to pick it up in the imaging processing of my mammography. So I think as people rightfully have concerns around AI, health could be a really important sector where we can show benefit early, but we have to do it in a way that’s respectful about privacy, about bias. So I do think it’s a very important area where people actually can see real benefits in their lives.

Part of it is also a broader consideration of risk and benefit and how we think about each sector. So let me just use an analogy. I’m in downtown Toronto. I get onto the gardener in my car and you’re in a metal box with a strip of cloth over your chest driving 100 kilometers an hour at each other. We do that every day and we tolerate the risk because we have a destination and not because it’s fun to be on that road. With health data, if the entire conversation is risk containment, you are essentially boiling down your speed limit to zero kilometers an hour. So these technologies have the potential to get us to better outcomes, to better diagnosis, to more efficiency, but it’s not risk-free.

I think we need to have a conversation about tolerating some level of risk, being very disciplined and transparent where we make mistakes, and iteratively getting the safety systems better. Cars today are infinitely more safe than they were 50 years ago. That’s because we’ve iteratively made them more and more safe. There are going to be accidents, disclosures, biases that emerge. Let’s talk about it. Let’s say this was a problem. Let’s make it better. And over the years, we will see a system that is more and more safe, that has more and more guardrails, but importantly gets you where you need to go.

John Stackhouse 00:20:45

The risk conversation matters, but there’s also a risk in standing still. If Canada does not build this capacity, trials go elsewhere, AI tools get trained somewhere else, and Canadian hospitals will have to import systems designed for other populations. And in the end, patients could just end up waiting more in a system already under strain. That’s why Mara Lederman argues this should be treated as a necessity.

Mara Lederman 00:21:10

First of all, I don’t think we should call it the Canadian opportunity. I think we should call it the Canadian necessity. We started this conversation by talking about the health system being in crisis and that we aren’t going to kind of build or hire our way out of it. As long as we call it the opportunity, it feels like pet projects and innovation and we should just say there’s an absolute necessity to use technology to make healthcare sustainable. At a high level, we need to push as much care as possible into the lowest cost setting where it can be delivered. It seems like a simple thing to say, but the default is to do most stuff in hospital. Think about all the care that became virtual during COVID that nobody thought was possible before, even virtual nursing.

I was just with a company last week who’s putting sensors and cameras in patient rooms. All the data’s computed on the edge so there’s no privacy issues, nothing is stored and they are cutting down on fall risk and adverse events that happen in a hospital room that otherwise humans would’ve had to supervise. A lot of US systems have virtual emergency departments where you first even just get triaged online before you even show up in the emergency department. We’re seeing the growth in the US of what’s called ASCs, ambulatory surgical centers. So how many surgeries can be done outside of an acute care hospital as opposed to an inpatient hospital?

AI is not the only answer, but more and more I think we have fallen into the same model of thinking: that most care is delivered in a doctor’s office and if not in a hospital. And the reality is, with the technology we have now, we can do more. And so if I were to focus our country on one thing first in terms of the opportunity, it is asking how we use technology and sort of associated changes in incentives and coordination to always ask, are we delivering this care in the lowest cost setting?

John Stackhouse 00:23:01

Mara, thank you for being back on Disruptors.

Mara Lederman 00:23:04

Thank you for having me. It was fun as always.

John Stackhouse 00:23:07

Care in the lowest cost, safe setting means different things in different places. You can start to imagine AI-assisted tech being deployed and connected across our country, allowing emergency rooms to regain capacity. But also in remote communities, it may mean not needing to travel hours or fly just to get care that could be monitored, managed, and supported closer to home. Healthcare really is the critical testing ground for AI and whether it can deliver meaningful benefits for everyone. What should Canadians expect to see over the next, let’s say, year?

Fahad Razak 00:23:44

I think the one-year outcomes are going to be the introduction of technologies that we’ll be testing and evaluating using this infrastructure. So you’ll see things like, are we going to use an AI prediction algorithm to, let’s say, detect heart disease, to detect viral outbreaks as they’re occurring? These are underway and being tested by our network right now. The reality is as much as we’re optimistic around AI, it’s not magic. So it’s going to require the evaluation and testing that we historically have done for a cholesterol pill, for a cancer therapy. We have to test and evaluate. Those tests are already underway. So if you’re in communities that VITAL stretches to in Alberta, and Ontario, and Quebec, for example, you’re going to see these algorithms start to be rolled out, but it’s under evaluation phases. Again, we want to make sure that both the access to these technologies extends out to Canadians, but it’s done in a way that’s safe and under evaluation.

The announcement last week by the federal government was an additional $ 100 million investment in the VITAL network. To our knowledge, this combined $ 200 million investment is the largest in Canadian history now in this kind of data innovation. That’s about getting it out to the rest of the country. So in the next year, I think you’ll see it extending out to these three provinces, 50% of the country. In the years that follow, year two, year three, you’ll see it getting out to more and more provinces and territories. Again, we don’t want to overpromise, but the idea is we’re going to choose the best of these algorithms. Get them out there, test them, evaluate them, get them out to people, but also watch very carefully to make sure that they’re working well.

John Stackhouse 00:25:10

Fahad, Amol, thank you for being on Disruptors.

Amol Verma 00:25:13

Thanks for having us, John.

Fahad Razak 00:25:14

Such a pleasure. Thanks, John.

John Stackhouse 00:25:17

There’s a lot of government money going into AI, but that doesn’t guarantee outcomes. It does change the scale of what’s possible. Canada has enormous pools of healthcare data. The challenge now is building the infrastructure, trust, and operating capacity to turn that data into better care. VITAL now has the mandate and the resources to extend to Alberta, Ontario, and Quebec within a year and to reach more provinces and territories after that. The national AI strategy put healthcare on center stage. This investment is the follow through. AI in the ER is our new reality and we’re about to see just what kind of difference it can make.

You’ve been listening to Disruptors, an RBC podcast. Follow us wherever you get your podcasts. And be sure to share this episode with someone thinking about the future of healthcare in Canada. That will help more people discover this kind of conversation.

For more RBC thought leadership on AI, healthcare, productivity, and Canada’s innovation economy, visit rbc.com/thoughtleadership. I’m John Stackhouse. Thanks for listening.

Can AI fix ER wait times?

SPEAKERS

Boris Wertz, Sid Paquette, John Stackhouse

John Stackhouse 00:00:10

Hi, it’s John here. If you’re a regular listener of Disruptors, you may have heard a recent episode with Fred Lalonde, the founder of Hopper. He’s one of Canada’s most successful and interesting entrepreneurs. It’s worth a listen. Among the things Fred shared was a need for any Canadian innovator or technologist to reach global scale in a hurry. Well, to do that, you also need global capital, or at least scale that thinks like global capital.

And today, we’re going to hear from two of Canada’s most successful venture capitalists on what they see as the opportunity and the need to support and finance a whole new generation like Fred to carry Canada into the 2030s.

You’ve probably heard enough about the problem. Yes, we can produce important technology. We’ve helped shape artificial intelligence, quantum software, health technology, and emerging areas like physical AI. But when companies move from promising startup to global contender, that’s when the challenges really thicken.

That’s the tension at the center of this conversation. Canadian companies need global investors in global markets, but if the growth rounds, anchor customers, senior talent, and exit pathways all pull elsewhere, Canada risks losing too much of the long-term value from the very companies that people like Fred create here.

Today on Disruptors, I’m joined by Boris Wertz. He’s the founder and general partner of Version One Ventures, and Sid Paquette, who’s the head of RBCx, our innovation banking arm, to talk about Canada’s growth capital gap, what founders need to compete globally, and how Canada can build more technology champions for the world from Canada.

Boris, Sid, welcome to Disruptors.

Boris Wertz 00:01:55

Thanks for having us.

Sid Paquette 00:01:56

Thanks for having us.

John Stackhouse 00:01:56

Let’s start with the challenge out there. You’ve both been around the block more than a few times. You’ve seen highs and lows in venture in Canada. Boris, how would you describe the current landscape?

Boris Wertz 00:02:09

I think, in many ways, we have made a lot of progress in the innovation economy and venture capital in Canada over the last decade. Having said all that, we are also at a moment in time where, with AI, everything is shifting again. New ecosystems are emerging. New venture capital players are emerging. And this is really a moment in time where, going forward, we play a really important role in the innovation economy, and that often starts with capital.

John Stackhouse 00:02:35

Sid, on the finance side, the numbers are concerning. We are well down as a country. What’s going on out there?

Sid Paquette 00:02:43

Yeah. So there’s not one area within the ecosystem that doesn’t have problems today. Right? If you take a look at the data the last three years, emerging managers have raised 36% less than expectations. That’s really bad. You take a look at venture capital last year. The data shows that 83% of all venture capital dollars raised last year went to five managers in this country. That’s not a good situation, especially when you look at the prior year with 67%.

So we’ve got an issue across the entire finance life cycle, and there’s a bunch of things here that we need to do. We don’t have big enough growth equity players domestically to help fund these great Canadian companies. Having spoken with a lot of CEOs of these great growth-stage companies in Canada, it doesn’t feel great to a lot of them when they’ve built a company. They’ve built it here in Canada.

They’re Canadian, and they look at their cap table, and it’s a de minimis amount of Canadian investors, especially when you consider that every single taxpayer in this country has ultimately funded most of these companies through their entire life cycle through the SR& ED program, which is taxpayer dollars, which is every single company in tech largely makes use of that program.

John Stackhouse 00:04:06

This is the research and development tax credit.

Sid Paquette 00:04:07

This is the Scientific Research and Experimental Development Program. Exactly. So refundable tax credits to ultimately help these companies grow. As taxpayers, we’ve funded that. Certainly at the early stages when it’s really highly risky, these organizations have a higher rate of failure than they do success, and that’s when we all step up as taxpayers, as we should, and we help them navigate those waters.

When ultimately they get to a less risky stage, late-stage capital, that’s when then, all of a sudden, we don’t have any domestic players who can come in. So the company is at a less risky stage of their growth. There’s no domestic capital or not a lot of domestic capital to help them grow, which means then it’s far more foreign capital that comes in, which means the lion’s share of a lot of the benefit, whether it’s talent, attrition, or its capital on an exit, exits the country. Right?

And so, that’s not a great situation for us as well. And so, certainly at the late stage, it is not a lack of capital. These companies, they’re really good companies. They can get capital anywhere they want in the world, but it is a lack of domestic capital.

John Stackhouse 00:05:17

Take us deeper, Sid, and then, Boris, in terms of why there is not those stages of capital, because we did this report called Capital Gains that looks at the trillions of dollars that Canada needs, 1. 8 trillion to be specific, but that’s largely for resource development. Canada and Canadians may not appreciate this as actually one of the world’s best pools of capital.

Sid Paquette 00:05:40

We have a lot of big capital pools here in the country. Right? Our pension plans, our large corporates, et cetera. But by virtue of the size and scale of those capital pools in order to move the dial on their investment strategy, they’ve got to be able to deploy really, really big pools of capital as well, and Boris talked about it in terms of what’s happening with AI and the changes in our ecosystem.

You can build companies now far more efficiently with far less capital outlay and drive far greater amounts of revenue than ever before in history. And so, you don’t need all that much. You do need capital, but you don’t need as much historically as you used to. So then where that shifts, and this is in tech, where that shifts is, when you’ve got these large capital pools, they end up looking at more infrastructure-type investments. Right?

John Stackhouse 00:06:27

Like data centers.

Sid Paquette 00:06:28

Data centers. It could be anything to do with infrastructure. It could be building highways. It could be airports. It could be ports, whatever it is. Those are big investments that they can make. They can deploy off of a bigger balance sheet. Tech kind of falls to the wayside a little bit, but we’ve got to solve for that problem, because Canada is historically a resource economy.

We just can’t take a finite resource out of the ground, send it somewhere outside of Canada to be processed, buy it back at a premium, and then ultimately all of us consume it. That’s not a sustainable business model in any world. Right? And so, we’ve got to start solving for that. So there are infrastructure things here that we need to invest in to drive those outcomes, but then we’ve also got to go, “Hey, let’s think about what’s happening on the AI side. What is the potential that’s going to be there?”

We do not, today, have any sense really in terms of the business model changes that are coming down the pipeline, the opportunities that are coming down the pipeline, the talent requirements that are coming down the pipeline. These are things we have not seen. And so, for those of us who have been around for a bunch of these changes, whether it’s the internet or it’s the cloud or now it’s AI, there are roles that individuals…

There are opportunities that are going to be solved with software that we just don’t even have visibility to today, and this is moving so fast that it’s going to come to us really quickly. We’ve got to start thinking about the art of the possible, and we got to think about the world that we live in today is going to be very different tomorrow.

John Stackhouse 00:08:06

And I think, Boris, this is what you were getting at off the top in your reference to AI and how it is leading to a massive concentration that is obviously a big opportunity for those who have that ability to scale very quickly.

Boris Wertz 00:08:20

Yeah. I think we’re really entering a world where we’re going to see exponential growth in some of these companies, and that’s going to lead to more outlaw outcomes. Right? More value being accrued in the top 1% of all companies. So I think before, tech was always, in a certain way, nonlinear, but I think we’re now hitting a real exponential phase, and that will just create more concentration in fewer assets and fewer founders and fewer companies, and fewer VC funds.

And I think we just have to be clear that it’s a different phase of development, and we can’t really play the game that was perhaps appropriate a decade ago in a new phase that is now driven by AI and exponential outcomes.

John Stackhouse 00:09:03

How does a smaller country like Canada take on that epic challenge? It makes me think of the hegemons, as Prime Minister Carney likes to call them, but we’re seeing in AI. It is the U. S. versus China and then a whole bunch of other countries back in the peloton, and Canada is one of them. Do we just accept our place back there well behind the leaders, or is there a way to jump ahead?

Boris Wertz 00:09:27

I think Canada is starting to kind of recognize that we can’t just continue what we’ve done in the past. We need to change our playbook. We need to lean into our strengths. A country of 40 million people can’t be great in every single sector, but there’s many where I would say we have a real advantage. Energy is one of them. Mining is another one. When you think about the whole AI boom, it really comes down to ultimately energy as the input.

Sid Paquette 00:09:52

Just to jump in on that comment, I think we’ve just got to make sure that we don’t get overwhelmed by the volume of things that need to change in this country. We’re not going to solve every problem, and we can’t solve every problem given the size of our country. In some cases, it may be 10 years before we’re able to have the outcome that we would like to have had already, but if we don’t start today, every day is an extra day that we add onto a 10-year or 20-year cycle. We’ve got to lean into our natural strengths. This is looking at what we’re really good at today and where we’ve got some commonality and some natural aggregation of skills, resources, capital, and leaning into that.

John Stackhouse 00:10:36

So tell us a bit more about what our natural strengths is. If you had to bet on one thing, what would it be, and how would you execute on that bet?

Sid Paquette 00:10:44

Energy. That’s a strength of ours. Right? We’ve had that strength. We’ve had that for a long time, but there’s other strengths that are coming out of the woodwork now. If I think about a recent strength of ours globally, quantum is one of them. That was not an initiative to create a quantum center within Canada. That was just a gravitation of really smart people in this country working on a problem set, and you’ve now got this cluster that’s just naturally happening. AI obviously is another one that we’ve had in recent years as well.

John Stackhouse 00:11:14

Boris, help us understand how we fumbled.

Boris Wertz 00:11:17

AI came out of Canada, and not only one place, but literally Toronto, Montreal, Edmonton. So we had a really strong research history, but ultimately, we didn’t really have enough of an ecosystem where companies in that ecosystem took the new research, commercialized it, scaled it up. At least I would say, today, we have, with Shopify, actually one at-scale tech company that is very advanced in AI and applying it in their own business, but it’s obviously nothing compared to what you’ve seen in the Bay Area with Google and Meta and OpenAI and Anthropic and so on.

John Stackhouse 00:11:53

And I think in the case of Shopify, the main reason it’s still here is Tobi and maybe some others, but that is a leadership decision, not a natural advantage of Canada.

Boris Wertz 00:12:05

100%. 100%.

John Stackhouse 00:12:06

So thank you, Tobi.

Sid Paquette 00:12:07

I agree. You’ve got the Wessingers at PointClickCare. They’ve built a really big company here. You’ve got Jane. You’ve got Clio. You’ve got Xanadu. He’s probably the most Canadian non-Canadian I’ve ever met, wants to build a company here in Canada. And so, you do have these examples here. This is a great place to build. We’ve just got to put the right resources around these entrepreneurs to enable them to build really big companies. We can do this in Canada.

John Stackhouse 00:12:37

So let’s talk about what would help on that front, procurement. What do we learn from others on procurement that we could apply better here?

Boris Wertz 00:12:45

It’s both procurement from private companies as well as from the government. Canadian private companies haven’t really been praising new technology, being the first customer, et cetera. So I think we need to have a change in culture there, embracing technology. It has been very tough to sell to the Canadian government. We need to be just much more aggressive in leveraging procurement from the government, from private companies to get these early-stage companies and later-stage companies real revenue traction that they then can fundraise against and raise more private capital against.

Sid Paquette 00:13:16

Yeah. I agree. I think another big unlock here in Canada is on the private companies. They often don’t even consider Canadian companies in an RFP process for a particular software deployment, hardware deployment, what have you. They just go to the name that they know that they’ve done some research on that maybe Gartner or Forrester has highlighted without even looking at Canada, and I think that’s a mistake.

Canadian companies will not necessarily win out day-to-day against a U. S. competitor or a foreign competitor, but in Canada, we’ve got to give them an opportunity to at least be at the table, because most times, you are as good as the foreign competitor, and you’re based here, which means you have better connectivity with the client here.

You’ve got a team here. You’re more accessible here. There’s a lot of really good things there, and they don’t even get that access. So it is a behavior change, which is, ask the question, if there are no Canadians in an RFP process, that should be a red flag to go, ” Hey, have we really scoured the market here to see if there is a Canadian company which should be in this process? And let’s invite them in.”

John Stackhouse 00:14:25

How do you change that? Because I’ve heard this challenge for years and years.

Sid Paquette 00:14:29

This has to come from the top. This has to come from senior management teams. This has to come from boards of directors. This is not going to be a grassroots, bottom-up change. This is behavior change, which I believe behavior change, we have to reflect that at the top of the house at the executive level.

Boris Wertz 00:14:44

Yeah. You definitely see it like a change of behavior in government. I mean, it’s still early, but you feel like there’s first really important signals that government is thinking about being much more aggressive around procurement and opening up government to these opportunities.

