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.

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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.

Tech Wins Gold: How Canada Can Rebuild Its Olympic Pipeline

SPEAKERS

Jennifer Heil, David Shoemaker, John Stackhouse

John Stackhouse 00:00:05

Hi, it’s John here.

When I say Milano Cortina, what jumps to mind? The Olympics, of course, but what are the images? Is it Courtney Sarault on the short track ice winning four medals or is it Mikael Kingsbury winning a silver in traditional moguls and then that unbelievable gold run in the brand new dual moguls event? The perfect ending to the greatest freestyle skiing career ever. Or is it those two amazing hockey gold medal games and unfortunately those two overtime losses to the USA? Or is it something else?

Whatever stays with you and still inspires you from the Olympics, it probably revolves around an athlete and those unforgettable Olympic moments of human achievement. Our athletes did incredibly well, even though the medal count was not what they wanted it to be. But what we probably all overlooked in this Olympic experience is the role of technology and the financial support that is essential to Olympic achievement at the level that we all know Canada is capable of. High performance technology is accelerating as fast in Olympic sports as it is anywhere else. It’s through the skis and skates that propel our athletes and yes, those remarkable BMW made bobsleds that help the Germans win gold, silver, and bronze.

Whatever the sport, technology is playing an increasingly valuable role. And as Canada thinks about the Olympics of the future, we need to think more ambitiously about the investments we can make in technology and in supporting our athletes.

This episode of Disruptors is so timely, not only because the Milano Cortina games are just a couple of weeks behind us, but because the always awesome Paralympics are well underway now and technology is just as important there as anywhere else.

Today we have two very special guests, Jennifer Heil, the Olympic champion and moguls and one of Canada’s most decorated freestyle skiers with gold in Turin and silver in Vancouver. She’s also Team Canada’s Chef de Mission for Milano Cortina 2026, and also the founder and CEO of her own tech company, Revvel Health, which we’ll hear a lot more about in this episode. And we’re joined by David Shoemaker, the CEO and Secretary General of the Canadian Olympic Committee. Before coming home to lead Canada’s Olympic movement, David spent seven years as CEO of NBA China and previously served as President of the WTA Tennis Tour. So he’s seen how the world’s biggest sports organizations build performance systems and scale them.

The world’s top Olympic programs are now running on tools that track every training rep, every night’s sleep, every hour of recovery, and feed that data into a unified athlete platform so coaches can intervene before an injury happens, but also use that data to help their athletes perform at their very best. And here’s what’s key to this conversation and frankly key to Canada for the years ahead. Other countries are funding this as infrastructure. Canada is treating it as a cost and we’re not treating it very seriously. That’s the context for today’s conversation. If we want to own the podium, we need to invest a lot more in our athletes, their support teams, and the technologies that other countries are racing ahead with. This is a moment of nation building. And as we’re seeing in Milano Cortina, there are a few better nation builders than our Olympians.

So let’s hear from a couple of our champions on what we can all do to continue to build Canada as an Olympic power. David and Jen, welcome to Disruptors.

Jennifer Heil 00:03:59

Thanks for having us.

David Shoemaker 00:04:00

Thank you for having us.

John Stackhouse 00:04:02

I’m so excited for this conversation, as I’m sure our listeners are too. And I want to start by taking us back to Milano. David, I’ll start with you, what was the standout moment for you?

David Shoemaker 00:04:13

Wow, that is definitely asking me to pick my favorite child. The saying in the Olympic sport is, “The only thing tougher than winning a gold medal is defending one.” And our women’s speed skaters in the team pursuit defended a gold medal from Beijing. So this is Isabelle Weidemann, Valerie Maltais and Ivanie Blondin. And they defended that gold medal and then they got up on the podium, and when “O Canada” was played, Isabelle embraced her teammates. And I usually try to belt down “O Canada” and I choked up after the first couple of lines. It was a really special moment for me and for everyone watching, and I’ll remember that one forever.

John Stackhouse 00:04:56

Love it. Jen?

Jennifer Heil 00:04:58

Yeah, I have two big takeaways. One is personal in that I left there inspired like the nine-year-old kid who first picked up a magazine seeing Olympic athletes. And I’ve been involved in the Olympic movement for so long. I didn’t expect it. I came back to my everyday life and I was like, “I want to be better.” And then in terms of a specific moment, I would have to say it was Megan Oldham. And that comes back to being a female athlete myself in an action sport. And these women at this Olympics across skiing, snowboard, they literally took it to new heights. And the level at which they’re competing now blew me away, left me so excited. And Megan is so tough. So she crashed really badly in her second run in slopestyle. She had so much bruising she could hardly stand on her leg. She went back up and won a bronze medal and then followed it up two days later with a gold. So for me, that’s the standout moment.

John Stackhouse 00:05:59

What wonderful Olympic memories, and that says so much about the Olympics. It is just humanity at its best. What we’re talking about today is how all of us as Canadians can do better in terms of supporting and investing in our athletes. And one of the great needs, as I said in the introduction, is technology. You’ve both been to lots of Olympics, seen lots of sports. Anything jump out at you at these games in terms of how fast technology is advancing?

David Shoemaker 00:06:29

From a viewing standpoint, the use of drones, and I guess I should be careful because it feels like two years ago when I used the word drone in public, we were talking about it in a very different context. But what it’s done if you watch some of the downhill ski racing or watched Megan Oldham in slopestyle or Kingsbury go down a mogul course and give you that bird’s eye view of what it’s like, how steep it is, how big those moguls are, how high they fly in the air and do their flips and their spins. It is really an awesome way of bringing the winter games into 30 million Canadian homes that watch these Olympic Games more than Paris.

Jennifer Heil 00:07:11

Yeah, I was totally blown away. I felt like I was on the Alpine course with the athletes, and it made me excited in the sense of really bringing people into the performance and the intensity of it. I would say what’s really interesting is ML and AI as a whole, it’s actually very good on the technical side. So it can do a very good job obviously of pattern recognition and identifying biomechanics and movements in sport. The opportunity there is immense on the judging side as someone that comes from a judged sport. I think that at a minimum, it should be incorporated into the next Winter Olympics where it’s making sure that there’s no anomalies within the judging score. I think that’s a great way to standardize what we’re seeing more and remove some of the error that just is always going to happen. So I think there’s a huge opportunity. We’re still very early in adopting that from the technical side of sport, but we know nations are working on it.

John Stackhouse 00:08:10

One of my eye-popping moments was with the bobsled and the Germans who, of course, dominate that have a program with BMW. Of course they do. They’re German making BMW quality bobsleds, and that’s not the only reason they won gold, silver, and bronze, but I suspect that’s one of the key differentiators. So just an indication of what other nations are doing.

David Shoemaker 00:08:33

Yeah. The Olympic movement will have to come to grips with whether technological advancement and innovation is something to embrace and let nations that can afford that gain from that, or by contrast, in Monobob where there are all the bobsleighs are made by one company, and while you can paint them up with your nation’s colors, it’s basically an equalizer. What do we want to see be the baseline of competition, technological advantage, or trying to have everybody start from the same starting point? And I don’t think we’ve quite figured that out as an Olympic movement yet.

John Stackhouse 00:09:11

What’s your view? It’s hard to imagine hockey players being required to wear the same skates or use the same sticks or Alpine racers using the same skis, but maybe I’m not thinking widely enough.

David Shoemaker 00:09:21

No, but maybe at least put some limits to it the way, let’s say the sport of golf has said, we need to say that the coefficient of rebound on a driver needs to be limited to a certain amount or a ball has to conform to certain specifications and then have at it.

Jennifer Heil 00:09:37

I’d like to see it broken into two things. I think it’s going to be very hard to stop AI and the use of technology to optimize performance, but from an equipment place, I think we should absolutely standardize it more and it shouldn’t be the differentiator between nations at the degree it is in some sports.

John Stackhouse 00:09:57

So if standardized or not, we’re going to need to invest. And I say want to invest a lot more in a whole range of things, but those technologies as well, they also have wonderful spinoff benefits. David, I wonder if I can ask you to speak to the request that you and the COC have made for $ 144 million coming out of the games. It seems like such a small number when we’re talking about billions and tens of billions for so many other things in society. And every dollar has a value. I’m not trying to make false comparisons, but as you said, this was Games that Canadians, regardless of the results, embraced and loved. And in this moment of national pride, it really is something I imagine most Canadians do want to lean into more, whether they’re athletes or not. What do we need to understand about where this money should go and would go?

