Endgame with Gita Wirjawan - Olaf Groth - Techno-Confucianism: Is a New Cold War Happening?

Episode Date: December 17, 2024

Does the world feel like it’s on the brink? Olaf Groth believes we’ve faced similar challenges before—and overcome them. In this episode, he explores why thoughtful policymaking, not hubris-driven innovation, holds the key to navigating our dysfunctional and fragile global systems. From politics and economics to technology, this conversation spans the US, China, Europe, Southeast Asia, and India, offering insights into a world in flux. #Endgame #GitaWirjawan #OlafGroth ----------------------- About Luminary: Olaf Groth is the founding CEO of advisory think tank Cambrian Futures. He serves as a professional faculty at UC Berkeley’s Haas School of Business, adjunct professor of Practice at Hult IBS, and honorary adjunct professor at Universiti Teknologi Malaysia. Groth is the lead co-author of “The Great Remobilization: Strategies & Designs for a Smarter Global Future” (2023) and “Solomon’s Code: Humanity in a World of Thinking Machines” (2018). About the Host: Gita Wirjawan is an Indonesian entrepreneur, educator, and Honorary Professor of Politics and International Relations at the School of Politics and International Relations, University of Nottingham. He is also a visiting scholar at The Shorenstein Asia-Pacific Research Center (APARC) at Stanford University (2022—2024) and a fellow at Harvard Kennedy School's Belfer Center for Science and International Affairs. ----------------------- Other episodes you might also like: Dr. Yasantha: AI vs AGI & Homo Sapien's Next Chapter Michael Levitt: Studied Physics, Masters Biology, Won Nobel in Chemistry Phillip Wong - America vs Everybody: Will The US Win The Chip Race? ----------------------- Explore and discuss this episode further: https://endgame.id/ ----------------------- Be our collaborator and partner: https://sgpp.me/contactus ----------------------- IN THIS EPISODE 01:28 - Personal background 05:58 - ‘The Great Remobilization’ Book 09:32 - What makes Olaf so optimistic to tackle his ‘6Cs’ 10:59 - Big questions in solving climate change 18:36 - “It’s a shared catastrophe waiting to happen” 22:14 - Climate change and AI 24:31 - FLP-IT 28:33 - The bifurcation of AI development 32:14 - Why is Europe seemingly not catching up on AI 39:10 - Paradox of Internet 47:08 - Energy thirst of AI 49:36 - The Three Shifts 53:43 - Digital decoupling between the US and China 55:46 - India 58:26 - Open-source and close-source? 1:01:45 - Political influence on academics in the US 1:06:28 - Data irony 1:15:35 - Historical amnesia and cognitive immunity 1:18:07 - Industrial Revolution 4.0 x Society 5.0 1:24:58 - How to catch up in an AI world?

The income gap. We always talked about, you know, high, medium, and low-skilled. But frankly, we are not drifting into an era where it's high-skilled or low-skilled. That rift between you and that avant-garde is widening even further, right? Who is to blame people when at some point they feel so left behind, they're working two or three jobs, can't provide for their families, have no educational perspectives for their children. Who is to blame them at some point when they start throwing Molotov cocktails, right? We need to dedicate more time to the computer science folks, understanding humans, and those who are not mathematically scientifically inclined, right, understanding data and AI.

We have left droves of people behind in that globalization 1.0 paradigm, and we need to recognize and acknowledge that, rather than saying, how can we just put a band-aid over it and get people to just accept? So we do have to break through that. And that's where we need, again, wise policymaking. And I don't think we have that yet. Hi, friends. Today we're visited by Professor Olaf Groh,

who is a professor at practice at Haas, the School of Business at UC Berkeley, but he also gets involved with UT Malaysia. Olaf, thank you so much for gracing our show. It's a pleasure to be with you, Gita, and your audience, of course. Thank you. Thank you. Tell us about.

how you grew up. You were born in Germany and you got stuck in the U.S. for the last, what, 30 years, and you've been sharing your wisdom to a lot of people in the book. Well, thank you. I appreciate that. Yeah, I grew up in northwestern Germany between the trading and banking town of Dissendorf and the Dutch border, small rural community of lots of lakes and fields. So a very agricultural setting. And I was born to parents who were both children of World War II and were both blue-collar, had not gotten any opportunity to go to college, but whose dream it was to instill a more intellectual grounding in their son. And so enabled for me this career very much that I benefit from today, and that enables me to have an impact on other people by sending me to college,

the first one in my core family, and then later to study in the United States. And I was only supposed to be here for about a year and then finagled my way into staying what is now 33 years shocking off. Who would have been more influential in shaping your educational journey? Your mother or your father or your siblings or friends?