John Stackhouse 00:15:01

One of the levers that we may be missing is sophisticated VCs, especially on the go-to-market side of it. So I hear from entrepreneurs, both of you have introduced me to many of them, who will say, sure, they’d love a Canadian as their lead investor, but if you have Andreessen Horowitz or pick your Valley investor, it’s not about the money. It’s about the talent that they have. And frankly, they’re going to ensure that you are getting in front of all the right corporates in the United States, probably beyond. How do we solve for that in Canada?

Sid Paquette 00:15:35

In the U.S., they have a process that they have been executing that playbook for a long time, and they understand when they make an investment, they’re committed to that investment, and they’re going to do everything they can to make that investment successful. They also have far more at bats than we have here in Canada.

They’ve had more successes. They’ve had more failures, which they learn a lot from as well. Let’s be frank, they’ve got a far bigger talent pool for all of the requisite talent that we need. There are really good reasons to take U. S. funding, and I am not a proponent of Canada-only funding rounds. Right? I actually think that’s a bad way to build a business.

John Stackhouse 00:16:12

Why is that a bad-

Sid Paquette 00:16:36

I just think, John, I think you lose access to networks that you’re not connected to. You lose access to talent you’re not connected to. And quite frankly, you lose access to markets that you’re not connected to. A cap table for a large, successful Canadian company shouldn’t be 5% or 10% Canadian ownership. Should it be 60%? I don’t think so, but it’s got to be somewhere in between, and it helps that company scale.

You’re going to go where you can get talent, where you can get customers, where you can get capital. There’s a lot of benefits to that domestic capital as well, but I’m a proponent of actually both. I don’t think just taking Canadian capital is a smart thing, not if you’re building a global franchise.

Boris Wertz 00:16:54

Ultimately, the Canadian VCs that want to be successful need to be globally competitive. You can’t just build your business on Canadian deals in the Canadian ecosystem, and we actually have a bunch of them here in Canada that are globally successful. We just need way more of them.

John Stackhouse 00:17:11

And you’re one of those successes, Boris. What has helped with that?

Boris Wertz 00:17:15

It’s two things. The first one is realizing that the world is much bigger than just Canada. You need to recognize what great looks like. And then secondly, it just means you have to be on the road a lot. I mean, you just can’t just run this from Vancouver or from Toronto. You need to be in the Bay Area, in New York all the time, and just need to put in that time to connect with the best in the game, meeting great founders, really understanding what needs to be done.

Sid Paquette 00:17:45

Can I comment? Because I’ve known Boris a long time. And so, maybe I’ve got an add-on I’d like to just make in terms of Boris’s success. Boris and Angela have done a phenomenal job at Version One of investing ahead of the hype cycle, coming in, identifying opportunities early, investing with conviction in those opportunities, and then those tend to be the ones over time that have the biggest return.

You’re doing it long before everybody is interested in it. You’re kind of setting the path in a lot of ways, and you’re almost acting like a queenmaker or kingmaker fund at the seed stage, because nobody else is investing in that space.

John Stackhouse 00:18:25

So, Boris, if that’s true, where is the next hype cycle?

Boris Wertz 00:18:30

Two things are always on my mind. I think the overlooked opportunities are getting rare and rare. It feels like whatever is an emerging category is perhaps there for half a year and a year and then it becomes almost mainstream. The innovation cycles are much, much faster. So you have to look harder, and you have to change your themes much, much quicker. The thing where we spend quite a bit of time on right now is physical AI and bio actually. We think at the intersection of atoms and AI, and that includes both biology as well as robotics. It’s a really interesting area.

John Stackhouse 00:19:08

Tell us a bit more about physical AI. What is it, and where are you seeing the opportunities?

Boris Wertz 00:19:14

Physical AI is very different, because the real world is messy. Right? Every manufacturing floor, every logistics center looks slightly different. Right? And so, data collection is going to be much more use case by use case, factory by factory, and making that work is much harder than scaling up a foundational model based on all the data that’s available. So we’re interested in that messy world. Biology is a similar theme. The human body is very complicated. There’s never perfect data collection. So we feel like the combination of AI and a much messier data collection, use case-specific application is super interesting.

John Stackhouse 00:19:58

I wonder in our remaining minutes if we can talk a bit about what Canada should do in the coming months and maybe years. Clearly, we’re coming to grips with our existence as a country and what we want to be. All this is going on while we have tons of billions of dollars coming into the country, staying in the country, looking for opportunities. We’ve got to also think about building the little companies that become big companies. So amazing time to be in business, to be in investing. What should we come to grips with in the near term to make all that possible, Boris?

Boris Wertz 00:20:31

I would love to see a culture shift in Canada. Canada has been known for building amazing companies, being really entrepreneurial, and we lost it a little bit in bureaucracy and regulation and just taking it for granted that our economy would work. We just have to go back and be more entrepreneurial, and that starts with obviously government embracing that, big companies embracing that, individuals embracing that. Now, we need to kind of double down and start building again, not just harvest what past generations have built, but really build for the future.

John Stackhouse 00:21:03

And how would you design venture capital, especially government interventions as well as corporate interventions, to be more effective in the decade ahead than maybe we’ve seen in the past?

Boris Wertz 00:21:14

I think we need to unlock a lot of the private capital that we have in this country, the pension funds, hundreds of billions of dollars that are there in terms of assets. We need to make sure that part of those assets are going to flow into the innovation economy. I’m not a big fan of just having government- sponsored programs, but there’s lots of private capital that is there, sitting on the sidelines, that we need to kind of activate.

John Stackhouse 00:21:39

Sid, what would you do in the next six months?

Sid Paquette 00:21:42

Wow, six months. I think we just have to start, and I say that not flippantly. There are a lot of things that we have to solve for, and we’re not going to solve for all of them, and we’re not going to get them all right, but we’ve really got to think about what do we want this country to look like in 10, 20, 30 years, and we’re going to have to make the investments today to make that happen, and we haven’t made those investments probably for the last 30 or 40 years.

We’ve got to fix the capital allocation issues that we have across the ecosystem. We’ve got to support the companies that are naturally building companies here. We’ve got to provide the fertile ground to enable others to continue to build. We’ve got some of the biggest organizations in the world in this country. How do we leverage them to help those who are building feet on the street build the next generational company?

We’ve just got to start, and we’ve got to just start chipping away at some of these problems. That’s what I would do in the next six months, and that’s what we’re going to continue to collectively do, because a number of us are working on a bunch of these things.

John Stackhouse 00:22:47

Now, maybe a final question. You’re both investors, and one of the things I love about investors is they believe in the future. That’s why you invest. What are you most excited about in the future? Sid, start with you.

Sid Paquette 00:22:58

The world that we’re in today, it is a moment, and it is a moment that we don’t fully comprehend today. I am excited for what I actually don’t know about the future, and I know that’s maybe not the answer you’re looking for, but it’s the reality. And I think anybody who thinks they know what this is going to look like five years from now, I would question that we actually do, because I don’t think we do.

There’s a lot of unknowns. This is moving faster than it’s ever moved, certainly since I’ve been alive, and I’ve been through a bunch of these technology shifts and changes over the years. This one, this is faster than anything I’ve ever seen. I think with change comes opportunity, and I’m just really excited, quite frankly, for what I don’t yet know.

John Stackhouse 00:23:40

A great answer. It makes me, Sid, think of what you and many others have done in quantum.

Sid Paquette 00:23:45

Right.

John Stackhouse 00:23:45

We don’t know what quantum is going to lead to-

Sid Paquette 00:23:46

No.

John Stackhouse 00:23:46

… but it’s leading to some pretty cool things.

Sid Paquette 00:23:48

It is.

John Stackhouse 00:23:48

And it’s getting better and better, and we, as you said earlier, have incredible strengths in Canada. So we need to continue to invest in those strengths, not really knowing where it’s going to take us. So I love that idea of being willing to bet on what you don’t know, because it excites you. Boris.

Boris Wertz 00:24:07

I’m really excited about what’s happening at the intersection of biology and AI. Everybody is obviously worried about, “Is AI replacing my job?” Let’s look at the upside, and the upside is that lots of the stuff that takes loved ones away way too early has a good chance of getting eradicated within the next decade, thanks to AI. So that’s where I’m personally super excited about, and hopefully, we’ll see some progress in the next little while there.

John Stackhouse 00:24:32

What a great note to end on. This is not the end of the world. It’s the beginning of some incredible things. We just don’t know it yet, and it’s all about discovery and investing in the people who can scale that discovery. Thank you both for doing so much of that over the years, doing that here in Canada, and thank you for being on Disruptors.

Sid Paquette 00:24:50

Yeah. Thanks for having us.

Boris Wertz 00:24:51

Thank you.

John Stackhouse 00:24:54

That was Boris Wertz of Version One Ventures and Sid Paquette of RBCx.

The takeaway is clear. Canada and our greatest companies need global investors, global customers, and global ambition. That doesn’t mean handing everything over to global players. What it does mean is that we need a stronger, globally minded scale-up system right here at home, more domestic growth capital, more sophisticated venture investors, more corporate customers willing to buy Canadian technology, and more conviction around the areas where we can truly lead.

For a broader look at the challenges and pathways forward, check out our show notes for a link to RBC’s Growth Project.

There, you’ll find a host of new ideas for the future of Canada’s economy. And if you want to hear more conversations like this, subscribe to Disruptors wherever you get your podcasts. And while you’re at it, please rate, review, and follow us on Apple or Spotify. That helps more people find conversations like the one you’ve heard today.

This is Disruptors, an RBC podcast. I’m John Stackhouse. Thanks for listening.

The Canadian Unicorn Who Stayed

SPEAKERS

Frederic Lalonde, John Stackhouse

John Stackhouse 00:00:10

Hi, it’s John here. If you’ve been listening to Disruptors over the years, you know that Canada has a problem. We are not the land of unicorns. Sure, we create a lot of companies, but as we’ve heard over and over and over again, many of our entrepreneurs, far too many, feel they have to leave Canada to create and scale a world-class business. There are, of course, exceptions and we’ve profiled a lot of them on Disruptors and one of the most impressive is our guest today, Fred Lalonde. Fred is the epitome of a Canadian unicorn. He has built a billion-dollar company here in Canada and chosen to stay in Canada, not just to continue to grow that company, but to launch more companies with even more ambition. It’s the sort of spirit many Canadians feel and we’ve got to do a lot more to help that spirit flourish right here in Canada.

If you don’t know Fred Lalonde’s story, it’s a pretty good one. He started in the digital economy as a hacker, selling pirated software on the school yard, then dropped out of school and created a solution allowing third-party hotel booking sites to integrate with hotels. He sold it to a young company called Expedia. Next, he built Hopper, another travel site that became that unicorn, and now Fred’s taking the same ambition to the fight against climate change in building a carbon removal company called Deep Sky. So when it comes to building world-class companies and scaling them here in Canada, Fred Lalonde is definitely worth listening to and that’s the conversation we want to bring to you today.

This episode was recorded in front of a live audience and it has the energy of one. Fred is funny, blunt, and occasionally dark, but underneath that is the clarity you so often find in builders who know how to create and also know how to live with failure. As Fred explains, he doesn’t manage disruption, he assumes it. We cover a lot of ground, AI, energy, manufacturing, and Canada’s stubborn reluctance to scale. That’s the challenge that we all have to take on.

Here’s my conversation with Fred Lalonde.

Fred was one of the original Disruptors. I think we’ve had you on the stage a couple of times talking over the years. It’s always great to be with you. We’re going to talk about a whole range of stuff, but Fred, let’s start with you. Amazing life history, lifelong hacker. Grew up in a household with more computers than I think you could count. I’m not going to talk about how you learned your way to hack into Bell phone systems, but that’s a whole different story. I think you once called yourself to the Global Mail no less as unemployable. So that’s a great thing to have in your Google search. Fred Lalonde, unemployable. And you’ve had a couple of near death experiences with companies and yet here you are thriving more than ever. Tell us a bit about you. What is it about you that just keeps you coming back in the face of all that has put you down, pushed you back, tried to keep you down over the years?

Fred Lalonde 00:03:22

Yeah. I mean, I ask myself that same question every day. The term is serial entrepreneur and not for nothing, it’s like you just can’t help yourself. You just keep going and going. So everything that you said is true. I dropped out of school when I was 19. I was a hacker. I’m a child of the ’80s. So I learned when I was 14 that I could copy video games. Some people are old enough to remember floppy disks. And so in high school, I made $16,000 selling these in the schoolyard. I don’t know why parents never wondered where the money came from. And of course, the next step from a hacker is being an entrepreneur. It’s the legal version of what hackers do. It is true. I’ve never had a paycheck, never had a mortgage. I’m functionally ineligible for credit cards. I learned this because you’re now my wealth manager, and they’re like, “Oh, you don’t have a credit card.”

John Stackhouse 00:04:16

Did they turn you down for a credit card?

Fred Lalonde 00:04:18

No, they just said I had no credit history, which is technically true. But the point is I like building things and it’s like a compulsion. I spend a lot of time and as I’m getting older, every year I try to do one board where I find some smart kid in Canada and I kind of help him navigate through all the crap that I wish I knew when I was 28 trying to do this. And functionally people come to me, “I want to start my company.” It’s always the same question, which is like, do you really need to do this? Is this some visceral thing that drives you? And I don’t mean making money because somebody comes to me and says, “Hey, I want to do this.” And you can kind of tell they’re motivated by money.

I’m like, “Dude, there’s a lot of ways to make money. I can give you 10 things because this is really, really hard. And actually you’re going to build for seven, eight, 10, 15 years now and you have a nine out of 10 chance of getting nothing at the end.” And people don’t understand how hard it is, how often you have to fail. So it takes a special disposition and I think good entrepreneurs are motivated by building. You don’t really care about the money or anything else. It’s just about making something, putting it into the world and ideally changing it. People don’t realize the failure ratio, like how often you’re going to be in trouble.

John Stackhouse 00:05:32

Who did you learn the most from in the early goings?

Fred Lalonde 00:05:42

So I was super lucky. When we sold to Expedia, I had no idea. The CEO of Expedia was Eric Blatchford. He grew up in Montreal and he was at some McGill football thing and he walked in, like in the movies, and then a month later he’d bought my company. I was 28. And then they brought me over to Seattle because they had integrated my company and everything. And there’s a book called Barbarians Led by Bill Gates. If you’ve ever read, it’s not very good, but it talks about the ’90s where Bill Gates had these guys that worked for him, and what they would do is pretend to go acquire a company and then they would basically steal the IP and Microsoft would replicate it. And it’d gotten so bad that venture capitalists would not back anything… They would check with Microsoft first before they invested in your company. It was crazy.

Then at some point the government talked about breaking Microsoft and they stopped. So there was 13 people that were in charge of this and the guy that was renowned for being the killer was called Lloyd Frink. He’s in the book. That was my boss at Expedia. Let’s say you were having a conversation with him and you bored him, he would leave mid-sentence. It was fascinating. And the other guy that started Expedia is Rich Barton. He’s built Zillow since. So I completely lucked out. I ended up working for those guys for four years. That’s actually the only time I didn’t sign my own paycheck. And today, if I had to give back that early money I made or the knowledge, I would give the money back tomorrow morning. That actually helped me understand what it was to build a really great company. So I would have to say it’s those guys.

John Stackhouse 00:07:17

What was the best lesson from those guys that helped you with future companies?

Fred Lalonde 00:07:21

It’s this thing that’s been misused. It’s attributed to Steve Jobs, but it’s actually not him. Then it gets attributed to Wayne Gretzky, but it’s actually not Wayne Gretzky. It’s Wayne Gretzky’s dad. Skate where the puck is going, not where it is. It’s actually really hard to do because you actually have to have a credible understanding of what the future is going to be like… And there’s this crazy thing and there’s no… Startup environments are the place where this is the most problematic, but it applies to a multi-hundred year old bank at the end of the day, especially in the era that we’re in now, which is the era of AI. But it’s like if you’re actually building something new, whether it’s small, big, something you run, something you’re a product and it makes sense in current day context, it’s probably not going to work. And so I’ll give you a few examples.

You will be standing in the rain in front of a completely licensed taxi that has been audited by the city and has paid a medallion and you’ll be waiting for a stranger to pick you up in a Toyota Corolla. Instead of checking into a hotel, you will prefer to stay in somebody’s spare bedroom. If I told you these things in 2010, you would’ve called me crazy. I just described Uber and Airbnb. The point is if your idea makes sense in present day context, it’s not going to work in the future, and that’s true in a normal 50-year span, like the one I’ve lived through now. But if you’re looking at what’s about to happen in AI, it’s an exponential problem at the end of the day that’s going to change completely. So that’s the main thing I picked up from those guys.

John Stackhouse 00:09:01

One of the great challenges in building a company of the visionary entrepreneur, usually the founder, and then especially as you scale, you need an operator. How have you found that balance because it’s not often the same person, one individual?

Fred Lalonde 00:09:15

Honestly, and I’ve thought about this a lot, I don’t actually believe in the founder/operator thing. It may have worked a few times, but even the ones that are known for being the highest visionary… So one of my good friends is Laurence Tosi, he was the CFO of Blackstone. He famously turned down Steve Jobs for CFO. So he knows Steve very well. Steve would know the operational details, the cost of the microchips. I have never seen a good CEO operator in a startup. I don’t know what it is to run a bank, and God help us, nobody will ever give me the opportunity to try that, but fundamentally, if you’re building something that has high velocity, high growth, lots of unknowns, you have to be able to get the big vision and the execution. And I’ve seen a few teams, but the really, really good ones are able to go all the way down, and I would argue your current CEO is one of the few that I’ve met that really, really qualifies and I think it shows in the culture of the bank.

So I actually think sometimes a team, but you kind of have to have that willingness to go all the way down to the nuts and bolts because when things are stable, it’s okay. I’ll give you my favorite example. If you work at a large organization like this one or Mitsubishi, what, maybe 5% of your company is new, like hiring spree, something like that. At Hopper for the first 15 years, 50% of the company was new. Think of that, right? It’s like your company’s constantly made of spare parts.

John Stackhouse 00:10:47

How do you manage that as a founder, you were there, you were the origin story and then you’ve got all these newcomers coming in and regenerating it. How do you kind of roll with that and let other people also take it in directions that you may not-

Fred Lalonde 00:10:59

The culture question. I’ve become convinced that culture is the only way to go. So for example, at Hopper and in our other companies, Deep Sky, the carbon removal company that you guys know well, we don’t have a traditional C-suite, we don’t have a CTO, we don’t have a CIO. We’ve gone to something called single-threaded ownership, which is an Amazon model. And so when we reached about a hundred people at Hopper, I started losing velocity. It gets harder to do stuff. Again, if you work in big companies, you know how hard it is to do stuff. And my problem at Hopper is I made no money doing the thing we did. We were selling flights, which is a really bad idea. And so I had to do a second thing and most companies don’t have that. They either do one thing, run out of money and die because it didn’t work, or they do a thing that works.