David Shoemaker 00:10:47

Yeah, this matters so much to me. I’ve been in this role since January of 2019, and I can think of no issue that I’ve prioritized more than advocating to the federal government on behalf of our national sports organizations and in turn, on behalf of this nation’s great athletes. For clarity, and I feel compelled to mention this every time this comes up, we’re not asking for a penny for the Canadian Olympic Committee. We are almost entirely privately funded. We have 39 marketing partners who support us generously. We’ve been able to increase our investment in Canadian sport and Canadian athletes by 300% in the last 20 years, and we’re going to continue to do more. We announced a 10-year strategy where we’re going to put $500 million into Canadian sport and to Canadian athletes over the next 10 years. But what has trailed us is the federal government’s investment in the 62 national sports organizations. They have not had an increase in their core funding since 2005. These are the organizations that the federal government has entrusted with, and you can imagine what things cost back in 2005 and what they now cost in 2025.

What we’ve seen happen over the course of the last five, 10 years is as they’ve been experiencing this financial distress, the burden of these financial problems has been shifting increasingly to athletes. And so athletes are increasingly being asked to pay what are called team fees, 10, 20, $30,000. So I’ve equated it to, “Congratulations, you’ve made the national team in your sport. Here’s the invoice to be a representative of Team Canada, and that doesn’t fit my vision for the sport.” So we are trailing our competitive nations. Germany’s putting about a billion dollars a year into sport, and we need to do better. Where will it go? It’ll go into high performance sport because these athletes are a great source of pride for us, and we need to continue to support them to do what they do to unite communities around the country, but we also have to invest in linking the impact of that triumph to what happens in the communities, to getting more young people broadly across the country, lowering the barriers to access to sport and to organized sport. And that’s where the money would go.

John Stackhouse 00:13:06

Jen, tell us a bit about what this means to athletes and maybe share a bit of your own experience as an outstanding athlete, but what you had to go through from a financial perspective.

Jennifer Heil 00:13:36

So I lived through a pretty big inflection point in the sport system. So that was where Canada was hosting the 2010 Olympics and we created Own the Podium. And so everything shifted in that moment, including the culture of sport. So what did we do? We got a strategy on how we were going to build a strong system. We had the resources to support that, including innovation. We brought a lot of innovation, a lot of top minds in staff and sport into Canada at that time. And then we had this culture of winning and there was this pride and this excitement. I mean, how many books have been written on culture building and company culture? All of that came together in a way where we had our best success winning the most gold medals of anyone that year. And we’ve seen the continued effects of that. And we’re at the tail end of this now, and we are at the moment of total brain drain in our system of the best minds in sport.

When I was asked about this issue at the Olympics, I had a top sports scientist in the world who’s been to nine Olympic Games, works for Canada, be like, “Jen, I want to work in Canada. This is where my family is. This is where I want to be.” He’s like, “I don’t know if I’m going to have a job after March.” I spoke to one of the best sports nutritionists globally who lives and works in Western Canada, and he’s already had to move 80% of his time out of the country and into the US because there isn’t the funding and support. I heard from a bunch of athletes on the ground and support staff, and they said, “Other countries want to come to Canada. It is a source of pride to be able to coach and be a sports scientist in Canada.” And so it’s not that people don’t want to be here and we don’t have a lot to offer, it’s just quite frankly, we can’t afford them right now.

John Stackhouse 00:15:02

What a great point. We talk a lot about talent attraction at this point in history and how many super talented people could and should be moving to Canada. And that includes not only athletes, but all the professionals who support them. Hearing you both speak so passionately and eloquently, I think, boy, we got to move on from elbows up to pony up.

David Shoemaker 00:15:23

We have the absolute best athletes in the world who continue to do more with less. And when we see what they do and the pride they instill in us, this is a very, very modest investment when you compare it to the other nation building activities we are so committed to.

John Stackhouse 00:15:41

David, can you give us a sense of what other countries are doing? And I’m not thinking of the United States because it’s kind of in a category of one in how it approaches these things, but smaller European nations, as an example, who certainly win more medals than us. I think in Norway, obviously, but other countries that we like to compare ourselves with.

David Shoemaker 00:16:01

Our Chief of Sport, Eric Miles, often talks about the fact that in Norway or in the Netherlands, if they call a team meeting among all their national athletes, they can all get there in an hour and a half. We don’t have that advantage. But whether you measure it in absolute dollars or whether you measure it on a per capita basis, we are being out invested at the federal level five, six, 10 times more by our peers. And that makes it awfully difficult for our sport organizations and for our athletes to compete at the level that they do. Our athletes did incredibly well. But when we look at the medal table, it’s not where we aspire to be at the winter games. And we know we can do better. We know we have a thinning talent pool. We know 75% of our medalists were over the age of 30, and that’s something that we’ve really got to address.

John Stackhouse 00:16:55

Can I stop you there? I don’t think most of us appreciate this point about a thinning talent pool. And when we think, or you think certainly about 2035 and beyond, what kind of situation are we looking at?

David Shoemaker 00:17:09

Well, we can illustrate it. Maybe the best one would be our long track speed skating team who actually did marvelously in Milano Cortina, but it was basically the very same medal hopefuls that we put on the track in Beijing. I don’t want to speak for any of them in terms of what their longer term plans are for 2030 and the games of the French Alps, but that puts a lot of pressure on them to then come back four years later and continue to perform. What has happened in order for Canadian sports to continue to perform at the highest level is that they’ve been mortgaging the future for the sake of the present. And that means that when they’ve been able to put less money into the development of the next generation of athletes, athletes who are likely five to eight years out, giving them international experience, giving them World Cup experience, giving them Olympic experience where other nations are able to bring them along. And that’s where we’ll see our lack of investment in the next generation catch up with us when we’d sort of say, “Okay, who’s up next? Who’s on deck?” And we look and the bleachers are empty.

Jennifer Heil 00:18:15

We’re creating a pay-to-play system, and I think that goes counter to Canadian values and what we aspire sport to do in this country. And what the other countries who are succeeding are doing well is that they’re investing deeper into the system where that has virtually disappeared in Canada. So for example, Norway isn’t funding every sport. They don’t have 62 NSOs that they’re funding. They’re choosing sports that align to their culture and their values, and they’re going deep into that system. Canada has to make some decisions and look at that on how we can be more efficient in the way we fund our operations. That for sure has to be part of the conversation. But what I was hearing on the ground in terms of this pay-to-play system and the younger athletes is that families are saying, “We’re here for one Olympic cycle, but we can’t afford to be here for two and three.” Which is where those conversions into medals start to happen. We’re saying, “How do we create the system that works in Canada?” And our athletes will always punch above their weight. And so to your question around technology, there’s so many opportunities that are opening up there. Yes, it’s expensive to invest in it, and yes, we need to have a strategy to make sure it’s part of how we move forward, but AI offers some incredible cost savings. And the company I’m building is a performance tech company where we take the knowledge base and we work with the experts, the very best in class to basically democratize access to that knowledge. So there’s ways that if we plan for this and we look strategically into the future, we can actually reduce costs over time and get more of these expertise to more athletes as an example of how we can be efficient and save costs if we embrace this and have a plan.

John Stackhouse 00:20:00

Jen, tell us a bit more about the company and what your vision is.

Jennifer Heil 00:20:04

So the company is called Revvel, and it’s really based off of my experiences in the sports system where under the conditions that we talked about around 2010, I had the best sports science and medical team around me that anyone in the world would have. So physio, sports psychologists, nutritionists, the best of the best. And it was extraordinary and it allowed me to go on and achieve my goals, but I started to think that was normal. And so when I retired from sport, I was like, “Wait a minute, this is weird. Where is everybody?” And so my goal has always been, how can we create these structures and get this knowledge that’s in the sports system that’s best in class on the human body, human performance? How do we get that into the general population? And so I went down to Stanford with this thesis where I did a one-year MBA and was able to go and explore the technology to do this because it’s never been scalable before. And so we’re building the platform where with the experts, we create their AI knowledge base, which is like a living, breathing thing that they have to upkeep. And then through an app, you’re able to access that knowledge and personalize it to your own life context.