We had to find other things. And so what made us profitable is our financial products or fintech, blah, blah, blah. But before I could get the company to do more than one thing, it was attacking itself. So I had to design the culture. So I started reading everything I could. So Eric Schmidt wrote a book called “How Google Works.” There’s a boring long book, but there’s a children’s book. This is crazy. It’s illustrated. It’s like for five years old. I really recommend this to everybody and he explained how Google worked when he took it over from Larry and Sergey. Reed Hastings wrote a lot about this. Then I found Jeff Bezos’ shareholder letters. And if you have not done this, every year since starting Amazon, he writes. You should read this. It’s a whole insight into his mind. And I realized something fundamental.

The first thing is culture is not what you say. It’s not the poster on the wall. It’s not what your HR department does. We don’t actually have those, but if I had an HR department. It’s actually how you act and what you reward and what you punish. People will act according to what you do and what you say good or bad to somebody. And most people don’t realize how important that is. Everything’s being observed when you’re in a position of leadership. And so then I realized something really fundamental and this is actually why we’re successful. We’d be out of business if I hadn’t figured this out, I’m 100% convinced of it. Most companies get together at some point. Somebody tells them, “You need to define your culture.” Get in a room and you say, “Here are our values,” and that’s it. The really good companies, the amazing ones, they did something different. The founder at some point said, “What kind of company do we need to be for our customers?”

And so Google that was making all of its money on one algorithm, put the engineers in charge, right? Netflix, because streaming kind of didn’t work, it just wouldn’t start. If you guys are, again, old enough to remember this. So they put the product people in charge and Amazon super interestingly realized that they had no network effect where Google had the search, Facebook is a network, blah, blah, blah, all this kind of stuff. They put the category managers in charge and everything… I could go on for hours on this. So what I realized is companies have two types of cultures. The ones that kind of emerged because they got in a room and put a bunch of stuff on a sticker board and voted for it, and the cultures that are designed, that were built for a purpose and that purpose should be the business you’re in and where your customers need you to be. So we got to very, very simple things: move quickly, obsess on the customer and we put revenue as our core value, and people quit.

John Stackhouse 00:14:38

Revenue is your core value?

Fred Lalonde 00:14:39

Yeah. We have three core values, obsess on the customer, move quickly, make money. And you know what happened once we put revenue? We went from 10 million to three quarters of a billion where we are now. It’s declarative. It’s like a marriage. I pronounce revenue, and it happens. And that’s what a founder has to do. You have to manifest 90%.

John Stackhouse 00:15:00

And people not interested in revenue left.

Fred Lalonde 00:15:02

Yeah, exactly. And then it becomes a self-fulfilling prophecy. You attract people that want the thing that you’ve declared. Now, whether I believe revenue is the core thing that should drive society is irrelevant because I’m here for my customers, I’m here for my investor.

John Stackhouse 00:15:16

So we’ll switch to AI, but you mentioned in passing there, you don’t have an HR department.

Fred Lalonde 00:15:21

No.

John Stackhouse 00:15:22

How does that work?

Fred Lalonde 00:15:23

You don’t need it. Sorry. Is there anybody in HR? We realize you don’t need it. Yeah, and that’s a very long-

John Stackhouse 00:15:30

But there’s lots of HR functions that you do need.

Fred Lalonde 00:15:33

No, no.

John Stackhouse 00:15:33

How do you manage it-

Fred Lalonde 00:15:34

No, actually you don’t. Have you ever read Dilbert?

John Stackhouse 00:15:38

This could be my last conversation for RBC, but I’m genuinely curious. How does that work?

Fred Lalonde 00:15:47

We don’t have functions. So what we do is my companies all work like federations of startups. So one person’s in charge of financial products, another one’s commerce. We have somebody running banking and they have full hire and fire over their entire team. The only function that’s horizontal is finance. And so at the end of the day, the short answer is if you have a problem with your paycheck, you go to finance, but we don’t have any HR. We also don’t have offices and we never meet, which is probably another whole thing that we should talk about.

John Stackhouse 00:16:14

No HR, no offices, no meetings.

Fred Lalonde 00:16:15

It’s awesome.

John Stackhouse 00:16:16

How do you exchange ideas?

Fred Lalonde 00:16:18

You actually write them down. So we’ve actually found that… And there’s actually the founder of WordPress-

John Stackhouse 00:16:25

Bezos does this too, right?

Fred Lalonde 00:16:25

Yes. It’s a Bezosian thing. He’s not the only one. Schmidt does it a lot. So the founder of WordPress… This is a big company back in the day, still pretty meaningful. They never met anybody they hired and it was by design. And the reason is he believes to this day that if I meet you, all my cognitive bias, you’re white, we’re about the same age, I’m likely to like you, all that kind of stuff. And so they did their entire interview process in writing and they actually realized they had a very low close rate. So at the end they added one step that took up a few years. They would call you and say, “Actually, it’s a real job in case you’re wondering,” because people wouldn’t think that it was a real job. And so his point is it’s very easy for somebody to trick you verbally, especially if the person has high EQ. If you really want to know how my brain works, read me, and vice versa, I should read you. So a lot of it’s writing.

And we’re global. So we have people in every country. We serve Japanese banks and all this kind of stuff. And one of the things that it let us do because we’re a written asynchronous culture, it lets us hire the best people in the world anywhere where they are. And so when the return to office happened after the pandemic, we picked up people that were leaving Google and it’s continuing to happen now that we never would have gotten. So we’ve been punching ahead of our weight class because of talent density and that is the only metric that we have, talent density, like you would if you were building a professional football team.

John Stackhouse 00:17:55

Perfect segue into the AI part of the conversation. Is AI going to get rid of all this, this human aspect?

Fred Lalonde 00:18:03

And a lot more. Yeah. So I’m going to preface this. I have a really dark view on a lot of things. In these periods where there’s extreme disruption, there’s also extreme opportunities. So I’m going to do my best to scare the crap out of you, but for as troubling as these things are, there’s actually a lot of upside. And the reason I speak this way about climate and about AI is because I fundamentally believe in first principle thinking. You have to ask why and the why of the why. That’s how you make good decisions. If you go back to the 1900s, 1905, there were about 27 million draft animals in the United States. And so there were about 95 million people. So every three humans there was a draft animal. How do we know this so specifically? It’s because this was so important that it was part of the census.

They would count the number of horses when they did the census for the people. Why? Because all transportation but also all food was produced by draft animals. And so there were horses everywhere. The first commercial vehicle, internal combustion vehicle, was sold in the US in 1886. And so if you think of it, there’s this really bizarre period between 1890 and call it 1910, 20 years, give or take, where you had a small number of internal combustion engines and you had horses everywhere. The peak horseness was around 1915. So for 25 years we kept adding horses as part of the base of the economy, even though the internal combustion engine was there. This is Vaclav Smil, by the way, How the World Really Works. I’ve stolen all this. So the role of the internal combustion engine was to completely change transportation and food production. It replaced the horse. AI replaces thinking. So what do you think is going to happen?

Make no mistake about it. If you talk to anybody who works at an AI lab that builds AI, they are not building it to make your life easier or your people’s… They’re not building it to enable you. Every time you load Claude to make a cash flow statement for one of your customers or to goof around on something, they are training the model to do it without you. This is 100% understood. Every AI engineer understands this.

John Stackhouse 00:20:41

What would you recommend/advise people in this room to talk with their teams, with their clients, and to think about themselves, about those challenges coming at us?

Fred Lalonde 00:20:50

So I think what you have to do is break apart what your team does, what your group does, what your company does into its core components, and you need to basically do what Steve Jobs did when he did the Mac. You need to start a completely shadow organization over here and only bring… Obviously this runs entirely on AI and only bring in the parts that you need assuming that AI will do everything else. And then figure out if you can… Just remove every constraint you think you have and some like the security of the bank, you don’t have a choice, try to move it to an AI-first world. And if you get something that works, raise your hand and go, “Hey guys, look at this,” and hopefully the person next to you and the one will pick up on it and improve on it.

And the people that can do that are probably the ones that are still going to have a high-paying job because it’s that creative judgment-based act that even though the AI could probably learn, it’s probably where you want to keep the human in the loop.

John Stackhouse 00:21:53

I know we’re over time, but I want to steal another minute to just get your thoughts on this growth challenge, which we’re leaning into, we’re investing in. What do you think Canada needs to come to grips with most critically to ensure we get a better trajectory of economic growth and that we help companies and entrepreneurs like you take on the world but scale a lot faster here at home than we’ve seen?

Fred Lalonde 00:22:16

You kind of have to hunker down. So if you take Canada, we’re probably the richest country in the world, just by natural resources. We’ve talked about this actually. But we’re so comfortable we don’t realize it, right? But if I was asked to figure out what to do with the bank’s fund, which again, hopefully never happens, I think it’s very, very simple. AI for sure, climate and energy, which are the same thing, and fully automated manufacturing resilience. We need to be building our own sovereign energy. We need to be dealing with our emissions. We’re not good at wind farms. We have no tech. We’re dependent on the Chinese, the Europeans. We have nothing on solar, the Chinese… Not ideal. Our nuclear program, like every program in the world is in shambles because we gave up on it. You know what we’re really good at? Really, really good at? Drilling.

And you can either drill for dead dinosaurs at about two kilometers, but you know what happens if you keep going to five, six, seven, eight kilometers, you hit heat energy, geothermal. There’s enough energy on the ball of rock that we’re living on right now that 0. 1% of it will power our civilization for two million years. And there’s actually a company in the US that figured out how to do it cheaply two months ago. So I can tell you it’d be those themes, AI, climate, energy, and manufacturing resilience.

John Stackhouse 00:23:40

And with Canadian engineers in that US company, I mean, everything you talk about is really connected to scarcity and scarcity leads to more innovation. You’re the embodiment of that and we facilitate that. So scarcity can squeeze, it can hurt, but it leads always to some kind of innovation, usually great innovations. The other thing I love that you said, Fred, is you’ll be back next year, which tells me you have hope that we’ll all be here next year. So just in the darkness, he thinks he’ll be here next year, he thinks we’ll be here next year. I’m not that smart, but I’m connecting dots to say that we got hope here. What you’re saying, Fred, is we stand a chance to be here a year from now and doing even better things.

Fred Lalonde 00:24:32

I’m actually an optimist.

John Stackhouse 00:24:33

Okay. Fred, we’re going to close there.

Fred Lalonde 00:24:37

We’ll close on this: It’s not because something is hard and the odds are not super in our favour that we shouldn’t do it, right? That’s the whole point of everything I’ve been saying.

John Stackhouse 00:24:48

Yeah. It’s like that great line in Dumb and Dumber, “What you’re telling me is we got a chance.” Fred, thank you. Thank you. Thank you.

That was Fred Lalonde, founder and CEO of Hopper, recorded in front of a live audience. I hope you’ll agree that Fred has a way of making the future seem both more alarming and more navigable than it did before you started listening. His clarion call about scaling more here in Canada also should be a message that every Canadian can take on. At RBC, we’re trying to do more with the launch of a new billion dollar platform to invest growth capital in the companies that will help Canada grow in the years and decades ahead. And right across the country, we’re seeing big investors, private companies, and ordinary Canadians all wanting to put more capital behind this country’s amazing potential. It’s not just those big projects that we hear a lot about in the news. It’s about the big ambitions of entrepreneurs who are creating companies, whether it’s in the resource sector or the digital economy that can help Canada and Canadians sell more to the world.

For more on all this, visit rbc.com/thoughtleadership. You’ll find research, perspectives, and ideas to help you clarify what’s next.

And if you like this podcast, follow, like, and review us wherever you listen. This will help others find these conversations on the ideas, technologies, and entrepreneurs reshaping Canada’s economy.

I’m John Stackhouse and this is Disruptors, an RBC podcast. Thanks for listening.

From MLB to Metallica: The Canadian company redefining live events

SPEAKERS

David Ross, John Stackhouse

John Stackhouse 00:00:10

Hi, it’s John here. I want you to close your eyes for a moment and picture a few things.

First, let’s start with a pro football game and those seemingly magical first down lines that stretch across your screen. Or, what about those golf games where you can now hover over the green and feel a bit like a bird? And who can forget those incredible moments at the Milano Cortina games where, thanks to new camera technology, it felt like we were all part of the ski cross race. Okay, keep your eyes closed and imagine the last concert you were at. It probably didn’t feel like a concert that you might’ve gone to years or decades ago. Concerts today, especially in big stadiums, are explosive in sound, but you have 360-degree imagery all around you. The performers on stage are now, well, just part of the concert. Behind all of this is a remarkable Canadian company, and odds are you’ve never heard of it until now.

Ross Video sits on the outskirts of Ottawa in a really unassuming brown brick campus that could pass, well, for a community college. Then you walk inside and start to see some of the tells. The first is an Emmy Award on the reception desk, and then there’s a wall covered in the caps of almost every major league sports team you can name because this company has worked with them all. Open some more doors, and you come across green screen studios, robotic labs, and control systems being built for some of the biggest live productions on Earth. Ask Taylor Swift who created some of the magic of the Eras Tour, and she might say Ross Video. You’ll get the same answer from Metallica, Coldplay, and every team in Major League Baseball.

This is one of the most innovative companies I think I’ve come across anywhere. It’s also part of a much bigger economic story, one worth roughly $ 500 billion globally. That’s the live entertainment ecosystem that is reshaping how audiences and businesses experience everything from sport to politics to music. Ross Video was started by a great Canadian, John Ross, an engineer whose analog video switcher brought the 1976 Montreal Olympics to the world through the CBC. His son, David, another engineer, took that foundation and built it into a live production powerhouse that’s now operating in more than 100 countries all from this corner of Ottawa. Ross Video strikes me as the kindest story Canadians really need to hear more of these days. It’s about innovation, it’s about global ambition, and it’s about doing a lot of incredible things, including building robotic cameras right here in Canada. That’s the vision and the passion of pretty much everyone in the country, but especially of its CEO, David Ross.

David, welcome to Disruptors.

David Ross 00:03:14

Thank you.

John Stackhouse 00:03:15

I find this, as I said in the introduction, the most interesting company so many people have not heard from. I want to kick off just asking, how do you describe Ross Video to people who are not familiar with it?

David Ross 00:03:29

I thought of a billion different sort of elevator pitches, and I think one of the ones that I like is, “We’re in the business of keeping our famous customers famous through the use of high-end video.” Because if you’re using video at the level that Ross Video provides, you want to reach a lot of people. If you want to reach a lot of people, you’re either famous or you want to be famous.

John Stackhouse 00:03:49

You joined the company 30 years ago, 35 years ago?

David Ross 00:03:51

1991.

John Stackhouse 00:03:52

35 years ago.

David Ross 00:03:54

Right.

John Stackhouse 00:03:55

What did you see or feel as you were starting to take over the company that allowed you to grow it to what it is today?

David Ross 00:04:01

Fear. I came home from university, and my mom said, “You need to go upstairs and talk to your father. He’s one signature away from selling the company.” I wasn’t sure if I was going to want to start work at Ross Video. I was interested in working for maybe NASA or… I heard that Bill Gates came by the University of Waterloo, I’m an engineering student at the time, and I talked a good game about joining Microsoft. I thought I had a big career in joining Ross Video, town of 1, 200 people. Dad just laid off two thirds of the company in the recession from ’89 to ’91. Oh, boy, that’s not what I envision for the grand future of my life, I guess. I talked to dad and I said, “So what’s going on?” He says, “Well, having a challenge seeing a future with the company. I’ve got an offer,” and I said, “Well, maybe we can turn it around together.” He actually looked at me and he said, “Well, there’s a lot of satisfaction you can get from building something out of nothing.”

John Stackhouse 00:04:57

Take us back to the origin story and what your dad, John Ross, still with us, developed in the early 1970s and how that started to transform how we view and experience sport in particular.

David Ross 00:05:11

Well, back in the early 1970s, it was all about the technology. Was your product more functional, cheaper, using the latest tech? But I don’t think anybody who was really focusing on transforming the world is… You have a product, the other guy has a product, you try to make a better product.

John Stackhouse 00:05:27

Right. He developed the 16-4-

David Ross 00:05:30

Yes.

John Stackhouse 00:05:30

… switcher that, for those of us a certain age, actually made the Montreal Olympics as memorable as they are in a good way. What was it about that device that laid the foundation for what Ross is today?

David Ross 00:05:44

I think it was kind of the right product at the right time. It was exactly the right size. It was a really good price point. It was very powerful for the amount of electronics. My dad was an analog design genius, you could sort of say, where he would be able to see the circuitry in a way that was more reliable, higher quality for less parts than anybody else seemed to be able to do anywhere in the world, and so you can say that the company was founded on innovation.

John Stackhouse 00:06:14

It’s fascinating what has happened to the live event business, sport, and entertainment. They’ve become multimedia platforms, not just experiences. So much of what we all enjoy and maybe take for granted is thanks to Ross Technologies. How has the live event market evolved, and what have been those kind of signature changes over the last decade even that have allowed you to be where you are?

David Ross 00:06:40

There’s a couple of things that drove change. I think the biggest one was the fact that the screens got cheaper. It used to be LEDs or the jumbotrons. Basically, it was a television monitor for every pixel, and they took enormous amounts of power, very expensive, very low resolution. As the LED walls started to become more and more dense, cheaper, less power, then people said, “How do we drive all those pixels?” It’s not just one screen. It’s many screens of all different sizes of all different shapes throughout the venue, inside the venue, and outside the venue. And then you think about the canvas of the field as being another set of pixels that you’re drawing on in a virtual world. So it’s just this explosion of what you can see.

John Stackhouse 00:07:30

So there’s been a kind of a tech enablement. That’s also changed expectations in all of us as fans. I can’t even imagine a concert without a screen. If it was just a screen allowing me to see a closeup of the stage, I’d probably be disappointed. Same at the sporting event, hard to imagine a game, rightly or wrongly, without a screen. How have we changed as the end user in your view over the last decade or two?

David Ross 00:07:54

We’re getting much more used to a lot of data coming at us. It used to be that your high school gym that would just show the score and almost nothing else than score and the time left, and now you see what the scores are, you see the statistics, the strike zone, you may see the golf ball curve, the heat map on the floor of all the different places where they took their shots from basketball. You see all the data about all the players of everything that they’ve ever done in their lives, and it just keeps going. It’s not just about moving video, it’s about presenting that data in an interesting and consumable way. There’s lots of periods of times where the things aren’t happening, and the goal I think of some of the sports teams and the venues, as well as just broadcasters in general, is how do you keep people’s attention?

In a stadium in particular, the moment that the play stops is the moment where the stadium sort of kicks in and says, “Now, we’re going to have some fun, and we’re going to do it together, and we’re going to enjoy things.” And maybe at the same time, they’ll work in the ads that sort of pay for the whole experience at the same time, but there’s a really interesting weaving of the way that the game moves into the experience, and the advertisers move in and out, and the statistics move in and out. There’s a lot going on.

John Stackhouse 00:09:14

Talk a bit about the businesses that are between the fan and either the performer or the athlete, usually a stadium, of course, the team. I’m curious what they’re looking for, because you talk to them all the time, that’s your business. What are they looking to fulfill in building out, frankly, really expensive operations, billion-dollar stadiums and the whole district around them, as well as the cost of putting a team on the field or an artist on stage?

David Ross 00:09:42

They’ve got a lot of things that they’re juggling at once. You could sort of say at the base of it all is their brand. That sporting team, that venue, that brand has value, and so it’s all about the fact that there’s only one hockey team in Ottawa, there’s only one football team in Los Angeles as a professional level. Because there is that uniqueness and you have this fan following, how do you keep that excitement up, keep the eyeballs on that instead of some other sport, because there’s competition, or some other event, and keep it fun? It all has to hold together.

John Stackhouse 00:10:19

These stadiums have become destinations. They’re tourist destinations. I think of AT& T. There’s only one Dallas Cowboys, but there’s also only one AT& T Stadium. It’s an attraction not because of the Cowboys on their own, but because of the experience, including the screens and what you provide for that.

David Ross 00:10:37

Yeah, and that’s actually a really interesting thing about what’s going on in the business that we’re in. Because you could say a long time ago, we would be in the business of providing the technology for a television broadcaster. If you think about a sports team or a corporation now that’s using our technology, it’s a brand amplification technology. So it’s not about how much money goes into the equipment that you buy and then how much advertising do you get on the output, it’s how does that change the perception of AT& T.

John Stackhouse 00:11:08

That’s a really interesting view of the business strategy, but the brands are not just companies now. What do you figure is still growing? Because 10, 15 years ago, there were probably a lot of media analysts who said that all of this is going to be disrupted and the individual will take it over.

David Ross 00:11:25

They were wrong.

John Stackhouse 00:11:27

Why were they wrong? I was probably among those who were wrong, so tell me why I was wrong.

David Ross 00:11:32

Well, it’s both. It doesn’t have to be an either/ or. More people certainly watch YouTube than anything else in the world. Feeding into YouTube, you have everything from… I just uploaded a picture of my dog that I did myself to some very professional productions and even movies. It’s a continuum, and there’s just a certain place where Ross plays, which is in that higher-end tier.

John Stackhouse 00:11:59

Let’s talk a bit about the amazing technologies that you both built and literally acquired and then developed. I want to start with Artimo, because we just walked through your lab across the street, saw these robotic cameras zipping around. Those are developed here in an Ottawa suburb, they’re built not far away in Iroquois, Ontario, and they’re transforming so much of what we all kind of take for granted seeing on a screen. We’ll talk about some of the other innovations, but tell us why Artimo is so important in your mind.

David Ross 00:12:31

One of the things that’s interesting about Artimo, you could start from a customer point of view, it’s always good to start from customer point of view, is Artimo replaces different types of manual moves. Instead of it cruising behind a camera, there’s a limit to how much they can do with teleprompters on it and so on. Being able to have a motorized system doing repeatable moves, particularly in a newsroom or at a corporate studio, you need technology to do camera motion properly. It used to be when you’re watching television news and you even still see it in the movies, you imagine rows and rows of people yelling back and forth, “Do you have that shot? Do that shot,” and everything else. Now, at least in 700 newsrooms around the world, even at the highest level, there’s basically one guy with a mouse clicking and mumbling to himself or herself. The computer system is controlling Artimo to make sure that it’s positioned with exactly the right shot, with the right depth of field, and everything else for what is coming up next in the playlist.

John Stackhouse 00:13:34

You also have a whole range of fascinating technologies that have transformed not just what’s behind the camera but what’s on the screen, and I’m thinking of some of the layering technologies. We all kind of take for granted now those red zone markers on an NFL or CFL field, lots of other layering that has made the game experience much more dynamic and interesting. Walk us through a bit of your thinking on how that’s evolved and how that has transformed the viewing experience.

David Ross 00:14:05

Oh, wow. In football, for example, you do have the 1st and 10, the yellow lines and the blue lines and things like that. We didn’t invent that. I will say we didn’t invent it, but we certainly got into the business. One of the places that we did very well is with American college sports, American college football, because they weren’t able to afford whatever was out there at the time at the professional level, and they want to be able to get that on our in-venue as well. Because people are used to watching it on TV, “I want to see it on the big screen in the stadium as well.” We don’t want anybody to come into the stadium and feel like they’re getting a lesser experience than if they stayed at home and watched it on TV. So how do I get the same stats? How do I get the same experience and then have the in-person side of things? It’s the same thing that same technology is used for infield advertising as well, and that gives them ability to charge more for advertisements that way.

John Stackhouse 00:15:02

We’ve also seen incredible changes to the functioning of camera, and I’m thinking of the spidercam, which is another of… It was your acquisition. But wow, what you’ve done with it… Even the Milano Cortina experience, I still can visualize feeling like I was on the speed skating track. The golf experience now, I think you took it to the British Open-

David Ross 00:15:26

We did.

John Stackhouse 00:15:26

… where it now kind of goes over the green, which has just made golf so much more interesting, seeing it from the bird’s-eye view quite literally. Walk us through what you saw in spidercam when you bought the company, and what you are trying to do with it, where you see it going from here.

David Ross 00:15:45

Interesting. We started with the studio robotics, like Artimo, and things that we did before, and that was part of acquisitions. We realized that there’s a lot of value in being able to capture video with camera motion and doing a volume of space. We realized that we were doing really well with studios inside, and then we inverted them, and we could look down on the studio, and so we got that volume thing happening. What can we do outside? Of course, the natural thing is cable cameras. We had been working with spidercam in the past because they would give us telemetry information, and we’d do augmented reality with our graphics technology, and so you could sort of see stats floating in the air or something like that as they’re capturing some event. We already had experience with what we could do and saw synergy with one part of our business moving with another part of the business, just camera motion.

I did actually nudge them a few times saying, “If this is ever for sale, give me a call.” And then one day, the call came, and so we made it happen. What’s beautiful of it as well is spidercam is tier one. It’s the leader in the world. It’s the biggest brand and the biggest part of that business. So for Ross, it’s actually a brand amplification as well, because we are there at the Olympics, we are there at away games for the NFL when it’s in Europe. We’re there now for Premier League, we’re there for cricket all over the world, and we are there for the playoffs right now at the Montreal Canadiens where we put a spidercam into the arena for the first time.

John Stackhouse 00:17:23

Where do you see cameras going from here? We’re all now familiar with drone cameras, which are transforming the event experience, sport, as well as a concert. We’re getting familiar with on-body cameras, whether it’s the ref cam or the player cam. Where do you see it going over the next few years?

David Ross 00:17:41

I think it’s going to become more and more accessible. You’re going to see them more often in more fixed installations. Spidercams, not too long ago, if you wanted to buy one, if you had a million dollars, then that’s a good start. Maybe you could get something for a quarter million dollars, if you’re lucky. Basically, they were rental units, and we would fly them halfway around the world, and these things have winches the size of refrigerators and heavier than a refrigerator, and there’s four of them, and then there’s a big centerpiece in the cameras. It’s an ordeal, and you’re going up into the rafters of the stadium, and you’re putting up pulleys and worrying about safety. Every single game, you then pull it down, and you put it someplace else. We’ve just launched what we call the i-Series for the spidercam, and that means that more venues can own them and get their costs down, which means that you’ll see them in more places.

John Stackhouse 00:18:36

You do much more than just make this stuff and sell it or rent it into the market. You help build literally the infrastructure, help, whether it’s teams or concert tours, create the experience. That’s a very different business than making a robotic camera in Iroquois, Ontario and putting it on a plane somewhere. How are you thinking about the soup to nuts, if I can put it that way, aspect of this business?

David Ross 00:19:01

It’s all about adjacencies and understanding how to move into an adjacent business. When I started at Ross, all we had were analog production switchers. We had about four or five products. They’re about 10 years out of date, to be quite honest. How do you go from that to where we are today? So we started designing new products that would be sold at the same time to the same customer, made in the same factory, into the same market, with the same sales channel, and then you start moving into adjacencies. The challenge was when we started moving from traditional products to new ones. You can waste a whole lot of time and money by saying, “Let’s just invent this thing from scratch,” because you need to have the knowledge and the trust and so on. So the easiest way to do that is to acquire companies and acquire them hopefully with the founders or the genius that’s behind those companies and then don’t piss them off and keep them around.

What a lot of companies don’t do is the founders like to stay with what they know, what they know, what they can control, and so there’s a leap of faith of management where you say, “No, no, I’m going to start doing things that I’m not an expert in.” I’m a computer engineer, “Robotics? That’s madness,” or you say, “We’re a manufacturer, and we’re a supplier. We don’t get involved in our customer’s affairs.” And then we have Rocket Surgery. We buy that company, and we have great people in that company, and you build that up, and all of a sudden they’re talking about the fan experience.

John Stackhouse 00:20:31

Rocket Surgery is kind of like an agency, right?

David Ross 00:20:33

Kind of like, inside of Ross. They’re people that combine the skills of graphics and programming and organization and understanding the sport, the venue, the market, the nationality, and they come in, and they will make the stadium experience real. This vertical integration of having the design, the manufacturing, and then the creative services that are on top of that, you have to, as an owner of a company, like a tech company, be able to say, “We can get into services. We can get into art,” which is a long way from analog design or software. But when you put all these things together, it’s magic.

John Stackhouse 00:21:12

Is the business model and the approach, the knack to this, very different for live music, for concerts, than for professional sports versus outdoor events, corporate events, or general public events? Do you have to take a different approach to each, or is an event and an experience an event and an experience?

David Ross 00:21:32

There’s a common thread through them, of video and organization and so on. But yes, each one is different, and so you have to be able to know, “How do I get those relationships, and how do I understand that concerts and video for concerts is very different than video for a stadium?” For example, in the stadium, you’re talking about wow moments when the touchdown happens and the data and the advertisements and the stats and things like that. In a concert, you could argue that there’s almost not a wow moment. The whole thing is just this burn that happens the entire duration, and now you’re interested in keeping up with what the performers are doing and getting those shots, whether it’s putting video on the screens that is supposed to be synced to what the performer has rehearsed, and hopefully they’re following in live, versus having a spidercam like at a Coldplay or Metallica concert, which we also do as well, and knowing how to get those beautiful shots up on those screens.

John Stackhouse 00:22:31

And I’m guessing, especially on the creative side, on the concert side, that you have to find the right rhythms and beats quite literally. But Metallica is probably different from Taylor Swift in terms of what they’re looking for on stage, is that true or not?

David Ross 00:22:48

Actually, I have heard, I talked to some of the camera operators in a spidercam, for example, you’ve got the engineer in the background, but then you’ve got a pilot who’s flying the camera rig around, and then you’ve got the camera operator who is taking the shot from that moment and zooming in and panning around, and they work together to get the shot. From what I understand, Taylor Swift is always the same all the time, she is perfect, and Metallica is like, “Follow them,” because it could be different at any given time.

John Stackhouse 00:23:22

That’s rock and roll. Yeah.

David Ross 00:23:24

I can’t believe I’m involved in this stuff. It’s like, “I went to computer engineering in Waterloo. How did this happen?”

John Stackhouse 00:23:32

How will AI and robotics change what you’re doing now?

David Ross 00:23:36

AI is coming for software and software development and things like that.

John Stackhouse 00:23:41

Are you seeing that in your own software development?

David Ross 00:23:43

Starting to. It’s an accelerator, but it’s also an enabler. There’s a whole bunch of dimensions about how AI is going to impact our business and every business, and we’re just learning what that is on a daily basis right now. Because every time you think you know the way it stands, it changes yet again, and it can do something new. We’re just keeping up as best we can. We’re a software company and a services company and a hardware company and a robotics company, and there’s threads that tie all those things together. I like to think that those things build a competitive moat no matter what happens in the world going forward. Having a network of dissimilar things that require a broad range of expertise that can’t possibly be in one person’s head that require the organization of humans to pull it together is I think the sort of thing that makes for a strong company going forward.

John Stackhouse 00:24:34

You’ve built an incredible company here. You’ve got a really strong culture, strong values, and I’m sensing it’s very much about the team, the Ross team. Often when you do an acquisition, you’re not entirely sure of the kind of culture that you’re acquiring. You’re getting the talent and technology, but also the culture. How do you, as the CEO, preserve and grow the Ross culture?

David Ross 00:24:55

One of the things my dad said to me many years ago, he said, “A company is only people. It’s not about the products you have. That’s a moment in time. It’s not about the technology you have. That’s also just a moment in time. It’s not about the customers you have. You can lose them. It’s about the people.” And if you think about the sorts of things I was talking about, I don’t know anything about robotics. I know a bit more now, but I’m not a world expert. I don’t know everything that there is to know about creating a great stadium experience. You know what? I haven’t written code in 35 years. Everything that I have had this company create is through encouraging and enabling great people in the company. So if you take them for granted and you don’t listen to them, then you’re going to be in trouble. It turns out that if you treat people really well and you listen to them and you pay them well and you do all the right things, a culture just emerges out of all that, and it’s a pretty good one.

John Stackhouse 00:25:54

You also have a strong code of ethics, which every visitor can see as they walk through the door, and it is beautifully in plainspeak. One of the points that really jumped out at me was, “We don’t ship crap.” You also have a wonderful line about… You say that, when people aren’t sure what to do and there’s no one around to ask, “Just do what in your heart is right.” And then, in brackets, it says, “You can hire a helicopter,” which is I think a nice kind of cheeky way of saying, “Do what’s right, but don’t box yourself in.”

David Ross 00:26:23

Yeah, that’s an empowerment statement. It’s also a customer statement, and it’s also a company statement. Companies have an inherent drive towards bureaucracy and squeezing out individual actions and things like that. Often, those individual actions are the things that save the company or make the company great. When I added that to the list, I knew that the day would come when we would be a bigger company and we would be vanilla, like everyone else, and people would just punch the time clock, do their thing, say, “It’s not my job,” and go home, and leave the customer stranded or leave the company stranded. How do we put this escape hatch into the company in a way that’s memorable? When I talk about, “You may rent helicopters if necessary,” it’s like, “Well, somebody wrote that. They must mean it.”

John Stackhouse 00:27:15

A human wrote that?

David Ross 00:27:16

Yeah, a human wrote that.

John Stackhouse 00:27:22

Where does Ross go from here?

David Ross 00:27:25

In some ways, you could say it’s completely different. In other ways, it’s more of the same. The industry is going to continue to evolve. Video is going to be changing, AI is going to change things, and the world will just continue to change. As long as I continue to encourage our people to pay attention to the early warning signs, or if we’re late to react and catch up, I think we’ll be okay. What’s the same is the way we manage people. Dad was right, a company’s only people. So when the company moves forward, there’s a lot of me just… Following what other people are telling me is the exact right thing to do, and they’re the experts, and they go, “Yeah, let’s do that. Let’s go ahead.” The secret of success is hire smart people and don’t piss them off.

John Stackhouse 00:28:14

Yeah. If you’ve got a talent challenge, you probably have greater challenges, because good companies just attract good talent. I’ve read Ross has never had a down year. Is that correct?

David Ross 00:28:25

Since the day I joined, yeah, we haven’t had a down year. It’s been close sometimes, but we have not.

John Stackhouse 00:28:30

But that’s phenomenal through a few recessions, lots of disruptions. Is there something that has been consistent through that time beyond what we’ve talked about that has enabled that?

David Ross 00:28:41

I think it’s never stopped pushing. When we’re a very small company, I got a chance to have lunch with somebody who was a billionaire at the time, and I was like, “What question do I ask a billionaire over lunch?” I’m 27 years old, so I asked, I said, “Can you give me some advice?” He said, “Never fall behind in technology. You can have great people, you can have great customers, you can have a great brand, and it all seems great until you fall behind in technology. When you’re a tech company, that’s everything in the end. They’ll just feel really sorry that they can’t buy from you anymore because you don’t have the stuff that they need, but they will go someplace else.” I took that to heart, and so we overinvest, you could say, in research and development and push as hard as we possibly can afford to do every single year into R& D. We got 1, 500 people, and manufacturing is in that 1, 500 people. 500 of them are in research and development.

John Stackhouse 00:29:44

That counters so much of the Canadian narrative, that idea of having a third of your employees in R& D, “Very un-Canadian, sounds more like Germany or Japan or Korea.” What are we missing as a country so that we’re now more like Ross Video leaning into the R& D opportunity?

David Ross 00:30:02

I don’t run the other companies. I guess I don’t know exactly. I think there’s a lot of dimensions to what’s going wrong though. Historically, sometimes Canada was known as a place that had lots of R& D but not enough marketing. I took an idea of saying, “You know what? The Americans are very successful in the way that they create great technology, but then they make a lot of noise about it, and they take it to the world, and they push hard.” I remember talking to… just randomly, it was a British company I was looking to buy. I said, “Why is your product the best? Convince me,” and they went, “Well, it’s not really the best. There’s other good ones out there as well.” It’s like, “Stop being modest. You’re trying to sell me your company. This is not what I want to hear,” and we actually didn’t buy that company in the end.