John Stackhouse 00:21:13

You also co-founded something called B2ten, which is designed to fill the gap between the national system and what athletes actually need. Tell us a bit more about B2ten and where it might take us.

Jennifer Heil 00:21:25

Yeah. So I mean, when we look at the sport system holistically, we need a lot of different players at the table. David has talked about the COC and the private investment. That’s a critical piece to our sports system. B2ten was really about bringing private dollars, philanthropic dollars into the system. And our donors have been with us for 20 years, have raised tens of millions of dollars, and it all comes down to nation building for them. They understand the importance of sport. They understand how sport brings us together as a country. And so we’ve been able to bring these top resources and really create these athlete-centric training programs, which is so key in terms of the culture, but also getting these expertise into the country and keeping them here. So that’s been a huge focus of it. We also have an arm of getting physical literacy into daycares and making sure that that connection from elite sport down to grassroots is happening. 2ten continues and needs to do its part in the system and making sure that the best in class are accessible to our athletes is a key part of the focus.

John Stackhouse 00:22:30

How do we get future generations more engaged? How do we support them and how do we use technology to re- up the pipeline?

David Shoemaker 00:22:39

You may have heard of RBC Training Ground, which is basically a talent identification program that has worked marvelously in its 10th year. RBC has been able to go around the country and find athletes and help them determine what sport they’re most likely to have success in. And we have some really amazing stories that have come out of that. For example, Kelsey Mitchell, who won a track cycling gold medal at the Tokyo Olympics was only five years prior to that a soccer player and had power in her legs that was off the charts. And Avalon Wasteneys, who was a rower and was identified by RBC Training Ground and was part of that Women’s Eight team that’s been so successful. I think also with AI, we can, and I’ll use Jen’s turn of phrase, democratize talent identification in the country. Imagine being able to go to youth all around and say, “Okay, here’s the new app on the phone, show us how you jump, how you run, how you throw, et cetera, et cetera and we’ll come back to you and tell you what sport you should go and sign up for at your local club.” We know that there’s efforts to do this in part of the African continent to try to get a little bit more Olympic activity out of some of those countries and Senegal in particular in the lead up to the Youth Olympic Games that’ll be happening later this year there. I’m excited about how sort of technology could help us in a country as large as Canada, tap into the talent that’s surely out there.

John Stackhouse 00:24:12

As we move towards close, I wonder if I can get both of your thoughts on what we need to strive for. I’m fascinated what other countries have done, we all know about Britain’s success with cycling, investing heavily in that. Australia’s invested more in sports science. Ireland funds a national athlete data platform for a country that’s pretty much the size of Greater Toronto. So other countries are making really interesting strategic bets. So as we think about that big vision, also what are some of the big bets we should be thinking about?

David Shoemaker 00:24:45

Well, we’ve announced a Team Canada 2035 10-year strategy that has three core pillars: podium, play, planet. And in terms of podium, we aspire to be top five in the world on a combined basis when we aggregate our summer and winter Olympic performance. In terms of play, we aspire to get a million more young people into organized sport. And that’s about linking the incredible performances on the world stage and the inspiration that creates in young people. So when Summer McIntosh ignites a world of young people to want to get into swimming, they’re not just left to wonder, how do I contact my local swim club? The local swim club is there for them and offering access at levels that are much lower than they are today.

And then planet is about our belief that we cannot achieve either of those first two pillars if our sporting environments aren’t preserved. And this is a winter problem, but it’s also a summer problem with incredible heat and air quality issues, but we do have to preserve our sporting environments with melting polar ice caps and snow issues. And technology plays a really important role there. We see more and more countries tenting snow over the summer months so that it exists for a reliable snow season going forward. And I think we’re just beginning to scratch the surface of what leadership could be in that space so that the winter games are here with us in the way we see them for many, many years to come.

Jennifer Heil 00:26:13

I want to just say the athletes don’t lack ambition. And that was very clear to me in Milano Cortina, being on the ground with some of the lesser funded sports, the heartbreak there was so real of the athletes. One of the athletes in a sliding sport spoke to her coach and she was like, “I want to be better. I’ve been here for eight years. What do I have to do?” And the coach who was a former athlete said, “Well, when I was that far into my career, I had more time on the track. I had that extra training camp or two training camps every year.” And the response was, “Okay, well, how much do I have to pay?” So this isn’t the system we want to build. It’s not sustainable. I want to see that same ambition matched from the leadership of the government. I think it’s important that as Canadians, we don’t mix up humility with ambition. Our athletes are hugely ambitious. We know that Canadians like waving the flag. We saw it in 2010 when there was just this incredible wave of pride in our country and pride to stand on top of the podium. We know that to be true, but the point is is that we do need a strong functioning system to inspire the youth to get Canadians active. All of this matters and all of this can be connected, but we have a lot of work to do.

John Stackhouse 00:27:36

Well, I think it’s on all of us. We all embrace the Team Canada spirit. What do we all need to do in the next, let’s say, two years to pick up the pace towards those longer term goals?

David Shoemaker 00:27:49

I believe the linchpin here is federal funding. I believe we have a Prime Minister in Mark Carney who believes mightily in the power of sport. We’ve seen him in hockey jerseys on the campaign trail. We have confidence that he hears our athletes, but we need action in that space. We have a Minister of Sport in Adam van Koeverden, an Olympic champion, an icon who also understands the power of sport. And so we just need to get this one over the line and then deploy it in a way that makes sense, consistent with the vision in the way that Jen’s spoken so well about.

John Stackhouse 00:28:28

Maybe one last question to all the young Jennifer Heils out there today, what’s your message to them?

Jennifer Heil 00:28:34

To me, sport equals joy. And I can tell you that being an Olympian, standing on top of the Olympic podium, some of my best moments in sport were school sport, where being a part of the school volleyball team was going to the Canada winter games and meeting incredible people from Newfoundland who sent me letters in the mail for an extra decade. To me, it’s about going out and striving to be your best in a positive environment. And I think that’s what we should aspire to build, whether that’s community, provincial, national team level. That’s what we should aspire to offer our youth. But for me, it was always about challenging myself to be my best, and that kept the fire alive. Of course, I wanted to win medals, that those were the outcomes, but that wasn’t where the joy was.

John Stackhouse 00:29:25

Being our best in a positive environment, what wonderful words. That really, really is joy. Thank you both for your leadership, for your inspiration. Let’s keep at it. It’s “Go Canada” time. Thank you for being on Disruptors.

David Shoemaker 00:29:37

It sure is. Thanks so much, John.

Jennifer Heil 00:29:39

Go Canada.

John Stackhouse 00:29:43

When you think of the payoff of 30 million Canadians cheering their athletes from a distance of future generations, investing themselves in sport and all that comes with that, or the technologies that have so many benefits and applications well beyond the playing field, we need to stop putting so much burden on our athletes and start thinking more strategically on how we as a country can invest in the sports infrastructure.

And a special note for budding athletes, you heard David reference RBC Training Ground. It’s a remarkable program and is resuming its search for the next generation of Canadian Olympians. In just a couple of weeks, anyone aged 14 to 25 is invited to register at rbctrainingground.ca and come out to any of the free local qualifying events that are happening right across the country to test your speed, power, strength, and endurance. If you’re looking for more ideas and insights, visit rbc. com/ thoughtleadership. There you’ll find a whole range of critical insights on how we could all make more informed decisions in a rapidly changing 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 more people find conversations like this one.

I’m John Stackhouse. Thanks for listening.

Harvest Now, Decrypt Later: The Quantum Era’s Encryption Challenge

SPEAKERS

Christian Weedbrook, Dr. Stephanie Simmons, John Stackhouse

John Stackhouse 00:00:09

Hi, it’s John here. I don’t want to be a scaremonger, but right now as you’re listening to this, are pretty good that adversaries somewhere maybe trying to collect your data, even your encrypted data. If you’re running a company, a hospital, a public institution, or just sharing data. Basically if you rely on encryption to create digital trust or rely on digital trust for anything, this episode is for you.

Now, these sorts of challenges have been with us for decades, but there’s one word that is really sharpening the challenge in the 2020s and that word is quantum. Today we’re going to talk to two of Canada’s leading quantum pioneers to not only understand what’s at stake in this new global battle that’s taking place in machines all around us, but to get a true sense of how Canada has become a true global leader in both the science of quantum and the art of trust.

We’ll be joined by Dr. Stephanie Simmons. She’s the founder and Chief Quantum Officer at Photonic. It’s a remarkable company that I’ve had the chance to visit in Burnaby B.C. And we’ll also be joined by Christian Weedbrook, the founder and CEO of Xanadu and we’ll visit his quantum lab in downtown Toronto.

You may know both of their names from previous episodes of Disruptors. They joined us in 2023 when most of us probably still filed quantum under the label “someday.” Now, these systems are moving from research labs into production infrastructure and will be critical to Canada’s competitiveness and sovereignty in a high stakes global digital economy.

Here’s a bit of background for those of you who may not have your high school physics textbook quite at hand. Quantum computers use qubits. Those are units that can exist in multiple states simultaneously. And when qubits become entangled, they behave as one coordinated system, solving certain problems exponentially faster than any classical computer could. But as powerful as quantum states can be, they are also incredibly fragile.

The real engineering challenge is correcting errors in real time before all those calculations collapse. Once a system reaches so- called fault tolerance, where they can fix errors faster than they can occur, today’s encryption becomes obsolete. Imagine the threats that can go with that, and guess what?

They’re already active. “Harvest now, decrypt later” means actors, usually bad ones, are collecting encrypted data today to decrypt tomorrow. And if that protection breaks, we just don’t lose privacy, we may lose trust in every institution that holds our information. So today’s episode is about protecting that trust layer of the economy before it’s too late and the breakthroughs that come with it. Let’s get into it. I’m here at the Toronto headquarters of Xanadu, which is really in some ways ground zero of quantum technology, certainly here in Canada. I’m with Christian Weedbrook, the founder and CEO of Xanadu, and behind me is Aurora, a creation of Xanadu and the world’s first networked quantum computer. Tell us what we’re looking at.

Christian Weedbrook 00:03:30

So the first thing to notice is this is a quantum computer. It’s the most advanced quantum computer anywhere in the world in terms of its networking capability. So what we see here is four server racks. They’re roughly about seven feet tall. They wouldn’t look out of place in a normal data center. And this is setting the vision for what quantum computing will become, but the challenge here is how to connect them together. Quantum mechanics makes it typically very difficult to connect server racks together unless you’re using photons or light, which is our approach.

John Stackhouse 00:004:01

Okay, take us deeper into that because certainly to the lay eye, it looks like server racks as you say. So what’s going on here that makes this quantum?

Christian Weedbrook 00:04:11

For any quantum computer, you need to be able to access things like the superposition principle entanglement and interference. So all those properties are occurring here. So we’re using photons or light. Qubits are creating up here. And as they propagate downwards, gates are acting on them. And so it’s very much typical of a normal computer. You have inputs, the bits normally, you have gates and then you have the readout. We have a quantum mechanical version of this where you actually have qubits, gates and then measurements at the bottom.

The key point here is that you actually have light starting at the top, getting created qubits and going all the way down. And that’s happening individually and all these server racks. But the really cool thing is they’re actually talking to each other. You can see down here the yellow cables of fiber optics being connected to their nearest neighbor. And that’s really the revolutionary aspect of this Aurora computer when it relates to scalability.

John Stackhouse 00:005:04

And speaking of scale, how much bigger does this get or is this the size and it’s just the intensity that needs to be focused on?

Christian Weedbrook 00:05:13

This can scale up to arbitrary number of server racks now, so that’s being solved.

John Stackhouse 00:05:17

So how do you improve the performance?

Christian Weedbrook 00:05:19

Essentially, let’s take a laser pointer. Whenever you shine a laser pointer at a wall, you can see the laser on the wall. But if you imagine the wall getting taken kilometers away, the imprinted laser starts diluting. It becomes faint. And that means photons have been lost.

Loss here actually causes the errors in our computation. And as mentioned before, that’s why we use error correction codes, so that will protect us against the loss of information. But the other one is working more and more with foundries. So we actually have photonic integrated chips. And we design them here in Toronto and send them off to different foundries around the world. They made or fabricated these chips and send them back to us. What we need to do is improve the performance of those chips, and that’s how we reduce loss from a physical point of view.

John Stackhouse 00:06:07

Christian isn’t giving us a scoreboard today. He’s actually showing us a path to scale. And here’s the uncomfortable part. Once systems like this truly scale, and they will, the encryption that protects identity and transactions today becomes obsolete. “Harvest now, decrypt later” is the storm on the horizon. Encrypted data is being collected and stored now to be open later, but if that promise of protection breaks, we just don’t lose privacy, we may lose trust in those who hold our information.

Implementing post- quantum cryptography is like replacing your roof before the storm hits. If you wait until water is coming through the ceiling, well, it’s already too late. So what does that actually mean for the trust layer of our economy? Stephanie’s going to break down the risk and what leaders need to do next. Stephanie, welcome back to Disruptors.

Dr. Stephanie Simmons 00:07:00

Thank you so much for having me. I’m excited to be here.

John Stackhouse 00:07:03

John Stackhouse: It’s great to have you as a repeat guest. What do you think about most when you think about this idea of “harvest now, decrypt later,” and what’s at stake?

Dr. Stephanie Simmons 00:07:12

Yeah. What I like about quantum is that we know it’s coming and we have the opportunity to prepare. When ChatGPT happened, it took everybody by surprise. But we know this is coming, so we have the opportunity to just take a deep breath and move. “Harvest now, decrypt later.” Data is a lot cheaper to hold onto today. We know that there’s quite a bit of tracking being done and holding onto communications today so that one could decrypt it in the future.

Now, what’s needed for the cryptographically relevant quantum computer has come down considerably. So just for reference, I’m a founder of a company called Photonic. And one of the things that we brought into the market about a year ago now was efficient QLDPC codes, much more efficient codes. What it does is it’s meant that the requirements to build these big quantum systems that can break into all these codes came in by an order of magnitude or more.

So a lot of these things are moving really quickly. And we know that what it can do is it asks us to think about coming up with a new cryptographic solution for the way that we communicate. Now, that’s just the cryptography side.

John Stackhouse 00:08:15

Well, let’s talk about some of the challenges in commerce and what could break down. Is it going to be identity, authentication, signing? Where do you think the vulnerabilities are?

Dr. Stephanie Simmons 00:08:26

It can do the math that we rely upon for what we’ll call the asymmetric layer of our cryptographic systems. And that’s kind of every exchange. So it’s not just authentication, although for sure it is every step along the way where you could take a look. What we use today is we use a, for the asymmetric part of the encryption, we have this handshake. So two different teams over the internet or whatever network, they have this agreement. We’re like, ” Okay, hey, you are who you say you are. And I’m going to rely that this math problem is really hard to solve, but if you have the solution, it’s really easy to check.” So that’s why it’s called asymmetric.

And what you have is that math is kind of what we’re trusting is unbreakable for all the comms. And so when you’re logging into your account, when you’re logging into anything, when you’re forming any communication, that math is what you’re trusting. And so I think that in the early instances, if an adversarial organization were to use that, it would get access to basically any communication we use online.

Now, okay, what I want to say is that there are new cryptographic standards that people are really excited about and they hope they will withstand all future quantum algorithms. We don’t know all the future quantum algorithms, but there is reason to hope that these ones will be resilient. And so we have the opportunity now to change our software and hope that those new cryptographic standards hold.

So there are solutions here, and people have been working on this, as you can imagine, quite a bit. What I’m glad to hear in this conversation here is the interest in actually taking that step and shift. And it’s not easy. It’s not easy because a lot of teams use third party suppliers that themselves are using vulnerable cryptography. So I think we have that awareness moment. The community knows that this is in five years plus or minus. And we can take the time to go in and just put that additional layer of security to know that we’re going to be quantum safe through the coming years.