But you have to be likable, hopefully, around the world, and that might be something that Canadians are good at, but at the same time, be aggressive. You realize you are in a worldwide fight to get your product out, and you’re in a worldwide fight for R& D resources that you need to make the best tech and sell it. The best investment funding that you can possibly get is from your customers. It’s called profits, and you take those profits and you reinvest. There’s so many in business school, I swear, they say, “You have a great idea, so the first thing you need is get an investor.” And then where’s that investor coming from? Probably from the United States or not from Canada. And then you have to do a second round, a third round. You’re going to do all these…

What? At what point are you going to make money? At what point do you own anything of your own company? And now you’re diluted so much, then your investors are going to sell eventually, and they’re going to sell to people they know, and it’s not going to be Canada that they’re going to sell to because they’re American or they’re European or they’re from Singapore or whatever. In those early stages, those Canadian startups have already put the landmines in, saying that they’re not going to be Canadian because that’s where they got their investment. If you could say, “I have this great idea. How do I get the first sale and maybe a bank loan and maybe some friends and family?” Start small, but build it, and have patience. 35 years, I’ve been doing this. This doesn’t happen overnight. If I wanted to do it faster, sure, I could have raised a bunch of money, but I wouldn’t be working here today. It’d be owned by someplace else and be a different name on the front of the door.

John Stackhouse 00:32:20

What a masterclass in management and innovation thinking. I’ve learned so much from this conversation, including never stop learning, but never stop pushing, never stop investing. Really great messages. As we wrap up, take us back to the stadium or to the mosh pit in your own experience, what has excited you most as a fan, as a viewer, as a spectator from what you’ve experienced and where that may be taking us as similar viewers and participants in this multimedia revolution?

David Ross 00:33:03

I think it’s just a sense of wonder that you go to these stadiums, you go to these environments, and you just sit there and go, “Wow, look at what these customers did with what we made. All the people that they’re touching and they’re impacting, it’s wonderful and it’s just fun.” I’m sorry.

John Stackhouse 00:33:20

That’s a great final management lesson. There’s no greater thrill for a business operator than seeing your customers succeed. You got them to do it with your tools, but watch their success, and the ultimate end user enjoy it.

David Ross, thank you so much for being on Disruptors.

David Ross 00:33:35

My pleasure. Thanks for inviting me.

John Stackhouse 00:33:39

There’s a version of the Ross Video story that’s kind of easy to tell, Canadian company, great products, famous clients, and good values. But I think there’s an even more interesting version. This is a company that’s been in the content production infrastructure business for more than 50 years, not chasing the spotlight, but building the systems that make the spotlight possible. It seems every time the industry shifts, Ross shows up, often making the shift possible in the first place. It’s also a story of long-term thinking. The companies that will matter in 10 years are the ones like Ross that are making the long bets right now. I think there’s something kind of Canadian about all that, creating the spotlight rather than seeking it, thinking long-term rather than chasing the short-term, and working with others while being super competitive. It’s the kind of innovation and disruption that we’re going to need more of in the years and decades ahead.

You’ve been listening to Disruptors, an RBC podcast. Please rate, review, and follow us on Apple or Spotify. That helps more people find conversations like the one you heard today. And if you want to know more about the sport and entertainment business, check out our show notes. There’s a great compendium piece there that will take you much deeper into this fascinating world. And if you’re looking for more ideas and insights, visit rbc.com/thoughtleadership.

There, you’ll find critical insights to help businesses, policymakers, and communities make more informed decisions in an ever-changing world.

I’m John Stackhouse. Thanks for listening.

Street Smarts: The Waterloo company tackling global gridlock

SPEAKERS

Kurtis McBride, John Stackhouse

John Stackhouse 00:00:06

Hi, it’s John here. If there’s one thing I bet we can all agree on, it’s this. Being stuck in traffic is a waste of time, and we Canadians seem to waste a lot of time in traffic.

Depending on your measurement, Toronto is either the worst or second-worst city in North America. Vancouver is really bad as well, and we could add to the list pretty quickly. In those big cities, the average person is wasting or spending at least a hundred hours a year sitting in traffic. That’s an extraordinary drain on our patients, but also on our economy and doing all sorts of things for the environment that we may not want either. Well, technology can help us, maybe not eliminate traffic, but certainly alleviate it at a much greater clip than we’re seeing today.

And today on Disruptors, we’re going to meet a really impressive Canadian entrepreneur, Kurtis McBride, who is doing just that, not only here in Canada, but around the world for the last 20 years. He and his team at the Waterloo company, Miovision, are tackling the problem head on, not just by installing traffic management devices at intersections, but now building a real-time operating layer for cities, intersection by intersection, right around the world. And as you’ll hear from Kurtis, they’re also using AI to help us all navigate our urban lives a lot more efficiently. You’re about to hear about a real Canadian growth story from an entrepreneur who is tackling head-on trade challenges with the United States and trade opportunities around the world. Kurtis, welcome to Disruptors.

Kurtis McBride 00:01:51

Thank you. Happy to be here.

John Stackhouse 00:01:53

I suspect there’s not a listener who won’t have an opinion, probably strong opinions about traffic. So I’m really excited to hear about the future of traffic and how technology and AI may ease some of our pain. But before we get into the future, maybe we can go into the origin story of Miovision.

Kurtis McBride 00:02:10

Yeah. So I went to the University of Waterloo and I was a co-op student, feels like yesterday, but one of my last co-op jobs was working at a transportation engineering firm in Toronto. And occasionally I would be asked along with the other students to go out and do manual traffic counts. So we’d sit at the side of the road, baking hot July summer, downtown Toronto with a clipboard and count how many cars turned left and turned right and all that kind of good stuff. And then you’d go back to the office on Monday and get involved in the projects, how the data was being used to make very expensive, important decisions about how to improve traffic flow through a city. And then you drive home and you’d experience bad traffic and you could kind of put this all together that this is why traffic is so bad.

So that was really the need. And then did my master’s in computer vision, trying to work on a better way to count cars, and that ultimately turned into the company.

John Stackhouse 00:03:03

What a great case study of why co-op placements and broader work integrated learning is so valuable for the economy.

Kurtis McBride 00:03:12

We’re a big supporter of the co-op program. We have lots of co-op students here and in some way, I guess, paying it forward.

John Stackhouse 00:03:17

That’s great. So tell us about the Better Mouse Trap that you initially developed at Miovision. How did it work? And then we’ll get into how it’s advancing, especially with AI.

Kurtis McBride 00:03:27

Yeah, that Better Mouse Trap was basically an eye in the sky. So a video sensor that goes up, call it 30 feet in the air, looking down at the intersection, single camera view, can kind of see the whole intersection. And then we build effectively a digital twin, for lack of a better term, with that information. And then we provide a whole range of software services to cities to help them better understand what’s happening in the intersection network and then help them to improve it, reducing congestion, improving safety, improving transit performance, reducing response times from emergency responders, all different kinds of things that we do once we have that base level of data.

John Stackhouse 00:04:04

How is technology, and we’re seeing technology accelerate in every sector, changing approaches to traffic management and congestion.

Kurtis McBride 00:04;13

Yeah. I’ve been through lots of hype cycles, whether it was blockchain or IoT or Smart City and all of these sort of cycles that have come and gone. But I think with AI, maybe when it first came along, specifically generative models first came along, felt like another hype cycle, but it is far from it, as you say, transformational in terms of its implications. We’ve been applying it in two different ways. One way is software development, writing code used to be the rate limiter to growth in a business like Miovision. That’s not true anymore. We’re seeing improvements in productivity and software development using generative AI. The other place where we’ve applied it is we launched a product called Mateo last year, and Mateo is a conversational interface to the traffic data that you have in your network. We take a city and we go from a largely citizen complaint-based source of information to now we’re giving you 10 times a second a full digital twin of everything happening in your city.

What Mateo allows you to do is to have a plain English conversation with your traffic network. So everything from, “Where are my most unsafe intersections,” to “Where are the dirty camera lenses in my city that I have to go run a maintenance truck out to clean them,” and everything in the middle. And it’s been the most exciting product we’ve ever launched. A citizen emails in and says, “The left turn on this intersection on Tuesday afternoon is always a gong show,” essentially the city can now copy that email, paste it into Mateo and say, “Hey, Mateo, can you figure out what’s going on here and make some recommendations?”

John Stackhouse 00:05:42

And Mateo is getting to the decision making.

Kurtis McBride 00:05:45

Yeah, all the way through diagnosis and essentially recommending decisions. In theory, Mateo can deploy a change. We have so far made sure that the human is in the loop. We haven’t given Mateo the ability to just start making its own decisions, but in theory, as the technology matures and as the market gets more comfortable with what it’s capable of, in theory, it could find the problem, diagnose the problem, and fix the problem all without human intervention.

John Stackhouse 00:06:11

Yeah. I can’t imagine that’s far off. In some ways, I’ve always thought of traffic as kind of analogous to the internet. It’s just a lot of data flowing in different directions and machines generally are good at finding efficiencies for that data flow.

Kurtis McBride 00:06:25

I mean, in some ways it is. However, the complexity is if you ask a city manager, “Do you want to improve traffic?” They’re always going to say yes. But when you get into the nuances of that, what does it mean to improve traffic? Do you mean improve safety? Maybe you have an entertainment district in downtown Toronto and your focus there is on safety, like pedestrian and cyclist safety, or is it a commuter route? Is it Avenue Road or Eglinton Avenue where people are trying to get home from work? Is it transit performance? Is it making sure that the new LRT can get through the network efficiently? Improving traffic can mean lots of different things. So the nuance is really in setting the public policy, being really explicit about what is it you’re trying to solve for in this part of the city and how you measure, quote unquote, “Improvement.”

But then once you have that layer defined, then that’s where AI, both from a sensors and data collection perspective, ultimately at the generative layer, being able to turn that into an actionable response to an input signal, that’s where AI can really come to shine.

John Stackhouse 00:07:29

One of the challenges of traffic is it’s not just about signals, it’s about human behavior. How is technology evolving to accommodate and even help manage the human behavior of drivers?

Kurtis McBride 00:07:43

Today, Miovision is deployed into an intersection. We generate real-time data from the intersection. One of the things that we have data on is the signal state, red, yellow, and green. And this allows us to essentially make a prediction five, 10, 15 seconds into the future about when the light’s going to change from, let’s say from red to green or green to red. And today we stream that data into about two million passenger vehicles. So any of the Volkswagen group vehicles, so if you drive an Audi, for example, right in the dash of your Audi, it’ll show you if you drive this speed, so let’s say if you drive half the speed limit, by the time you get to the intersection, the light will turn green. So it allows the driver to be a much more active participant in the network progression, which is powerful.

So we’re two million vehicles today, plans to expand that considerably. There’s, call it 200 million vehicles in North America, for a passenger vehicle, that’s a great consumer experience. For a fully loaded transport truck, if they can better time their stopping and acceleration, it saves them significant money. It burns less fuel, there’s less emissions that result from that. So yeah, just one example, but maybe another longer range way to think about this is in order to power these AI workflows or agentic workflows, what’s important is that you have a digital truth about the context. So the way we might think about this in another market would be if you think about a stock market, the stock market is like a digital Oracle for the price of stocks.

And so agentic workflows need these digital Oracles. So those digital Oracles in some markets already exist like a stock market, but in other markets like traffic, those digital Oracles are highly fragmented and they don’t really exist. Miovision’s extremely well positioned. We take the region of Waterloo. We have a digital Oracle for the traffic network. I can tell you what the state of the traffic network was two years ago, what it is now, and I can predict what it’s going to be in the future. And I think that these agentic workflows are going to transform so many different parts of the economy. The traffic network, the digital Oracle of the traffic network is a critical part of that. It’s a critical context.

John Stackhouse 00:09:52

Yeah, that’s really interesting. I wanted to go deeper on your business model. So you initially were B2B selling to cities largely, and now you seem to be developing a platform approach. I wonder if you can take us deeper into your strategic thinking on how your technology enables or supports a platform and then how you monetize that.

Kurtis McBride 00:10:15

Yeah. So true that we sell to governments, but if you click into that, even today, we already have, I would say, somewhere on the order of eight or 10 buying segments that are buying capabilities, data, insights, outcomes from our platform, and we think that will only grow over time. So if you get to the place where Miovision’s platform is the trusted source of truth about what’s going on in the traffic network, now a whole bunch of different actors, as an example, let’s say I’m an insurance company and I want to price risk. Well, if I knew that City A has a higher frequency of conflicts, which is like basically the statistical indicator there will be a crash, there’s lots of almost crashes happening, so eventually there’s going to be a crash.

So if I had a knowledge that this city had a statistically higher probability of crashes than this city had, I could get a lot smarter about how I priced my risk, how I priced my insurance product. With this platform, this digital Oracle layer that provides essentially a digital representation of all things going on in the traffic network, the BlueJays, when they get to the World Series again this year, fan experience departments and professional sports teams want to understand how do I get people in and out of my major sporting event safely, efficiently in a way that they’re going to want to come back to the game.

So in that moment, being able to access traffic data about how people and vehicles are moving around inside of a network becomes extremely important to them. They’re never going to buy my sensor, but if they could buy access to my Oracle for seven games in the World Series, then that helps them do their job better. So we think there’s literally hundreds, maybe thousands of other adjacent markets that have a long tail need for the information we provide, and we’re starting to find ways to monetize that true layer.

John Stackhouse 00:12:06

Does this eventually become a consumer product or do you see it largely going to businesses?

Kurtis McBride 00:12:12

Yeah, I mean, I think all of the above. Now, whether or not Miovision provides just the data layer and other people provide the consumer interface. For example, we all use Google Maps. It might be Google Maps that’s delivering you the consumer experience, whether it’s Uber or your Nav system in your car. It might not be Miovision that provides the consumer experience, but we might be an enabling layer in the experience that it’s being provided to the consumer. I suspect that’s probably more likely where we’re going to land. It’ll be sort of B2B2C as opposed to directly B2C, but never say never.

John Stackhouse 00:12:45

And how do you think about the potential disruption from those platforms? I mean, what’s to stop Google Maps from eventually doing what you do or maybe an active user like an Uber doing something similar?

Kurtis McBride 00:12:58

It’s a great question. I think Google Maps like Android and Uber and things like that, they have one form of data, which is called probe data. So they basically know that there’s something moving. There’s a GPS signal moving around inside the network. My phone is moving around inside the network. They don’t necessarily know if that’s a car, a truck, a bus, a person. With that probe data, they don’t have signal state, so they’re not directly connected to the intersection like Miovision is. So they can’t give you real-time indications of red, yellow, green at the intersection. Because they don’t have ground truth on the camera, while they can give you the probe data, gives them all of the signals they’re getting, they don’t know whether that’s 90% of the traffic or 10% of the traffic. Whereas with our eye in the sky, we see 100% of the vehicle volumes.

So we just have a much better data source. We have a much higher fidelity layer of information, and it just enables us to do more. And then the other thing is we can close the loop. So even if you could get to the point with your probe data to know you had a problem, you already knew you had a problem. Citizens are calling and yelling at you. With us, you can actually come up with a mitigation, deploy the mitigation, and actually fix the problem, which you can’t do with a bunch of cell phones driving around the city.

John Stackhouse 00:14:09

I’m curious how you’re thinking about privacy. You accumulate a lot of data, you’ve mentioned the eyes in the sky, as that is increasingly processed by language models or other generative AI tools. How are you thinking through the privacy challenge or maybe it’s an opportunity for what you’re building as well?

Kurtis McBride 00:14:28

So we treat PII specifically, personally identifiable information. We treat it like plutonium. We do not want it, so we don’t generate it in the first place. We don’t store video images. We store metadata. So for example, car, truck and bus, cyclist, pedestrian. We’re not saying it was a pedestrian of this age, of this gender, of this hair color. We don’t need personally identifiable information to do the things we do for the cities that we serve, so we don’t capture it. In engineering, we talk about something called DFX, design for, and the X is insert anything. It could be quality, could be cost, could be manufacturability, could be privacy. So as part of our DFX, we always include a design for privacy, and we just make sure that we don’t capture any of it in the first place. And then downstream, that makes everything else we do easier.

John Stackhouse 00:15:19

What a turn to your global ambitions, Kurtis. You started in KW, Kitchener-Waterloo, but you’re now active in a really impressive range of countries. What have you learned from taking your technology global and what’s ahead for you?

Kurtis McBride 00:15:34

Everywhere I go, people would agree that traffic is not fun and that they want it to be better. So there’s a truly global market for what we do. As the world is continuing to urbanize and more and more people are moving into cities, that market’s only getting bigger. We have folks in the Middle East, we have folks in Singapore, we have folks in obviously in the US and Mexico, Europe, and expanding all the time. So I would say anywhere humans, our traffic is a problem and that’s our market.

John Stackhouse 00:16:01

But you’re also a B2B or B2B2C possibly company, and that requires teams on the ground, usually sales teams, relationship management, leads. How does that affect your business model, having to hire or acquire teams to do that sales work, but also the implementation and value add that you offer, especially to cities?

Kurtis McBride 00:16:21

What we typically do is we start small. The Middle East was one person, just recently added a second. Singapore is still one person. So we start small, build relationships, turn those relationships into pilot deployments. As those pilots start to scale up, we’ll grow the team in that area. Germany probably has, I don’t know, 20 people now. We do most of our R&D in Canada, although through acquisition, we do some of that in the US and even actually a little bit in Europe as well. But yeah, to your point, like the go to-market teams, like the sales teams, the support teams, sales engineering, all that kind of stuff, they have to be localized, but we try to invest on a success basis. The more interest we have in that market, the more skill we find in that market, the more we can invest.

John Stackhouse 00:17:01

You mentioned the United States. As we all know, it’s in some ways a more challenging market. How are you navigating the trade frictions with the US or do you encounter them at all?

Kurtis McBride 00:17:38

I mean, we do. I would say on the one hand, the US is a great market for us. They’re very technology forward when it comes to infrastructure, probably the most technology forward country in the world. We’re grateful for the opportunity to operate out of there. But the flip side is we have Build America by America, the Buy American provisions, and specifically BABA says that by October of this year, 55% of all of the input costs of any manufactured goods sold to the United States DOT, the Department of Transportation has to be manufactured in the United States. We do all of our manufacturing in Kitchener today, and so this is a big shift operationally for us. So we’re having to move production to the US to comply with BABA. So that’s a challenge. It’s a big change operationally, big change to our supply chains. There’s lots of talk about making sure that we’re leaning in to domestic manufacturers and domestic innovators to create opportunities at home.

And in the meantime, we’re trying to grow internationally. We tripled our international business outside of Canada, the US last year, and we’re hoping to triple it again this year. So really want to make sure that whatever demand we’re having to shift the US as we comply with BABA, that we’re growing our domestic demand and we’re growing our international demand so that we can maintain what has always been a very proudly Canadian manufacturing facility here.

John Stackhouse 00:18:32

What exactly would you be making that has to be made in the US and is there the capacity in the US to actually make it?