John Stackhouse 00:10:38

So that’s the threat. “Harvest now, decrypt later” isn’t science fiction, it’s a trust crisis on a timer. We’ve seen the threat, we’ve seen the defense architecture, but there’s another side to this story. Back to Christian Weedbrook. What can quantum computing actually do for us today and what will enterprises use first?

You’re doing a lot around drug discovery, which is one of the big opportunities with quantum. Tell us more about what you’ve done and where you’re hoping that will go.

Christian Weedbrook 00:11:08

Once you have a large enough quantum computer, as mentioned, once you have hundreds of these server racks performance, our world will look very different. So if you look at pharmaceuticals, it starts off with classical simulation of quantum systems. You go through then synthesizing candidates for drug discovery, same with materials. And then you do clinical trials. So meaning you go from simulations all the way through.

And then ultimately what happens is 90% of the candidates after all these trials fail and you’ve wasted 10 years, one to two billions of dollars, and you only have a 10% success rate. So quantum computing will flip that. So whether it’s drug discovery materials, the simulation of complex systems as the starting point, which traditional computers are doing, quantum computing will do significantly better. And the hope is instead of taking 10 years, you can actually do it in significantly less time, say a year or even a few months. And so that’s why our world will look very different.

John Stackhouse 00:12:08

Stephanie, walk us through some of the opportunities that you’re most excited about.

Dr. Stephanie Simmons 00:12:14

Quantum mechanics is hard to simulate classically. By classically, I mean using light switch, zeros and ones. And because of that, we are okay at simulating small chemicals like some of the small elements that we use for drug design and the rest. But once we get to heavy atoms or complicated molecules, even as complicated as caffeine, we can’t simulate it fully.

So having a tool fit for purpose for the material world opens up with the opportunity to produce not just a large language model, but a large chemistry model or a large physical model to really understand how the physical world works, which would be a whole other layer of capability that we can then bring to whatever industry we want. That can help with corrosion, it can help with metabolism, it can help with more complicated drug design, photosynthesis or redesigning of the energy landscape with having new catalysts to help with all kinds of energy efficiencies. That’s a big one.

In the financial world there’s a lot of people that are looking at how to use these tools to better help with some of those applications, whether or not it be optimization or detection of anomalies or whatnot.

There’s a way to leverage not just AI and classical computing, high-performance computing, but then bring quantum into the mix to have all of the computational tools available to sort out our most challenging problems computationally.

John Stackhouse 00:13:39

I’ve had the privilege of getting to see your computer up close. Most people will not get to see a quantum computer, but they’ll discover quantum through the cloud and through quantum as a service. Tell us a bit more about QaaS, Quantum as a Service and how different enterprises, but also individuals should be thinking about accessing quantum through the cloud.

Dr. Stephanie Simmons 00:14:03

We should all have roadmaps internally. By we, I mean the broader community. How does it impact your business? And understanding those applications and doing the application engineering and development to know what kind of quantum resources you’re willing to pay for. If we were to put a hyper capable quantum computer into the cloud, most wouldn’t know what to do with it. So having that roadmap for like, ” Hey, what would you pay for?” I think that’s really important because if you don’t do it, your competitors will, and then they’ll be able to use it to their advantage in a first mover sense.

Quantum as a Service is the way to get quantum capabilities into the hands of everybody who needs them, but can’t afford a single system. But this is similar to how we’re using cloud compute today. Most teams don’t want to build their own data centers, but they do want to have access to that capability. And I think what’s going to happen over time is the field will progress and the quantum part of it will be under the hood, and you’ll only see the application layer.

And that is again, how people are using a lot of the tools today, right? AI or high performance computing, the really, really high performance teams will go all the way in and understand how to do it themselves, but there will still be a lot of appetite for the high level access that only is providing solutions to problems, not compute cycles themselves.

John Stackhouse 00:15:29

As that evolves, again, help but think about sovereignty and security, the more that quantum is distributed. If you have your own computer as you do, I imagine that is more secure, but as quantum gets distributed through the cloud, there’s more vulnerabilities. How should we be thinking about both sovereignty as a country, but also security for organizations and individuals as that distribution starts to accelerate?

Dr. Stephanie Simmons 00:15:56

That’s a wonderful question because the last thing you want to do is have a quantum computer that could hack anything just be freely available online. That one might be a bit messy.

John Stackhouse 00:16:06

That’s a scary thought.

Dr. Stephanie Simmons 00:16:07

Well, I mean, okay, let’s just be clear. If we get through the cybersecurity transition, which will be a transition, there’ll be some number of years and then we’re done with it, then we should have those tools available for everybody to use for whatever they need. So there will be a place where we think about yes, sovereignty and security through this transition, and that’s where, again, especially because Canada invested in quantum so early, we have a little bit more cultural awareness here than most other countries. We should take that step and be in front of it because then we could be one of the first to actually, from a security perspective, leverage the full benefits.

Now, this comes back to the value side. Perhaps all you’re asking for is an optimization to a problem. And you could submit that job rather than have access to the computer. Then you could make sure that the actual requests are secure, right? Because asking for an optimization is different than asking to hack a communication. Right? And so that could be managed from a security perspective by the providers and done so in a way where it’s not limiting the providers to actually provide value to the world.

Now, I would share that Canada’s way ahead of many, many nations on quantum. And there’s maybe a top 10 list of teams around the world that are on this race to deliver these big commercial scale systems with all these applications. And so from a sovereignty perspective, we have the opportunity to not make the mistakes that we did before and actually double click on a commercialization frontier for this technology, not just invention.

I think it’s our time to learn lessons of commercialization from a sovereignty perspective, because if you take a look at how a lot of new technologies have been developed, you take a look at the iPhone for example. Most of the components for the iPhone were developed through DARPA contracts, a US government agency that fueled defense aspects, but also then were used in the commercial market. And I think that we can learn lessons like that because those programs, they’re absolutely part of the mix, especially if it’s important from a sovereignty perspective to be first and have an actual commercial landing.

Some of the other incentives that come along are all kinds of matching programs or incentive programs. These are really part of the game. And teams want to succeed in stable, lovely places like Canada, but the money talks too. So yeah, we do have to think about that structure and make sure that the plans and structures are in place because people want to win here, and we absolutely can.

John Stackhouse 00:18:41

Companies and universities, public sector organizations and individuals need to come to grips with this incredible opportunity. What’s the key to get going with and focus on in the year ahead?

Dr. Stephanie Simmons 00:18:53

Yeah, I would suggest get a quantum transition plan in place. There’s a lot of work that now exists that you can leverage. You don’t need to start from scratch. Part of that is going to be putting some of the suppliers on notice that you as an org need them to be quantum secure. And also think about internally how you want to benefit from the applications that are known already, and then think about developing them further. Because I would tell you that those applications are coming in thick and fast now because people are really seeing how close this is.

I think back to Avro Arrow and Bombardier and Nortel and Blackberry, I mean, we can do it and we can keep it if we learn from what structurally seems to be working elsewhere, just honestly pattern- matching and hitting that market. So one of the things that the US government is doing, for example, is putting in $ 300 million per quantum company that they think has a shot on goal. And Canada very helpfully is playing with that market force. And so that’s an awareness thing that I think is really positive progress.

From a regulation perspective, I think it’s important to not get too fearful and lock it down because that could be a market force that’s a disincentive to actually build. But let’s just be smart about it, right? Let’s get the cybersecurity in place across the country. We already have a date now. 2030 is our date with the Five Eyes. In general we are thinking about this date, plus or minus. I think we need to bring it in a little bit personally, but that’s because I know some things that maybe others don’t. And we can do it. There’s nothing wrong with it, and then we can really benefit. I think it’s going to be a wonderful wave of capability that we can use on all kinds of hard problems.

John Stackhouse 00:20:30

John Stackhouse: It’s no coincidence that in pretty much every national strategy we now see whether it’s defense and space or autos, and of course, AI, quantum is a key element. And a lot of that is due to your leadership, Stephanie. So thank you for that and thank you for being on Disruptors.

Dr. Stephanie Simmons 00:20:48

Oh, absolutely. Thanks for having me on. It’s a great conversation. Really appreciate it.