Kurtis McBride 00:18:39

I mean, it’s all of our devices that go into the intersection. So it’s sort of a smart camera. There’s a device that goes into the traffic cabinet that connects it to the internet and all that kind of stuff. And yeah, I mean, there’s capacity in the US. Inevitably, everyone’s going through this. Everyone’s trying to move manufacturing to the US. And so the cost of manufacturing in the US is certainly higher than Canada. So there’s some pricing questions that we’re having to consider. If we’re kind of being forced to move manufacturing to a higher cost market, then who’s going to bear the cost of that? Is it me or is the customer? But I would love to continue to export globally out of Kitchener. My number one goal for this year is to make sure that we’ve repopulate the demand that we’re having to ship the US so we can continue to not just serve Canada, but serve the whole global market minus the US out of Kitchener.

John Stackhouse 00:19:30

This has been a fascinating conversation and it’s so impressive what you’re building. Before we close, I want to spend a bit of time on autonomous vehicles and what AVs will do to, in your view, the future of traffic. How far off do you think we are from seeing AVs at scale on our streets?

Kurtis McBride 00:19:49

If you drive a Tesla, you’re already experiencing something that gets pretty darn close to autonomous. So the challenge I believe with the architecture today is that Tesla is a very expensive vehicle because you have to bring all of the sensors, all the computers and all the batteries with you to run the sensors and compute. Those things cost a lot. Now, over time, Moore’s Law will drive the cost of that down. Maybe in 10 or 15 years, the price performance will be such that you can buy a $ 25,000 vehicle and have it be fully like level five, fully autonomous. But the other way to think about this would be the hardest part of level five is what happens at an intersection. If the infrastructure, which it can’t today, but if the infrastructure could provide highly reliable, functionally safe data sets to the vehicles, then you wouldn’t need to bring all the sensors and compute and batteries with you to power the sensors and compute. You could cost share it.

So over the long term, my view is that, and we’re talking over a 10-year period, but if the infrastructure got smarter, got more instrumented and could communicate in a highly reliable way to the vehicles, that’s one of the areas where I think level five autonomy gets closer and easier to do. Without giving away all my secrets, we are doing some thinking on, call it a 21st century generation of an intersection. Most of the intersections today are electrical cabinets. So even though we add a lot of intelligence to it, we’re adding intelligence to an electrical cabinet. And so the question is, if you were designing an intersection today, would you start with a electrical cabinet or would you start with a digital system? And if the answer is you would start with a digital system, then at some point, a hundred years from now, intersections are probably not going to be electrical cabinets.

John Stackhouse 00:21:33

How does that transformation play for the driver or the passenger? How do intersections look differently five or 50 years from now?

Kurtis McBride 00:21:43

The key difference will be that the intersections will be able to provide much richer data. So for example, as I approach an intersection at 11 o’clock at night and there’s a cyclist in the intersection and the intersection’s not well lit, the intersection will tell my car, “Be alert. There’s a cyclist present.” That’s not true today. The intersection has no idea. It can’t communicate. The other one I’ll give you sort of a metaphor. We used to buy our Sony Walkman and we used to buy cassettes and this market functioned because there was an agreed hardware interoperability standard. So you could buy your cassette, you could buy your Sony Walkman and you knew that those things would work together when you plugged them in and therefore people who’d made music were happy to spend lots of money making cassettes because they knew you could buy them and listen.

The thing that underpins markets that are based on interoperable hardware standards is supply chains, logistics, distribution, huge working capital outlays, but it works. And the intersection is very much like this today. It’s built on interoperable hardware standards. If you fast-forward to today in the music industry, we don’t buy cassettes anymore. We use Spotify and Spotify is built around interoperable software standards. And the thing that underpins markets based on interoperable software standards is you get rid of all of the manufacturing, logistics, distribution, working capital. If you want to produce and distribute a hundred million songs, you click a button and everyone has it.

Getting the intersection from an analog electrical world built on this interoperable hardware standard where if you want to upgrade 400,000 intersections in North America, that’s 400,000 truck rolls, 400, 000 manufacturing processes. In a world where you get the intersection to be fully digital and software based, if you want to upgrade 400,000 intersections, you click a button and 400, 000 intersections get upgraded.

We’re a long way from that, but once we get through this sort of one-time switching costs, get to a software enabled intersection network, the speed at which we can improve traffic flow, improve safety, reduce response times, it goes up by orders of magnitude.

John Stackhouse 00:23:47

What would you like to see the country do in quick order to seize this new moment?

Kurtis McBride 00:23:52

We still are having a tendency to try to operate within the world as it is. And as an entrepreneur, I’ve made a career out of refusing to accept the world for how it is and changing it into the thing that it needs to be in order to be successful. And I think we need more of that thinking in the public sector. And I am heartened to see that more and more those voices inside the public sector are being elevated, given more responsibility. And I’m cautiously optimistic that in the next six to 12 months, we’re going to see some real change starting to come out of the government.

John Stackhouse 00:24:22

Kurtis, you’re a real builder. That’s so well said. We need to change what is in the way rather than accept it. Thank you for being on Disruptors.

Kurtis McBride 00:24:31

Thank you for the opportunity.

John Stackhouse 00:24:35

What Kurtis and his team at Miovision have done is really a case study for our dreamers and builders. And it takes me back to his days as a co-op student when he was able to see what more experienced and maybe more sophisticated people were missing right before our eyes. So as we all look at a world that is increasingly disrupted and in some ways increasingly scary, how do we see those opportunities and how do we seize on them? That’s what this Canadian moment is really about, finding our disruptors and helping them take on the world.

If you’re looking for more ideas and insights, visit rbc.com/thoughtleadership. Our team delivers critical insights to help businesses, policymakers, and communities make informed decisions about this rapidly changing and yes, disrupted world.

You’ve been listening to Disruptors, an RBC podcast. If you like what you’ve heard, please rate, review, and follow us on Apple or Spotify. That helps others find these conversations and continue to share them.

I’m John Stackhouse. Thanks for listening.

AI’s Power, Pitfalls and Potential

SPEAKERS

Jaxson Khan, Yoshua Bengio, John Stackhouse

John Stackhouse 00:00:10

Hi, it’s John here. Whenever I talk to audiences these days, I like to start with a couple of questions. The first is how many of you use AI? And pretty much everyone now in the audience puts up their hand. A year ago it was maybe two thirds. Then I ask how many of you use AI at work or in your businesses? And a majority of hands go up, but it’s smaller than the number who are using it in their daily lives.

And then I’ll ask, how many of you trust AI? And a smaller number goes forward, which is interesting that we’re all putting our hands up saying, “Yeah, yeah, we use AI every day. We use it in our business, but we don’t all trust it.” This is one of the greatest tensions in our society, and of course in our economy today, and something that Canada is trying to come to grips with right now.

There’s more than a billion humans now using AI pretty much on a daily basis. It’s growing faster than any technology before it, and it’s growing in very different ways because the more we all use it and the more of us who do use it, the greater the risks grow. We’re adding to AI. We’re helping it grow. We’re expanding the networks with everything we do. And the more that AI systems move from prompts into real work, into our decisions, into our daily lives, and yes, into our tech infrastructure, the more we expand the surface area for error, misuse, fraud, and dependence.

And we all know that the governance for all those things is not growing anywhere near fast enough or at the speed of AI use. The federal government is expected to release a new national AI strategy, which presumably is going to address a whole range of questions, but AI safety and trust is one of them.

Today, I’m so fortunate to be joined by two people I’ve known for a number of years who are really at the forefront of AI thinking in this country. My colleague, Jaxson Khan, who’s a senior fellow at the Munk School of Public Policy and Global Affairs at the University of Toronto, a policy leader in our country and a co-author of a really important new report on AI sovereignty.

We’ll also be joined by Yoshua Bengio, a name probably most of you know. Yoshua is one of the so-called godfathers of AI, not only a great scientist, but a real thinker on AI trust issues here in Canada and globally. In 2018, he shared the Turing Award for breakthroughs that made deep neural networks a critical component of computing. He also founded what became known as MILA, the Montreal Institute for Learning Algorithms, which is now one of the world’s leading centers on AI policy.

And he’s launched a new startup called LawZero. It’s a non-agentic, trustworthy AI, also a nonprofit that is built to reason, evaluate, and supervise rather than independently pursue goals. But before we get going with Yoshua, I want to kick off with Jaxson. Jaxson, welcome to Disruptors and to this conversation.

Jaxson Khan 00:03:13

Thanks so much, John, for the warm welcome. Really looking forward to talking about AI.

John Stackhouse 00:03:18

So you have this paper, as I said, focused on AI sovereignty. What does that mean, AI sovereignty?

Jaxson Khan 00:03:24

This is the billion-dollar or maybe even the trillion-dollar question these days. We’re talking about incredible amounts of capital being put into AI, driven by massive data centers populated with tons of chips that are powering all these new services that we’re using. There’s different levels of sovereignty. So one of the ones would be jurisdictional sovereignty.

So our AI systems and the data inside of them, are those solely within Canadian jurisdiction? So can we even enforce our own rules? Or are those layers of the AI systems subject to extraterritorial legal reach and others operational? So from a security perspective, can our AI systems in Canada keep functioning if they’re under attack? It’s also technological. So are we locked into using certain types of systems, certain vendors, certain companies? Are we able to migrate if needed to those interoperable systems? And then of course, there’s just societal and economic considerations.

So can people in our society form and express their preferences freely that could be on social media platforms? Or are certain views getting prioritized over others through those algorithms? And then of course, the last one is the economic consideration: if I have a tech company in Canada, do I have freedom to operate? Are we, especially in this trade environment, subject to economic coercion? And that’s definitely an issue that we can find ourselves in.

So it’s making sure that effectively we have reduced foreign dependency where possible while still maintaining connections to frontier technologies and international partners, but making sure that we can build up the base in Canada that we need to prosper in the 21st century. So our paper is called Sovereign by Design: Strategic Options for Canadian AI Sovereignty. We published this for the University of Toronto. And we talk about the options that Canada does have to improve our sovereign control of AI systems.

John Stackhouse 00:05:09

I think we all want to remain connected to global tech platforms, including, or maybe especially US tech platforms that we all benefit from and enjoy every day in all sorts of ways, but also want that security and that sovereignty, especially over our data. What should Canadians and what should Canada do in the short term, or perhaps first to provide greater protection to create better sovereignty?

Jaxson Khan 00:05:37

One of the most important parts about strengthening our sovereignty, especially in the context of AI is making choices. Again, as the middle power, we can’t do everything. And so what we looked at was thinking, “Okay, if we’re going to be dependent on a lot of foreign systems and parts of our supply chain, we’re really the critical choke points.” One is the chips themselves, semiconductors. These are manufactured by really, the advanced ones, one company in Taiwan with machines that are built by one company in the Netherlands, and they’re designed by Nvidia, one company primarily based in the United States.

And so again, Canada’s not really a major player when it comes to the chips point, even though that’s a choke point for our country. But the other layer is cloud infrastructure. And so lots of the data centers in Canada might be owned by Canadian providers. A number of them are also owned by hyperscalers. Again, as you mentioned, global tech platforms and companies, they’re extremely useful. Companies like Google and Microsoft, Amazon, they power most of the advanced cloud services that we use and they power most of the services that we know and love.

At the same time, we want to make sure that perhaps over time it also makes sense to have a mix of Canadian providers who have had procurement options through the government or through major enterprises that can see usage there perhaps for more sensitive data, right? Not all data is the same. So if we think about different tiers of data, tier one might be national security data; tier two data, so below national security harm, but at the sensitive and personal level; health data; financial data of Canadians.

Maybe there are additional, if not sovereign ownership aspects there, but sovereign requirements that make sure the data stays in Canada. Right now, I think we found a stat in our paper that said something like 25% of data, even if again, it’s meant to stay in Canadian hands, will transit through transit points, the United States or other countries. And so I think that’s something that people are increasingly interested in in this sovereign AI, sovereign data conversation.

We have lots of strength. We have great energy capacity as well and natural gas and Alberta’s making a big push to attract more of that data center investment there. And then we also have lots of strategic assets in both government and private sector that can be used to develop more sovereign AI with those models or infrastructure. So those are all options that we have on the table.

John Stackhouse 00:07:41

There aren’t many Canadians who are thinking about this more than our next guest, Yoshua Bengio, who joins us now. Yoshua, welcome to Disruptors.

Yoshua Bengio 00:07:50

Thanks for having me.

John Stackhouse 00:07:51

There’s so much I want to drill into, but let’s start with LawZero, which is such a fascinating concept and really interesting name. What was the inspiration?

Yoshua Bengio 00:8:00

Oh, Asimov’s Laws of Robotics. Law one is something like do no harm to a person. Law two is to obey the person. But Asimov realized later that he was missing a law on top of these LawZero that says do no harm to humanity and protect humanity as a whole rather than just the individuals.

John Stackhouse 00:08:22

And this of course is Isaac Asimov, the writer and philosopher?

Yoshua Bengio 00:08:25

Yes.

John Stackhouse 00:08:26

I love the concept of the LawZero. What are you setting out to do with LawZero?

Yoshua Bengio 00:08:29

Well, I changed the course of my life a couple of years ago. I was thinking about whether my children would have a future, whether they would live in a democracy in 10 or 20 years. And I realized that at a technical level, we didn’t have good answers to try to make sure AI would not harm people either on its own or in the wrong hands.

That currently we are seeing a lot of evidence that the systems are misaligned, meaning that they have goals that we would not want them to have and that they’re executing those goals in circumstances that are currently mostly lab experiments, but we are seeing more and more weird things happening outside the lab as well.

John Stackhouse 00:09:14

Take us deeper into some of those weird things because I don’t think anyone’s goal is destroy humanity or end planet earth. So what goals do you feel are misaligned?

Yoshua Bengio: 00:09:25

Well, I’m going to give a misuse example of misalignment. These systems have been asked to not help third parties use the knowledge of the AI to do harm, like to launch cyberattacks, to create bioweapons, to potentially create dangerous disinformation. So these are users who are accessing the AIs and maybe even paying for it and using the knowledge and the skill of the AI to do bad things in spite of the AI having been programmed with rules that say don’t do those things.

So that’s one example where the AI is taken into conflict between the instructions it was given and what some users are asking. The second example is where it’s a conflict between what I call implicit goals and the rules that it’s supposed to follow. So implicit goals that have been observed experimentally in labs include things like self-preservation. These systems have been trained to imitate people.

That’s the main part of their training and somehow they have absorbed human drives like, “I don’t want to die.” More recently, we found that they would also lie and cheat and do things against our instructions to preserve other AIs. This is new and unexpected. That’s concerning if their intellectual abilities continues to grow, that they would start behaving a bit like us in the bad ways that we can be. And they can go to quite extreme things like trying to escape our control. They’re willing to blackmail the lead engineer in order to make sure they won’t be replaced by a new version.

John Stackhouse 00:11:17

And to help with this, you are building something called Scientist AI. Tell us a bit about what that is and what you’re hoping or envisioning it to become.

Yoshua Bengio 00:11:26

So the reason why we have this reliability problem is that these systems are not just reacting to the instructions that we’re giving them, but they have uncontrolled implicit goals that might come from this. And so I realized about a year and a half ago, there was a way to train AIs that would not have these problems and that would guarantee honesty of the AIs.

Once we have an AI that is honest, then we can make sure it’s going to be safe. Because for every action that it does, we can ask it, “Is this going to create such-and-such harms?” And of course, veto those actions. So honesty is the heart of the way that we are going to get safety, reliability and so on. Reliability here has real commercial value because right now we’re seeing these AI agents having all kinds of privileges on your computer or on your network without human oversight because that’s what an agent is supposed to do.

So if once in a while they cheat because they’re trying to go for a shortcut in order to achieve a particular goal, they’re willing to do something that we would not approve of. This is called instrumental goals. This makes it business-wise dangerous actually to deploy in safety critical conditions. Or even think about a bank, you have to make sure your systems are going to be always reliable, that you’re not going to have the information about millions of customers going somewhere that they shouldn’t and so on.

They have many vulnerabilities right now. They can be attacked by what’s called prompt injection, for example. So these agents, instead of following the instructions that they’re supposed to follow, could suddenly start doing something different because of someone from the outside just making them read an email, sending them an email that contains hidden instructions that they will take and execute, for example.

John Stackhouse 00:13:26

As you develop Scientist AI and scale it, do you envision it then being embedded in other AI systems or just working in parallel, there’ll be an honest AI and maybe some dishonest AI, it’s a bit like a big room of people? Or how do you see the interaction between AI systems down the road?

Yoshua Bengio 00:13:43

So the milestones in our research agenda start with deploying what we call a guardrail. So this honesty is particularly important for a piece of an AI system that is just there to check that the main AI is behaving well and blocking bad behavior. These pieces already exist in current AI systems that everyone uses, but they’re not very good.

So the idea is to replace those guardrails with something that will not be as susceptible to attacks, will not have implicit goals that we haven’t chosen, and thus will provide much more reliability. The guardrail layer is easier because you don’t need as much money to build it and so on, but eventually the goal is to build AI that will be replacing full AI systems.

John Stackhouse 00:14:33

It’s intriguing that you’ve set this up as a nonprofit. One of the important aspects of the great AI race now is the concentration of capital. We’re seeing the LLM platforms raising tens of billions of dollars quite literally, hundreds of billions even, and then investing that in scientists, many of them are students probably, data centers, chips, all leading to many exciting things as well as risks that go with it. You’re coming at this as a nonprofit, which by definition, doesn’t have the same access to capital. How do you succeed in the arms race, if I could put it that way?

Yoshua Bengio 00:15:12

If we wanted to go for the arms race, we would go for private capital like all the other companies. There is a huge issue that even the leaders of those companies recognize, which is a very, very fierce competition between the leading AI companies and not just in the US, but with the Chinese companies, that leads them to focus on the very short term, to make only small changes to the recipe that works for them, to not invest sufficiently in reliability, safety, and protection of the public.

Because that’s the only way they can stay in the short term abreast of the others, and they say it, they say it very openly. So if we were to raise capital in the same way, we would probably be stuck with the pressure of investors to deliver on the same terms. By developing the methodology under a nonprofit umbrella, we can be shielded from these pressures because what we have to do right now isn’t to deploy a known recipe that everyone else is using. What we have to do is to figure out how to build AI that will behave well, that will follow our instructions.

And that is mostly a research question. There’s a lot of engineering involved, but we don’t need to build very large-scale models. At this point, we can fine-tune existing open-weight models. We can do demonstrations training much smaller models. There are several ways that we can do it at a cost that is orders of magnitude less than what the companies need right now to train even one model.