John Stackhouse 00:20:55

Here’s one thing that’s really important to remember. Quantum computing isn’t some day, it’s now. The systems are real. The threat is active, the clock is ticking, but this isn’t a story about inevitable disaster. It’s a story of choice. You can treat quantum as both a capability bet and a security retrofit. You can start now inventorying where you rely on cryptography, prioritizing what must stay secure and migrating to post- quantum strategies before today’s protected data becomes tomorrow’s breach. Or I guess you can wait for the headline moment, but by then, too late.

If you want to know more about quantum, check out rbc.com/thoughtleadership. You’ll find lots of great content there, including a new quantum primer from our research associate, Sabrina Schuchel.

You’ve been listening to Disruptors, an RBC podcast. Please rate, review and follow us on Apple or Spotify or wherever you get your podcasts. It helps more people find conversations like the one you’ve heard today. I’m John Stackhouse. Thanks for listening.

The $15m Cliff:  Keeping Canadian Agri-Food Startups Scaling at Home

SPEAKERS

Lisa Ashton, Darren Anderson, Kyle Scott, John Stackhouse

John Stackhouse 00:00:10

Hi, it’s John here coming to you from Ottawa to talk about agriculture. Now, I know this isn’t exactly the place you probably think about for agriculture, or for that matter, the time of year. Ottawa is frozen, and by frozen, I mean minus many double digits, and it’s hard to see any green shoots around the place even during Winterlude. But Ottawa this week is actually the very center of an important debate about Canada’s agriculture future and particularly about the kind of capital we’re going to need to grow quite literally a lot more in the years and decades ahead.

On this episode of Disruptors, we’ll hear from leading innovators as well as capital mobilizers, but I want to kick off with my colleague, Lisa Ashton, who is RBC’s Ag Policy lead, and the author of a new report on Canada’s growing challenge of capital for agriculture and particularly ag tech. The report’s called Seeding Scale. Lisa, welcome back to Disruptors.

Lisa Ashton 00:01:13

Thank you for having me.

John Stackhouse 00:01:14

What do we need to be thinking about as a country in terms of the capital that farmers and all the techies behind them are going to require in the years ahead?

Lisa Ashton 00:01:24

So over the last few months, I’ve had the opportunity to go literally coast to coast, meeting with farmers and processors in PEI and incubators in Vancouver. There’s a deep concern that we’re exporting our startups because we’re not supporting them at the growth stage.

John Stackhouse 00:01:42

Let me pause you there, Lisa, because that’s a well-known challenge in tech land that get gobbled up by American VC firms or bigger tech companies. This is actually happening in ag too. Tell us more about the ag tech companies that are getting gobbled up, particularly by the US.

Lisa Ashton 00:02:00

Certainly, so it’s not even just ag tech companies. What we’re hearing is this challenge about agri-food companies within the Canadian context. They have relatively strong support at the early stage. We have incubators, accelerators, venture firms that are really growing within the sector. But once they get to about the 15 million market-

John Stackhouse 00:02:20

Is that 15 million in capital size or revenue or something else?

Lisa Ashton 00:02:24

In injections in venture into a growing company. What that means is that those companies that are looking for Series B, Series C, Series D types of funding to grow their business, they have to start to seek foreign funds, which isn’t necessarily a bad thing. But when we think about the domestic regulatory frameworks in terms of bringing products to market and getting approvals in Canada, mixing that with the capital challenge drives companies to foreign markets so you can almost simply think about it as we’re investing in Canadian IP and then exporting that IP to benefit other countries’ productivity, job growth, and expansion of their agri-food sectors.

John Stackhouse 00:03:08

One of the things I found really interesting in your report, again, it’s called Seeding Scale, is that this was not always the case. In fact, just a decade ago in the 2010s, Canada was doing much better in terms of capitalizing ag-tech, and then it seemed to go off a cliff with the pandemic.

Lisa Ashton 00:03:26

Yes, there’s certainly a downturn in terms of growth capital across sectors. We see a 10-year low in terms of value in deal count for agri-food growing companies. Venture firms were really hot and heavy up to the 2021 peak, and we’re seeing the capital flow much slower. The sector attracted roughly 4% of growth capital over the last five years, and when you think about that in comparison to the sector’s contribution of GDP, around 7%, it’s certainly undercapitalized in that regard as well.

John Stackhouse 00:04:00

One of the other challenges I’ve seen is also the lack of knowledge in a lot of companies, whether it’s those federal agencies or VC shops, they have people who really understand software as a service, but have no understanding of how agriculture works. That’s not the case in the United States. When I get to visit VC shops in Silicon Valley, there will be an ag-tech expert who has deep subject matter expertise. Two things going on this week that we’re part of. One is a national round table with Canada’s agriculture minister, Heath MacDonald, as well as investors and operators and innovators from across the country talking about this very challenge. Also, Farm Credit Corp, a big federal agency, has its annual Future of Food conference where farm leaders and agriculture leaders from across the country get together. Maybe that’s one of the reasons it’s happening in February, not a lot to do back on the farm.

Follow us on our social media channels for more on those engagements. I think it’s worth stressing that for all the talk we’re hearing, and it’s good talk about the amount of capital Canada is going to need over the next decade to build more economic independence across the country and across all sectors. Yes, we’re talking about oil and gas and minerals and advanced manufacturing and auto and defense and space. Not enough talk about agriculture.

Lisa Ashton 00:05:27

I couldn’t agree more, John.

John Stackhouse 00:05:28

It’s probably maybe closer to 10% of the national economy, that and more of export potential. I like to say it is the one sector that stitches together every single community across this country. It’s also important to our national fabric, and it is all about technology. As we’re talking about attracting capital, retaining capital, growing capital, in all these other sectors, we got to think agriculture, agriculture, agriculture as a place where we can really scale fast. Lisa, before we get to our guests and expanding this conversation, what’s the one thing you would love Canadians to really come to grips with as we think about the year and the years ahead?

Lisa Ashton 00:06:13

I really hope that Canadians come to grips with the potential in agri-food. It’s a large exporter. It’s a key exporter for the Canadian economy, but within our regional hubs from Vancouver to PEI, it really is a driver of innovation across universities and businesses and governments. And so it really is a place for career development, but again, that investment in terms of the opportunity to grow and meet Canada’s ambitions that have been clearly laid out over the last few months.

John Stackhouse 00:06:47

Let’s hear now from a couple of amazing Canadian innovators who are on the front lines of all this and more. Darren Anderson is CEO of Vive Crop, a company building solutions that have to work in the real economy in real growing seasons. And Kyle Scott is the Managing Partner of Emmertech, a Canadian ag-tech investor who knows a thing or two about how to attract and grow those millions of dollars that we’re going to need in the years ahead for Canada to be a true ag superpower. Darren and Kyle, welcome to Disruptors.

Darren Anderson 00:07:19

Thank you for having us.

Kyle Scott 00:07:20

Thanks very much.

John Stackhouse 00:07:21

Darren, I’m going to start with you. Give us a snapshot of the vision you have for the company.

Darren Anderson 00:07:26

Sure. We make more sustainable and effective pesticides, and it’s all based on technology that was originally developed at the University of Toronto almost 20 years ago now, which is kind of crazy to say out loud. But we bring products to market that increase producer productivity, increase their profitability, increase their sustainability, primarily focused on North America and our products will be used in about three million acres this year.

John Stackhouse 00:07:48

And how big are you today?

Darren Anderson 00:07:50

We’re about 75 people. About 95% of our revenues in the US will be about 25 million in revenue in Canada this year.

John Stackhouse 00:07:59

Great story just getting going. We’ll come back to what you need to keep that going. But Kyle, tell us a bit about Emmertech.

Kyle Scott 00:08:06

Emmertech is a Canadian-based investment firm. We invest solely in agriculture companies, mainly domiciled in Canada. It’s mainly strategic egg companies, so some of the large corporates in the sector, and then a number of high-net worth farmers from across the Canadian prairies as well.

John Stackhouse 00:08:21

And Kyle, what have you needed to get Emmertech up and running and to succeed where maybe others have shied away in Canada?

Kyle Scott 00:08:29

I’m originally from Saskatchewan. Spent most of my time working out in Toronto in management, consulting and private equity with some of the largest players in Canada. I think that one of the things that I noticed then as well as now is there’s just not a lot of people who come from that space who are pursuing agriculture and agricultural opportunities. I view it as a pretty big part of my role to get more of those people interested and knowledgeable about the space to be able to bring more investors and more capital into agriculture.

John Stackhouse 00:08:58

And one of the big things, if I can call it that, that you’ve been instrumental to is a commitment this week among a range of financial institutions and capital mobilizers to get roughly a commitment for $ 4 billion of new capital. For ag-tech, this is being led by Farm Credit Corp. RBC is part of the pledge. Kyle, what were the biggest challenges in getting those commitments to this $ 4 billion?

Kyle Scott 00:09:25

Yeah, for sure. More champions in the sector and doing a better job of telling our story, I think are two of the big ones. We have some of the greatest founders in the world here, especially when it comes to agriculture. And when you speak with Canadian founders, it’s truly compelling how close they are to their end customer base. I think, John, you might’ve alluded to this earlier about how agriculture in Canada touches every community and touches everyone in the country.

And one of the things that’s starting to attract more and more capital into the sector is just having those founders out there, doing a better job of telling our story, and quite frankly, starting to have some pretty significant wins. When you look at a company like Vive, like Darren’s company, what they’ve been able to build and grow domestically from Canada has been truly amazing and it’s just getting started, and there are myriad other examples like Darren across the country.

Darren Anderson 00:10:18

Well, and I think there’s actually a unique opportunity in Canada specifically because, to put it bluntly, because we tend to operate in a more capital constrained environment, Canadian founders tend to build real companies earlier than maybe some of our competitors down south. And so I think one of the things that that means is when companies are now ready for that growth stage, they’ve built one heck of a foundation to grow off of that their competitor companies just don’t have.

Lisa Ashton 00:10:43

Darren, just quickly, what do you mean by real company? We heard from a lot of stakeholders that startups may be coming out with solutions that don’t actually solve a problem in the agri-food sector. Is that maybe what you’re referring to or is it something else?

Darren Anderson 00:10:58

There are a set of companies that, to put it bluntly, are better at selling to their balance sheet customer, to their investor set than they are at selling to real farmers and making a real difference on the farm. And those companies can often raise capital quite successfully and grow quite successfully, but those are also the ones that tend to get way out over their skis and potentially end up just not making it. And I think we’ve seen a number of those high profile failures recently. I think for a lot of Canadian companies, presuming the farmer need is there, the reality is because they’re capital constrained, they have to know how to make money out of the gate. They have to know how to generate a real demand, real value to the farmer. They have to know how they’re going to make money, and then that sets them up to be able to scale quite rapidly as they build that repeatable, predictable, scalable engine inside their companies.

John Stackhouse  00:11:49

Darren, one of the riddles I think a lot of us wrestle with is the opportunity and challenge of the United States. So you said, what was it? 95% of your revenue is now in the US, that’s great. I mean, every Canadian company needs to be almost out of the gates an exporter. The best market to start with an export strategy is the United States, despite all the concerns that we have right now, it is our ticket to scaling, but it can’t be our only ticket.

One of the challenges though that I hear about over and over and over again is that a company becomes largely beholden to the US market. Then it starts to raise Series C, D, E from US VC companies who offer sometimes more favorable terms, who have subject matter expertise, and then say, “Oh, by the way, now that we’re taking a material share in your company, we’d like you to move to Austin or Silicon Valley or wherever they see the opportunity to scale there because you’re in a bigger ecosystem.” Walk us through how Vive is navigating those currents.

Darren Anderson  00:12:53

Yeah, we’ve been fortunate in that our shareholder base is still very much dominated by Canadians. We haven’t had some of the pressures that you’ve been talking about.

John Stackhouse  00:13:02

95% of your revenue in the US, 80% of your capital in Canada.

Darren Anderson  00:13:06

Correct. And I mean, there are many issues with that. I’m incredibly passionate about bringing our tools to Canadian growers, and if you think about it, 80% of our capital is coming from Canadian capital pools effectively to help US growers out compete Canadian growers because the US growers have our tools and the Canadian growers do not. I don’t think that’s what any of us want to be happening, but if we look at our next stage of growth, there is no growth stage capital in Canada for companies like ours, almost nothing. What FCC is doing is incredible and has the potential to be incredibly catalytic, but before they came along, there was almost nothing as far as growth stage capital.

And so for us, the next stage of growth was going to have to be in the US or in Europe or in Brazil where you have these major funds that have the agricultural expertise that you all talked about and know what it takes to build a company. And I worry about taking capital from those types of organizations and having them say, “Yeah, I understand it’s awesome that you’re a Canadian company, but why don’t you look at moving?”

John Stackhouse  00:14:04

But we can fix that. Kyle, I’m looking at you.

Kyle Scott  00:14:08

Yeah, it’s a bit of a funny problem. Up here, we do really, really well with early stage financing. The problem is that we’re one of the larger ag tech investors in the country, and we can’t go in when Darren or some other companies that we know quite well across the country are looking to raise 30, 40, 50 million dollars. That’s an entirely new snack bracket and requires an entirely different fund structure to be able to participate in. So in Canada, it’s once you hit that growth stage that there’s really, really a significant lack of capital. This year, two of our other companies as well have gone out and successfully raised $ 30 million plus rounds, and almost all of the capital and certainly the lead investors from those have come from either Europe to US or elsewhere, not domiciled in Canada.

John Stackhouse 0 00:14:56

What on the corporate side, Lisa, do we need to ensure that the value chain, as it’s called, is investing in farmers and ag tech companies?

Lisa Ashton  00:15:04

There are a few movements that are happening currently in the agri-food ecosystem, particularly the Canadian Food Innovation Network has designed a program that is specifically for connecting corporates to early stage founders. This is mutually beneficial so that food retailers, for example, can actually see what’s coming down the pipeline, seeing what kinds of food innovations or food products are being developed, and then it provides the startups with early access to their potential buyers, their potential exit, or their potential collaborator across the supply chain.

Kyle Scott  00:15:43

Yeah, one of the things that we definitely see is more and more productive corporate engagement when they’re participating with funds. Either as an investor in a fund that then invests in companies or alongside into the company, there’s quite a few examples, fairly well known, that when a corporate gets too involved and has too much control directly of a company, it can go pretty sideways pretty quickly for the founders. There’s some different mechanisms to get more involvement, and I think what Lisa was referring to there, the corporate participation, if we could see an elevated level of that working alongside more of the investors in Canada, I think that that’d be super, super helpful.

John Stackhouse  00:16:27

Kyle, take us through the typical journey of a growth company. As you’re saying, there’s plenty of early stage capital from folks like you. Get to $ 15 million valuation, you’re fine in Canada. Now we may have public sector entities like FCC and BDC that would help bridge the valley of death as it’s known. But with all due respect to those organizations, they tend not to be cutting edge on a global platform to help companies get to that unicorn status. What should we be thinking about as a country to ensure that we do have that sophisticated, savvy, globally relevant growth capital operation that firms like Vive can work towards as they get through the valley of death?

Kyle Scott  00:17:14

Holy smokes. It’s a tough nut to crack, and one of the things I’ll say about the Crown Corporation, specifically EDC, BDC, and FCC, they’re an interesting participant in the ecosystem because I firmly believe that they want to be helpful and they will follow another investor into an investment, but they will not lead an investment. And so the challenge you run into is that those groups are there to participate. They are not there to solely carry the torch for a company going forward. So without someone to match or someone else to lead, that tool stays in the tool belt and can’t be used. So that becomes one of the challenges with those groups. The broader point about how do we create more globally relevant larger growth stage ag-tech investors. To be perfectly honest with you, it’s one that I’m trying to fix right now. It’s a gap that we’ve clearly identified as we’ve invested in early stage companies and they’ve grown up.

One of the number one places for us to be able to go is our Canadian financial institutions and our Canadian agriculture corporations who really, really care about the sector. And so for us, it becomes much like when our founders go out to raise capital, it becomes being able to tell the story, show why this sector is important, and because you are investing in financial assets, show why you’re able to make money doing it. To tell those three parts of the story to people who are unfamiliar with the sector takes time, it takes resilience, and it takes on your investor side, someone willing to take the leap with you and put money to work in the sector.