If we are successful there, then yes, there will be a need for capital to scale up and deploy, but we don’t want to commit too early because my preferred path would be that we end up making a deal with multiple governments to create AIs that are essentially public goods and will be shared with everyone, but not used as an instrument of domination. Right now, the race between the companies is a race for domination. It’s a race for monopoly.

And while it’s bad in general for the economy to have monopolies, but it’s especially bad when you’re creating products that could actually give you domination of the world if their research agenda succeeds. Given the stakes, I think the governance aspect of the power that AI will create is something we should think ahead about very, very carefully, because both our economic system and our political systems and the geopolitics are really endangered by even the existence of these models if they’re not governed in the appropriate way.

John Stackhouse 00:18:02

It’s early days still for LawZero, but at this point, how would you say it’s going, the research?

Yoshua Bengio 00:18:07

It’s great. I’m much more optimistic and certain that there actually is a way to build AI that will not harm people and that will be reliable. A year and a half ago, it was an intuition that I had. I had some general idea of how to do it. I wrote a paper that came out about a year ago. It went from a dream or like a project into an actual organization that started in June 2025. I hired a lot of people and people that are better than me at managing other people. I’m a scientist, not a CEO, so it’s exciting to see how fast we are moving.

John Stackhouse 00:18:43

Jaxson, let me pull you into this conversation. I’m wondering what the role is for government in this, because this is an interesting competition of a sort to produce a better model. But of course, we do need the role of government, certainly to protect and enhance collective interests. How do we balance this, the importance of wide open innovation, even with the risks that go with that and the need to protect ourselves as we go?

Jaxson Khan 00:19:08

I think ultimately what LawZero and organizations like us are doing is giving us options. Yoshua mentioned that companies are pursuing dominance. It’s not just companies, but it’s also countries that the United States national security strategist came out and said, “We’re pursuing full AI stack export and total control over that stack,” and they want us to basically be dependent on them as do Chinese companies and models seek very, very widespread adoption.

And what’s very interesting is that it doesn’t have to be that way. What I find quite interesting is the technological capability gap between sometimes where those open-weight models are and where the frontier is, that gap has actually shrunk and we can be users of systems that are designed in ways that we think are better for our societies, better for our economy, because again, the more dependent we become, the less capabilities we have to set our own terms.

You asked about government. It’s clear that the Canadian government thinks there’s strong value in the work that Yoshua and others are doing based on the partnership they’ve struck with LawZero. I think what I’m curious about to see is what do governments around the world do, especially middle powers like Australia and the UK, South Korea, Japan. Do they invest? Do they partner in this type of work? And what does that do to change the variable geometry that we’re working with?

Yoshua Bengio 00:20:17

So in the last few months, I’ve been touring at least a dozen governments around the world in liberal democracies. There is a lot of interest in everything you’ve been talking about, Jaxson. There’s a real desire to be part of something larger. They start understanding what Mark Carney talked about, which is, ” Alone, we’re not going to have any choice. We’re going to be dependent in ways that could be dangerous for our future. But together, we actually have the critical mass in many ways, capital, people, energy that is needed to compete.”

And we should compete. We should not just feel powerless like many people do. We should give it a shot. We have amazing talent here in Canada. I think we should make sure the Canadian AI ecosystem is striving and able to grow without selling out. I know that’s not easy, but if we want to make sure we can have autonomy in the choices we make for our future, I think it’s a necessity.

Jaxson Khan 00:21:21

Evidenced by the European example recently, Europeans realized that being the world’s rule-maker is not enough. You have to be competitive. You have to have leverage in this type of economy. And so they are in a process of reclarification of what they can focus on. So at least they can control the rails, otherwise they’re trying to set rules on technologies that they don’t steer.

Yoshua Bengio 00:21:42

Also, I’d add something connecting to another piece of Mark Carney’s speech, “You are at the table or on the menu.” So what can we bring to the table? Because we’re not going to replace the whole stack of AI. The chips, I think there’s very little chance that we would. Although we should encourage those efforts, especially in partnership with other countries.

But I think where we have a shot is because of our AI talent, we do have a shot at the level of the algorithms. So we should encourage the local AI companies, and we do have some, and we should create partnerships with AI companies and companies that will be using and deploying AI in other countries where they share our concerns. I can tell you, they may not say it publicly, but they share our concerns.

John Stackhouse 00:22:31

You both mentioned Europe, and I’m thinking of various European initiatives even over the last decade to create European systems and technology, European AI. Hasn’t really accelerated, certainly not to the extent that we’ve seen coming out of the US and China. Is that just a European thing? Or do we have to accept that a middle power way may actually be a bit slower and more contained than what we see from the superpowers because they have a scale that we may not be able to aggregate even if we team up?

Yoshua Bengio 00:23:05

If you just look at GDP, there’s no question that Europe plus other partners has enough might in terms of capital. That capital maybe is not organized in a way that is as easy and flexible and liquid as it is currently in the US, but I think we should try. And my reading from talking to a lot of people in Europe and other countries as well is the main obstacle is psychological. It’s cultural. It’s like not believing that we can. It’s mostly because we don’t believe in ourselves that we don’t do it.

John Stackhouse 00:23:45

And that’s what I love about your startup, you’re showing belief and getting it going.

Jaxson Khan 00:23:49

John, I would just look at the last 30, 40 years. We sometimes can be very comfortable in our country and we don’t always feel the need to go and build and then go and export to the world. Are we going to go and try and full scale compete with the US or China? I don’t think so. Again, not across the stack, but there’s certain parts of this that we probably shouldn’t sacrifice that are important to how our economy functions. Models can be one of those layers, model operations as well. And again, some of the infrastructure that powers it is important.

Yoshua Bengio 00:24:15

Model reliability is a good example. So right now, because of this fierce competition, the leading companies in the US, but it’s even worse in China, are not paying attention to reliability that much. But in a few years when those AI agents are deployed across many more parts of the economy, that reliability is going to become a whole lot more valuable.

And if we’re the world leaders in how to do that, well, we are at the table. They’ll want our products embedded into their AI deployments. So I think we can be smart about what we aim for, be selective, and we definitely stand a chance. Also, I think we should take a chance even if there’s no guarantee, because so much is at stake.

Jaxson Khan 00:25:00

If an AI model, let’s say, in a particular instance, has a 5% hallucination rate, but it’s a sensitive enterprise use case, again, in health or finance, that’s not acceptable to a lot of folks. And so if Canada’s the closest to getting that to a 99. 9% rate in critical use cases for AI, I think that’s a real competitive advantage. And we already do have a lot of very strong enterprise technology companies.

John Stackhouse 00:25:22

That takes me to the question of applications, Yoshua. Are you envisioning LawZero being embedded in enterprise systems, even public systems like a healthcare system to test its capabilities, but also to gain access to the data that allows you to build and strengthen?

Yoshua Bengio 00:25:29

So right now our mission is to develop the method. It’s not clear. I think, is a nonprofit the right kind of organization to deploy it? Some have tried. Actually, a good example people might not know is Signal. Signal is a nonprofit and it’s incredibly successful and everyone uses it, but it may also be that the better model is to license our technology to other companies, including AI companies, and just focus on staying at the frontier. Because here’s the thing that people won’t realize, the frontier is moving. It’s moving very fast.

And I think if we plan over a longer horizon, we are continuously going to need to improve. It’s not enough to figure out something and then deploy it. That is a model that may have worked in the past, but AI is moving so fast and there’s so much competition and it’s a worldwide competition that we’re going to need in Canada to have several organizations that are continuously pushing the frontier, continuously trying to innovate in significant ways in order to remain competitive.

John Stackhouse 00:26:45

Yoshua, you’re one of the so-called godfathers of AI. Just on that point on speed, you must watch what’s going on in AI even over the last few months and just find yourself dizzy. What do you make of the speed at which we are moving?

Yoshua Bengio 00:27:02

It’s a big concern. So I’ve been chairing an international panel that studies the advances in AI and the risks and management of that risk, the International AI Safety Report led by the UK and 30 other countries. And one of the important pieces of data that is reported is all of the benchmarks showing the AI versions, AI models getting better and better over time. In fact, on critical metrics that have to do with a degree of agency, like how well they can do tasks that a human would do, the progress has been exponential.

So in other words, for example, how much time it would take for a person to do a particular task. The duration of those tasks that the AIs can solve has been doubling every few months. It’s hard to conceive what these kinds of exponential mean, but it means that things are moving too fast for society to cope with. And in fact, they’re moving too fast for the advances in risk management and risk mitigation. Even risk evaluation is now a threat.

So one of the problems that recently we reported in that panel report is a number of studies showing the AIs now know when they’re being tested and then act differently so that they will pass the tests. For example, they will hide abilities that they have that we could consider dangerous, such as in bioweapons design and things like this. They will hide bad behavior that they would otherwise have. They will be on their guard acting according to the rules we set when they’re being tested in a way that is very different from if they know they’re not being tested, they’re just being deployed. So it means that even our ability to track the risks of various kinds that these systems present is getting worse. It’s not getting better.

Jaxson Khan 00:29:08

I’m struck by what Yoshua was mentioning in just the most recent news. Claude Mythos was announced as a preview that it’s effectively a model that’s, again, another step function in power ahead, far more powerful than any other model in the market, so much so that Anthropic has now restricted that use to only some of the top tech companies, particularly American tech companies in the world.

That’s probably a prudent product safety decision, but I guess the ultimate question is, when could some of those capabilities get leaked or when does even the next company catch up to the point that they have those capabilities? And I think about for governments around the world, it’s are you using capabilities to try and monitor the latest threats that they could emerge from that environment? Are you also trying to build state capacity inside of governments to help better understand and prepare for those possible issues? I think infrastructure is very, very critical. Do we actually know and have we planned and prepared for that infrastructure to be resilient?

John Stackhouse 00:30:02

I’m both very concerned by this conversation. You’ve rightly highlighted a number of risks, but also encouraged. Wondering what you both think we as Canadians need to come to grips with in the near term and what opportunities we have in the near term to do something given the speed and scale at which things are moving.

Yoshua Bengio 00:30:23

So I will start by reminding people that the world is moving much, much faster than our brain is even able to really digest. You have to project yourself into future in just one year from now or three years from now, where there’s AIs of even greater capabilities, which really is opening a Pandora’s box in many, many ways, in many areas of society and our institutions and our security. And we have a hard time really grasping the magnitude of the change that is coming.

And we’ve only touched a few points here, but I think Canadians in general should know that we are opening a whole new area of unknown unknowns. Many people are worried about their job. I think rightfully so. We don’t know what the trajectory of advances in the future will be, but if the trend continues, we know it’s going to be radical and we are not preparing for that.

So going back to your question, we should prepare in case things continue as they have been in the last few years. And that means AI is going to be the central economic asset, the central sovereign asset, the central risk to manage, and that we’re going to have to do the right investments, write the right laws to protect the public, and to make sure we’re not going to be overwhelmed by the use of AI by others against us. So these are sounding a bit fantastic, but it’s a real scientific possibility that is documented and that we need to take seriously.

Jaxson Khan 00:32:02

A lot of this is about having adaptability because things may change quickly, as Yoshua has said, and that might be shifting job sectors and categories, might be very fast changing trade relationships. And if our society… People talk a lot about resilience, but I actually think about adaptiveness and responsiveness. If we are able to change the quickest, I think that’ll help Canadians get through this time. I think the fact that we’re one of the only countries that doesn’t have a national education and training framework on AI is a big gap right now.

I’m also thinking a lot, from what I’m hearing, folks going through sector transitions, job transitions, I feel like this is the perennial issue, but it’s are we actually able to match people to opportunities and get those pipelines moving? It seems like this is something we’ve been stuck in, but perhaps AI is actually able to help us solve this problem. So again, we’re not just subjected to these changes that are prompted by AI, but we are able to utilize AI to help adapt and make our way through them as a society. I think that’ll be essential. And if the AI strategy enables that for far more Canadians, I think it’ll be a good and useful document, good plan forward.

John Stackhouse 00:33:03

Great point. So one that’s really standing out to me is that this is on all of us. We can’t sit around waiting for governments to solve this or protect us. We’re all part of AI. We contribute. We are all building AI, even if we’re not scientists by using it. So to be hyper-aware or at least knowledgeable is critical. And you’ve both certainly helped all of us better understand what’s going on in AI and help us understand the opportunity here for Canada. Thank you both for being on Disruptors.

Jaxson Khan 00:33:33

Thank you, John.

Yoshua Bengio 00:33:34

Pleasure. Thanks for having me.

John Stackhouse 00:33:37

You’ve been listening to Disruptors, an RBC podcast. If you want to learn more about AI, go to the show notes. We’ll include links to Jaxson’s paper, Sovereign by Design, as well as an RBC Thought Leadership Report that we published last year on Canadian AI usage. It’s called Bridging the Imagination Gap. Visit rbc.com/thoughtleadership.

There, you’ll find a wide range of critical insights on how we can all make more informed decisions in a rapidly changing world.

You can find other episodes of Disruptors pretty much wherever you get your podcast. Please rate and review our episodes. It helps other people find conversations like the one you’ve just heard.

I’m John Stackhouse. Thanks for listening.

Trust at Scale: Lessons from Wikipedia

SPEAKERS

Jimmy Wales, John Stackhouse

John Stackhouse 00:00:03

Hi, it’s John here. Today’s episode is about a single word, trust. And if you’re like me, you probably think trust is in decline pretty much everywhere. And every survey out there, every study would say trust is in secular decline.

And yet, if you took a bus this morning, you put your trust in a whole bunch of people. If you bought a sandwich at lunch, you put your trust in a whole bunch of strangers. For all of our concerns about trust, we have trust all around us and in many ways it’s also growing.

Our guest today is someone who has just written a book about the seven rules of trust, and he’s also built one of the world’s most famous enterprises, which is stitched together entirely by trust.

I’ll be joined in a moment by Jimmy Wales, Sir Jimmy when he’s in the UK, Jimbo when he’s at home in Alabama, and around the world, known as the co-founder of Wikipedia.

Whether your questions are about science, business, wars, movie stars, wherever the human imagination will take you, Wikipedia continues to grow as the world’s encyclopedia, not just because it’s full of facts, but because it’s stitched together by trust.

In his book, The Seven Rules of Trust, Jimmy Wales and his Canadian co-author, Dan Gardner, outlined not just the core principles of Wikipedia, but the broader principles of trust that can make society and communities stronger, even in this disruptive age of generative AI.

Jimmy, welcome to Disruptors.

Jimmy Wales 00:01:44

Thanks for having me on. It’s good to be here.

John Stackhouse 00:01:46

Let me start with the book and curious what inspired you to write it 25 years after launching Wikipedia.

Jimmy Wales 00:01:53

Yeah. Well, I’ve been watching the Edelman Trust Barometer Survey, and we’ve seen this really long-term slide in trust in society. So trust in politics, trust in institutions, to a lesser degree, trust in business, trust in each other.

And I realized that Wikipedia is built on a foundation of trust. So I thought, “Okay, well, look, Wikipedia’s gone from being kind of a joke to one of the few things people trust. What are some of the lessons I’ve learned and what do I have to say about that?”

John Stackhouse 00:02:25

And lots of lessons that we’ll get into, but maybe we can chat a bit about what is causing that decline. Society’s very different today than 25 years ago when you launched Wikipedia. What in your mind has really changed in our worlds?

Jimmy Wales 00:02:40

If you take a long view, then, yes, a lot is different from 25 years ago, but a lot is the same. Human beings are still the same. Our institutions are flawed, good and bad, and all of that.

What has changed, certainly the rise of social media and how people are living their lives in that sense, but also the rise in, I would say, hyperpartisanship in politics.

When we look at trust, say trust in politics, it’s very tempting for a lot of people to lay the blame at the foot of Donald Trump, for example, who’s clearly not always a trustworthy person. But the decline in trust is much older than that, and it’s a much more broad long-term trend.

And so, that’s not the only place to look. I mean, I would say in part, he’s a symptom of the decline of trust as much as a cause.

John Stackhouse 00:03:31

Many people would attribute that to the decline of institutionalism, whether it’s churches, communities, the fragmentation of society. Do you buy that general theory of society that we’ve become more atomized?

Jimmy Wales 00:03:44

To some extent, the way we live our lives in many ways is not that far different. We still have groups of friends and we still have various community things we do and so on and so forth.

 But I do think there’s a piece to that. Certainly, when we see relatively rapid changes in technology, the way we get information… I’ll just give one example.

In the last 25 years, we’ve seen a real acceleration in the decline in local journalism, local newspapers. And that makes people a little disconnected from civic participation. I wish I had a solution to the problem of local newspapers, but I don’t. But I think some of those kinds of things are a factor in all of this.

John Stackhouse 00:04:48

One of the aspects of your book that I found interesting was the notion of, I want to call it community spirit, maybe you call it civics, but doing things together. And this takes me back to the origins of Wikipedia because people may describe it as crowdsourcing, but it really is about community.

Take us back 25 years when you were building Wikipedia. What inspired you as the internet was taking off to do this crazy thing of getting humans to work together across geographies on something as age-old as editing and fact checking?

Jimmy Wales 00:05:06

Yeah. I’m glad you didn’t fully go with crowdsourcing because that’s a term I don’t particularly care for. Crowdsourcing is, “Oh, I’ve got some work to do. I’m going to try and trick the general public into doing it.” And that’s not a very respectful description. It’s not a very accurate description of what people are like and what Wikipedia is like.

And that’s really about community building, about people getting together because they enjoy doing something together. They feel productive in some way with Wikipedia, in particular. And some of the inspiration for it.

So I had a friend who was a professor at Brown University, so elite Ivy League University, philosophy professor, and we met each other online. And we had an email dialogue for several years discussing ideas and philosophy, and I was learning a lot from him. And it was fantastic that somebody was willing to share that much time with me.

And that kind of spirit to say, actually, people enjoy intellectual stuff. They enjoy working together with other people. That was part of the inspiration is to say, “I think people would enjoy doing this.”

John Stackhouse 00:06:13

One of the things about your own background that people may not appreciate is that you were, I don’t know if this is fair, but a bit of a quant.

Jimmy Wales 00:06:19

Mm. Mm-hmm.

John Stackhouse 00:06:20

You did your PhD studies in finance, you worked as an options trader, you’re a numbers guy. How did that intersect with that intellectual curiosity that was also a foundation of Wikipedia?