John Stackhouse  00:18:47

One of the challenges there I suspect is just exposure. It’s knowledge. If you go into any financial institution or large investment operation, likely they have experts in life sciences and health tech. Increasingly, I suspect there will be that expertise in defense tech because that’s the hot hot thing now with tens of billions of dollars of new NATO commitment coming to the fore. And then there’s poor old agriculture, our original growth sector where we just take it for granted, but don’t have that expertise in probably the large pension funds, but other large institutional investors as well.

Kyle Scott  00:19:23

Yeah. To your point about the institutional knowledge around agriculture, it’s funny. I say this pretty frequently. It’s nice for agriculture that it hasn’t been, and I say this lovingly, co-opted by the MBA mentality. I’m an MBA, so I get to say that. But the downside of it is that a lot of the folks who rise up into those roles and come from there, they just don’t know the sector. I think that one of the challenges there is more fundamental and goes back to how do we make agriculture a cool, interesting industry for more folks who are passionate about finance, passionate about investing to be able to come in and actually drive those outcomes.

John Stackhouse  00:20:00

Make agriculture cool again. I’ll let people play with that, especially in MBA schools for all the MBA deans listening.

Lisa Ashton  00:20:11

Darren, you raised a really interesting point that beyond just the growth capital challenge, there’s a number of other factors to why you’ve seen your markets grow in the US much faster than Canada. In our report, we looked at the three Cs beyond capital, and one of those is competitiveness. Would love to hear your view on that and why you’re seeing those factors lead you to a market growth in the US relative to Canada.

Darren Anderson  00:20:37

I do think for any Canadian agri-tech company, they’re going to have to be looking at the US as a market, but unlike in almost every other sector where the US is 10 times the size of the Canadian market, in most areas in agriculture, you’re looking at being something like a third. So the question is just how do you capitalize on them? So as you noted, we started selling in the US in 2016 when we received our first regulatory approval. We received our first regulatory approval in Canada in 2023. We have 11 products approved for use in the US right now. We have one product approved for use in Canada.

John Stackhouse  00:21:08

Darren, let’s pause for a second there. You’re saying that you’ve had one regulatory approval in Canada, 11 in the US. If Team Canada loses 11 to one to Team USA, it will be a national crisis. We got to come to grips with that. Give us a sense of the quick changes that you would like to see happen this year to allow us not to lose 11 to one, but actually maybe win 11 to one.

Darren Anderson  00:21:33

I’ve got one big swing, and then one small swing, if you’ll permit me. On the big swing, I think there’s an opportunity for Canada to target a culture of reciprocity, reciprocal recognition of regulatory approvals from other countries. Now that wouldn’t be in all cases, right? But default is that if something’s been approved in Australia or if it’s been approved in the US, it should be a faster path to be able to bring those products to market here in Canada. That would be one change. It’s a big one, but it is doable and it is something that I’d like to see our trade representatives focused on. The smaller ask is, if you think about, we’re spending so much time right now talking about “buy Canadian,” what about “regulate Canadian?” Canadian domestic companies, front of the line for regulatory approvals.

John Stackhouse  00:22:17

Seems easy. Kyle?

Kyle Scott  00:22:19

We often say capital’s like water, it’ll find the path of least resistance to the largest ROI. And so removing some of those regulatory burdens and regulatory pathways that allow our companies to scale and commercialize rapidly would be hugely beneficial to attracting more capital to the sector.

John Stackhouse  00:22:35

Yeah, capital is like water. There is no shortage of capital in the world, no shortage of capital in Canada actually, but a lot of it is flowing to the US because of those opportunities. Even over the last 12 months, capital has been flowing fairly assertively to the US because of the opportunities there, including in ag-tech, which we know is so critical to the country. We know what the challenges are, but let’s also think of the opportunities. We are hearing more interesting Canada from around the world, across all sectors.

I actually got to spend time with a European investor who, the firm’s been around for 400 years. They said, “We have 50 year strategic plans and we review them once every five years. And we’ve just gone through a review and we’re actually really interested in Canada and we’re really interested in Canadian agriculture because when we think about all that the world is going to need over the next 50 years, food is going to be one of the big needs. So we are looking for investible opportunities in Canada right through the value chain over the long haul.”

Darren, give us a macro view of what you’re seeing out there in the world and help us understand what we can do to bring more of those opportunities to Canada.

Darren Anderson  00:23:57

The way we view the world right now is there are a massive number of companies out there that would be really, really interesting targets for us to go acquire. We’re actually actively in market right now looking at a number of those targets where we can bring them in house, take advantage of our distribution network, our technology, and build that unicorn right here in Canada. Canadian companies, because they tend to be capital constrained, are good companies. These companies have solid foundations and those are amazing foundations to build off of whether you’re looking at organic or inorganic growth, and I think given the overall market conditions right now, it’s an amazing opportunity to be building something like this in Canada.

John Stackhouse  00:24:36

As we move towards close, I want to take that big picture idea forward. Our research at RBC shows, Lisa, I think we can grow our exports by at least 20% by the end of this decade. That’s our moonshot as a country, and it isn’t just producing more at the farm level. It’s developing lots of technologies right through the value chain of agri-food production so that we can be more competitive here at home, reduce food costs for everyone, but also make ourselves more relevant in an increasingly competitive global market that is going to need lots more food. Kyle, what’s the one thing we as a country need to come to grips with this year in 2026 to get that payoff by 2030?

Kyle Scott  00:25:22

I’m going to cheat and say that there’s two things that I’m thinking about. The first one is working with international partners, attracting more FDI into the country, investing alongside in our companies with knowledgeable investors who can help us export to other markets is critical. So whenever we hear there are other investors passionate about investing in Canada, I think it’s wonderful. The second thing I would say is there’s a lot of ag infrastructure that is due for an upgrade where we can leverage some new technologies as well to become a more reliable, not only producer, but trade partner and exporter.

John Stackhouse  00:25:56

That’s a really interesting point about export infrastructure. Darren, what are the one or two things you would suggest we come to grips with this year for that 2030 payoff?

Darren Anderson  00:26:05

I want to see the FCC capital commitment and the capital commitment by groups like RBC and Emmertech land successfully. I actually think that that is an absolutely transformative and catalytic event for the ag-tech space here in Canada. I think it has the scale that’s coming behind it and the ability for it to have an impact across the entire ecosystem is incredible, and I think making sure that we follow through on those commitments would honestly be the single most transformative thing this year. The nice thing is it’s already underway.

John Stackhouse 00:26:36

Lisa, as we wrap up, seeding scale has so many ideas in it. What are one or two that you want to leave us thinking about?

Lisa Ashton 00:26:44

Darren, you brought up unicorns. When we looked around the world, we looked at China, the US, India, they have stables full of unicorns. The UK, Australia, even Ireland, more countries that we would consider our peers have examples of unicorns in the agri-food sector. Canada has none. So these unicorns, they’re privately held startup companies that are building revenues of over a million dollars per year. And I think building some unicorns in Canada should certainly be a moonshot for Canadians to be thinking of.

John Stackhouse  00:27:17

Yeah, we really should have the Shopify of ag-tech.

Lisa Ashton  00:27:20

Absolutely.

John Stackhouse  00:27:21

There’s no reason that Canada can’t. We just need to continue to scale what we’re doing. Thank you all for being part of that scaling story and for being on Disruptors.

Kyle Scott  00:27:31

Thanks so much for having us.

Darren Anderson 00:27:32

Thank you.

John Stackhouse 00:27:35

Before we go, if there’s a through line from today, it’s that this is a solvable design problem. Canada has the land, the operators, the science, and the entrepreneurs. The work now is alignment, capital that fits agri-food realities, pathways that prove adoption in the real world, and the confidence to build value add here at home. Lisa, your report, Seeding Scale, how can people find it?

Lisa Ashton 00:28:02

It’s live now. Please visit rbc.com/thoughtleadership. It’s part of our growth project where we’re really focusing on key levers within the Canadian economy that can help us achieve our national growth ambitions.

John Stackhouse 00:28:17

If you found this episode useful, please follow Disruptors wherever you listen. Better still leave a rating and share it with someone who’s building or funding what comes next.

I’m John Stackhouse, thanks for listening.