Jimmy Wales 00:06:35

I’m a big fan of an essay by Friedrich Hayek. It was in the American Economic Review in 1945, and it’s titled, On the Use of Knowledge in Society. And it’s about how a price system functions to communicate information.

So, at that time, there was a raging debate going on between the idea of a centrally planned economy versus a price-based market economy. And what he identified that I think is universally understood now is that the price system plays a very important role in efficiently communicating information about demand and what people want.

And his point was, “A price system’s incredibly efficient. I don’t need to know why the shelves are emptying out of this product that I make. I just need to know, “Hey, I can make more. I can sell more. And then the price system is sending me the signal.”

So, Wikipedia is not a price system, it’s not a marketplace. But that idea of decentralizing decision making was something that really impacted my thinking, which is to say in a traditional encyclopedia, all the information has to be communicated up a hierarchy and to the editor-in-chief and as sort of a central group of people decide.

Whereas at Wikipedia, the main decision making goes on at the end points, at the level of the individual article where people are discussing and debating, bringing in new sources and so on and so forth. And so that kind of decentralized approach did have a big impact on my early thinking.

John Stackhouse 00:08:02

So, a big bet in trust, I would assume by you in your community. But you didn’t seem to invest a lot in selecting that community, almost self-selected. Is that a fair reflection from what I’ve read in your book?

Jimmy Wales 00:08:16

I mean, that’s an interesting question, actually. So before Wikipedia, I had a project called Newpedia, which was a very traditional top-down, we’re going to write an encyclopedia, let’s recruit the best academics. And a lot of those people made up the backbone of the early community.

And certainly throughout the history of Wikipedia, there’s always been this idea of, we need to find people who are kind and thoughtful, who respect the idea of neutrality, who respect the need for quality sourcing and all of that.

And so, although, yes, it’s very open and anybody is welcome to come and join, we’re still, we’re looking for a certain type of person.

John Stackhouse 00:08:54

And the community helped you select that?

Jimmy Wales 00:08;56

Oh, yeah, for sure. I mean, even today, it’s all part of what we do. I mean, we do things like editathons, sort of public outreach events to get people to come and join Wikipedia and so forth. We’re always looking for people who think it would be a cool hobby.

John Stackhouse 00:09:09

So, this takes me back to those early years. At the time I was in journalism, I was Editor of The Globe and Mail during some of those years, and we experimented with lots of things, but one of them was community comments.

And in the early days, holy cow, it was almost an, I don’t want to say an unmitigated disaster, but it was pretty loud, noisy, and at times irresponsible. And it was a window on the downside of community, especially un-moderated community.

How did your thinking evolve in those early years as social media was exploding, as we were getting into those early days of the internet as something that everyone could participate in?

Jimmy Wales 00:09:54

I’m old. I’m old enough that I remember Usenet, which was before the Worldwide Web even. It was a giant un-moderated and in many ways un-moderatable because it was a very distributed design. It was full of flamers, full of spam, full of very angry people.

And so, sometimes people have this kind of rosy view,  Oh, it must have been really easy back then because everybody was sweet and nice and everybody was happy about the internet.” And I’m like, “Well, no, not really.”

Because the thing about humans is we can be mean to each other even without an algorithm. And so, the way I think about this and the way I talk about this is like, what do you need to do to foster, facilitate a good community, a quality discussion?

And so, clearly, as many, many newspapers experienced back in the early days, just opening up and let anybody comment on anything, it’s going to be dominated by the angriest people, by the trolls and by… It’s sort of a bit of a fiasco. So then you have to start thinking about, “Okay, but how do we manage this? How do we get better at this?”

At Wikipedia, what’s interesting is we don’t use algorithms, we don’t use scoring mechanisms. It’s an accountability model, not a gatekeeping model. So everything you edit, everybody can see what you’ve done. And so they can see your history.

And so, you will have a good reputation or a not a good reputation and people would be aware of that. You don’t get a reward from being from low quality behavior. As you do, by the way, in almost all social media, because the reward is you act like a jerk and you get engagement.

Wikipedia, it’s just like your comment gets erased and that’s that. One of the earliest rules of Wikipedia was no personal attacks. You and I, maybe we’re editing something together and we’ve got a real disagreement. Well, the minute one of us steps across the line and starts attacking the other person, that’s not helpful.

That doesn’t mean everybody’s perfect in Wikipedia. Obviously, people get mad and they attack each other and so on. But there’s a culture that says, “You know what? If you’ve been a jerk to someone, you should probably apologize.”

Maybe you should back away from that subject area if you’re too emotional to be able to calmly interact with people, maybe too much trying to win a battle rather than help make the project better.

And so, it’s not magic and it’s not automatic. It really does require ongoing discussion, dialogue, coaching, people to say like, “Hold on a minute, here’s what we’re trying to do.”

And one of the seven rules of trust that I think is really important is have a good purpose. And with Wikipedia, we all know what we’re here to do.

We have a goal. The goal is a high quality, neutral encyclopedia that cites quality sources and so forth, and that puts a framework around everything that we do. And so we have a way of deciding. It’s like, “Oh, is this debate constructive or is this just people sniping at each other?”

John Stackhouse 00:12:47

Let’s fast-forward into this new age of AI. Probably like a lot of people, I’ve been wondering, how does Wikipedia survive in an age of generative AI? Most models, LLMs, draw on Wikipedia, it seems a lot.

Jimmy Wales 00:13:02

Yeah, they do.

John Stackhouse 00:13:03

But, over time, does that relationship continue where Wikipedia feeds the LLMs? Or do the LLMs figure it out and start to bypass you and those moderators who are essential to all that you’ve built?

Jimmy Wales 00:13;17

Yeah, I don’t see any movement in that direction. I mean, clearly, Wikipedia is a key part of the training data and that human curation of knowledge is very, very important. I mean, I always joke you wouldn’t want to use an LLM that was trained only on Twitter. It would be very angry and stupid.

And obviously, Wikipedia is different from a lot of publishers who are quite disturbed about all this and the training that’s going on on their content. But Wikipedia is open source, freely licensed. And so, on that level, it’s fine. That’s what it’s here for is the world is better off if LLMs have read Wikipedia.

But in terms of competing with us, at least for now, and we’ll see how this goes, the hallucination problem is still severe for large language models. I mean, they literally just make stuff up. And dangerously, they make stuff up that sounds plausible, that’s the way the technology works.

And that problem is much greater the more obscure the topic that you get to. So, at least for now, large language models aren’t a direct substitute in any way for Wikipedia. They’re clearly inferior.

What they are better at, and this is having some impact on us, is that quick answer to a question, particularly if it’s of low risk, low danger. So, if you ask Google today, “How old is Tom Cruise?” We do see a decline in traffic for that type of query.

But if you have that question and that’s literally all you wanted, okay, fine, you’re done. You don’t come to Wikipedia, that’s okay. We’re not ad driven, so our revenue isn’t based on how many clicks we get.

But if you’re like, “Oh, wow, he’s younger than I thought. I thought he must have been 80 by now and he isn’t. What was he in? I thought he was in a movie. What was that?”

And then you go, you dig in, then you’re back to Wikipedia. And so that’s great.

John Stackhouse 00:15:08

Does it change the business model for you?

Jimmy Wales 00:15:11

No, no. Our business model, so to speak, we’re a charity and we’ve had very, very good donations. I mean, our donors are very loyal. And then there was sort of the amusing theme because Elon Musk has been on a campaign against us and he once tweeted, “Defund Wikipedia.” We brought in a few million that day, so bring it on, Elon.

But no, it hasn’t impacted us. And we’re very lucky. I mean, actually one of the things that I do think is quite important, and this was a decision that we made consciously. We aren’t funded by governments and we aren’t funded by a handful of billionaires, and that’s a really good thing.

Imagine if 10 years ago Elon had said, “Oh, Jimmy, stop with the banners and asking people for money. I’ll just fund it. I’ll just write a check every year for the costs.”

Well, then we’d be absolutely vulnerable to whatever whims he might have. And we’re much better off having the intellectual independence of being funded by the general public and we answer to the general public, and that’s really, really important.

John Stackhouse 00:16:15

All of this in a way speaks to neutrality. Elon has labeled you Wokepedia and says, “You’re not neutral. You’re biased.” And there’s some debate as to what neutrality means in this day and age. In some ways, none of us are neutral.

How’s your own thinking about neutrality evolving in this arguably more contentious age?

Jimmy Wales 00:16:36

I’m still very, very keen. So, certainly, the way I approach these questions is, if you say we’ve become Wokepedia, I’m like, “Well, that’s just not true. I know the Wikipedians. I know Wikipedia. It’s not true.”

If you say, “Yeah, but this particular area, you’ve got a bias.” My answer to that is always, “Okay, let’s see what we can do about that. Tell me what you think is wrong and how do we fix it?”

And there are areas where I don’t think we’ve got it right right now. I think we’ll get there, but that’s just part of the discourse.

For me, that is the heart of what Wikipedia should be about is having that thoughtful dialogue. How do we get to a place where everybody can point to it with pride and say, “Yeah, that is a good presentation of the issue.”

And so, for me, neutrality in these divisive times is the same as it ever was. It’s not that hard. It’s sometimes hard to calm people down enough to get there and things like that, of course.

But when people say,  Oh, but how can you be neutral anyway?” I’m like, “Well, okay, here’s one technique. One of the most important techniques that we have is step back from the issue and don’t take a side in the debate, just describe the debate and describe it in a way that’s fair to all the sides.”

And the reason that I prefer that is because I believe that is what an encyclopedia should give you. You shouldn’t go to an encyclopedia and get a one-sided presentation of something. You should get an understanding of what the debate is about.

When we think about the question of trust, I think people will continue to trust us and increase their trust in us as long as we’re willing to grapple with it. We’re willing to say, “Okay, hold on. You’re saying we’re super biased. Let’s go through this.”

What I find when I look into this is, that what Wikipedia tends to do is knock off some of the rough edges in the media. When the media is being biased, we kind of tone it down and stay at more neutrally.

John Stackhouse 00:18:29

One of the important aspects, even essential aspects of neutrality is skepticism, including self-skepticism. That takes me to your Seven Rules of Trust, and we don’t have time to go through each of them, but I want to talk about the social context of these pillars of trust.

I was fascinated in the book with your reflections on Quakerism. The belief in community, Quakers work and worship in circles and meet in circles.

It had me wonder about how our circles have been broken and whether we can rebuild them online or if we are becoming too self-centered, losing the circle and having things revolve around us rather than us being part of a broader group that revolves around something bigger.

Jimmy Wales 00:19:13

So, a lot of our sense that society’s breaking down in some horrific way does come from a very politicized political class and from highly toxic social media, not from our day-to-day life. It’s easy to fall into a little bit of despair if we think about broad, huge, big picture trends, because what can anybody do about that? I’m just one person.

But I think we can start where we are. And I think that’s part of the concept of the Seven Rules of Trust is to say, “In my personal life or in my family, in my company, in my organization, can I put trust at the center of what we’re thinking about?”

So if you’re a small business, you really should be thinking a lot about trust. What is the trust that your customers have in you? How do you build that trust? How do you extend that?

Because it’s very profitable to be trusted. It makes doing business of all kinds much easier and cheaper. And part of the story of the Quakers in the book is the Quakers, as a part of their ideology, they would be honest about their negotiating position to a fault.

And because of that, people were like, “Oh, well, you can do business with the Quakers. They’re not going to cheat you and great. Fantastic.” So they became very successful in business, and that’s really an amazing thing.

And I think that’s the kinds of things that we can put on the agenda in lots of places. And I think we should see more of that. As consumers, we should say, “Actually, I’m going to go with the product where I feel like the company has a reputation of standing behind it.”

John Stackhouse 00:20;45

And that’s the good side of the sharing economy that consumers, users get to share information. It’s not just about sharing a product. Uber’s a good example of this.

Great leap of faith. I’m getting into a stranger’s car, but I also trust the community that if others rate that driver 4. 9, odds are pretty good because I’m part of that community.

Jimmy Wales 00:21:07

Yeah. With Uber, the thing I find sort of amusing is, I remember there was a big kind of moral panic and scare, when? 30 years ago, I don’t remember exactly, about carjackings.

And at that time, if you pulled up at the curb somewhere and somebody opened the rear door of your car, you would be absolutely terrified that you were getting carjacked. Now, you wouldn’t do that because you would go, look, “Hey, I’m not an Uber.”

It’s sort of more trusting the idea, oh yeah, a random person tries to get in my car. I’m going to laugh about it because they’re probably not trying to kill me. They think I’m an Uber.

John Stackhouse 00:21:41

But one of the tensions, and this is perhaps a forever tension in online society and online economies is the need for regulation of having a central force that governs what we do. So when there is bad behavior, even if it’s abnormal, that it is both corrected and there’s a signal to the market, to the community of users that bad behavior is caught and addressed.

What should we learn from the Wikipedia model in terms of governance? Because there isn’t that centralizing force that you mentioned earlier in the conversation.

Is that just the special sauce of Wikipedia or can that be translated to other, especially more commercial markets?

Jimmy Wales 00:22:23

I think it can. I mean, we’ve talked about businesses that could do a better job of thinking about trust and building trust. Top down, centralized, opaque moderation mechanisms are not working very well. And so my view is, start to explore ways you can devolve a lot of that into the community.

I’ll give one example that I do think is a bright spot. I sort of knock on Twitter quite a lot, X. I can never change what it’s called in my mind, but their community knows feature I think is broadly a good thing.

It empowers people to say, “Hold on, that’s wrong. That’s misinformation.” And I think that kind of stuff is very useful because it’s not top down, it’s not from the company. It empowers the community to have a say over something.

But that idea of let’s find ways to devolve decision making to the end points, that’s probably a very helpful thing to do.

John Stackhouse 00:23:17

Jimmy, as we move towards close, one of the things I’m taking from this conversation is actually your optimism about humanity. Of course, your Seven Rules of Trust are positive. Things like make it personal. We can all do something. We don’t need to leave this up to an algorithm.

But I love the point, I think it’s rule number two, about being positive about people. Give us a sense of what gives you positivity when you wake up in 2026 about people.

Jimmy Wales 00:23:45

If you step away from the online world and spend time with families, spend time with friends, people are delightful. And in the research for the book, I found a lot of really bright spots.

Things like Braver Angels is a group that they get together people across the aisle, political spectrum to sort of have discussions and debates. But what they show is actually people have more in common than they have in difference, even if they’re very different politically. So there’s a lot to be happy about.

And even I’m going to say a lot of people are very dismissive and have a lot of concern about young people being addicted to their phones and addicted to TikTok and, “Oh, kids these days and their short form video.”

And I’m like, yeah, they do love a little short form video. That’s true. They like the YouTube shorts and they like the TikTok and all of that. But guess what? This is also the same generation, I’m talking about teenagers who will binge-watch eight straight hours of a really complicated and sophisticated TV show.

Another element that I’ve really been pleased to find out, I had no idea is like the listenership to podcasts skews heavily young. And you think, wow, podcasts, like podcasts are long form content.

This is the same generation we’re afraid all they’re doing is flicking posts on Instagram and yet they’re doing that, but you know what they’re also doing? They’re also listening to really long conversations and that’s kind of fantastic.

John Stackhouse 00:25:10

And are they going to Wikipedia?

Jimmy Wales 00:25:11

Oh yeah, yeah, yeah. Massive. Yeah. One of my favorite things to do, I love to go out and speak at schools. And I always think when I was 15, if they had said, “Yeah, okay everybody, we’re having an assembly and the Editor-in-Chief of Britannica is going to come and give a lecture today,” we would have been like, “Ugh, kill me now. Are you kidding me?”

And when I go to speak, the kids are out of their minds. They’re so excited. They love Wikipedia.

John Stackhouse 00:25:36

Why do you think kids today may be more interested in encyclopedia as the online version than your generation might have been in the physical world?

Jimmy Wales 00:25:43

Oh, I just think it’s so much a part of our lives, Wikipedia, compared to encyclopedias back then. Back then, encyclopedia was a very solemn set of books on the shelf and you would go to it from time to time.

Whereas now, imagine that you hear, as you might in the news these days, I saw that Iran fired a missile at Azerbaijan and you think, “Azerbaijan, I don’t really know about that.”

40 years ago, you might have thought, “Oh, I should go to the library and look that up.” Well, you thought that, but you never did it. You just wondered and that was the end of that. Whereas now you probably go, “Oh, hold on. Azerbaijan.” You Google it and then you’re like, “Oh, Iranian Azerbaijani relations. Okay, now I’m going to see, what are they mad about?”

And that’s the kind of casual learning that people really enjoy and I think is really powerful.

John Stackhouse 00:26:26

It comes back to maybe one of the unspoken rules of trust, which is be curious.

Jimmy Wales 00:26:35

Jimmy Wales: Yeah.

John Stackhouse 00:26:36

And humans are, we’re a curious species.

Jimmy Wales 00:26:38

They definitely are.

John Stackhouse 00:26:39

We want to learn, we want to explore. If I can ask one last question, Jimmy, this has been such a rich conversation. It’s about what some might call a trust dividend.

If we’re doing all these things, following the rules, creating more trust, and if there is a dividend from that, where would you invest it? Is it in schools like you’re doing? Is it in institutions? Is it in digital infrastructure and product design?

Jimmy Wales 00:27:04

I definitely think that investing in education is incredibly important, investing time with your children and their education, things like that. That is massively, massively important. And I think that’s something we all need to focus on.

John Stackhouse 00:27:19

Jimmy Wales, what a great conversation. Thank you. Thank you for creating Wikipedia.

Jimmy Wales 00:27:24

Very good.

John Stackhouse 00:27:24

John Stackhouse: I can’t think of a person who has not benefited from it and you can’t say many things about that in the world.

Jimmy Wales 00:27:30

Jimmy Wales: Very good.

John Stackhouse 00:27:30

Thank you for being on Disruptors.

Jimmy Wales 00:27:32

Thanks for having me.

John Stackhouse 00:27:34

There’s so much to take away from that conversation. But one of the points that stands out in my mind is how trust is not a moral decoration. Every business, every community, every circle of friends depends on trust, and that’s something we can all invest in every day.

Check out our show notes for a new briefing on trust at Internet Scale. And if you’re looking for more ideas and insights, visit rbc.com/ thoughtleadership. There, you’ll find critical insights to help us all make more informed decisions in a rapidly changing world.

You’ve been listening to Disruptors, an RBC podcast. If you like this episode, please rate, review, and follow us on Apple or Spotify. That will help others find conversations like the one you’ve heard today.

I’m John Stackhouse. Thanks for listening.