They were both instrumental, but in very different ways. My mother was always the very studious one, very diligent about work, and instilling in me, of course, a certain diligence about getting your work done ideally ahead of time. I think my father was more of the intellectual in the family, and I think tended to opine on societal issues, on economic issues, on business issues more and more frequently. but, you know, by his own self-admission, didn't have the tools, really, to do so in a sophisticated way or for an audience that he needed to explain it to. And so I think that combination of the diligence and the intellectual curiosity and the drive really to do something in the public interest or at least something that's critically reflective, right? Both of them gave me that. I think the latter part, that was my father.

And I think both of them, having been children of World War II and having been through the, you know, what was called the economic miracle, the Virchavst Wonder at the time of rebuilding, had that building element in them as well. And that stuck with me too. And, you know, the idea of building your own venture or helping build some program or some academic strategy or or, or. you know, not to sound too grand, but helping build a country, right? Which is what they really had done. I think that's, that ethos stuck with me. Got it. In addition to your being an academic, you're also involved in Cambrian Futures. Yeah. Talk about that.

Yeah. So I'm the founder, a co-founder and CEO of Cambrian Futures, which is a, an advisory think tank that provides clarity for the emerging technology economy around. the world. So what that means is we do research, we create insights, we generate foresight on the role of emerging technologies like AI, data, brain computer interfaces, genomics, on policies, on, of course, corporate strategies as well, investment strategies. And we help decision makers see the future evolve more clearly, because there is so much noise going on and so much hype around tech these days that I think it sometimes takes a little bit of a clear-eyed view to cut

through that. So I work that with six other people who are mostly in the United States, but a few in Europe and elsewhere. We have a network around the world. But we're all more or less senior trusted advisors. This is not a traditional consulting firm. What motivated you to write remobilization? Yeah. You know, this was really between me and two colleagues of mine, Mark and Terrence, who during the pandemic, saw how there was this swelling of anxiety around the world, of course, understandably, because most of the people alive at the time and in junior or senior decision-making positions had never been through anything like this. There was this new phenomenon of this tiny little virus essentially crippling the global economy overall. And we felt that it was incumbent upon us really to help people, starting with our students, see through that pandemic and understand what lies beyond. The pandemic was really a prism through which we viewed the current dysfunctionality

and really the systemic fragility of our global economy or global, global 1.0, as it were. And so we wanted to use our skills and our networks to unpack that for people and show them, hey, why is that going on? What exactly is that fragility? And how do we see through this and see there's an opportunity to flip that chaos into a new horizon that we're all better off with? And so we decided to first do a webinar that anybody could join. That then became a another webinar, and before you knew it, we sort of thought we should, we should create this book to have more lasting impact. So that was really the impetus of it. You talked about the six Cs. That's right. Yeah, you want to talk about some of these or all of these? Yes. So, so,

so we started with COVID, but frankly, this is not about the virus itself. Right. As much as it is about the science, CRISPR, and of course, cognitive technologies that enabled vaccines, as well as, I think, a clear-eyed view of why we couldn't get a grip on this virus as quickly as we should have wanted to around the world, right? So the first C is COVID. And then, of course, there are cognitive technologies that I've already mentioned. So that's AI, data science. We briefly talk about the coming wave of brain computer interfaces that are already here and now awaiting commercialization and genomics and the role of AI and genomics. And then we go into cybersecurity because you can't really talk about all these digital technologies or even life science

technologies anymore without talking about cybersecurity. Crypto, because we believed that crypto and still believe that crypto is much more than coin. Coin is important, and we can talk about the ups and downs of Bitcoin versus Ethereum and other. But really, the underlying message of crypto is one of governance. It's Web 3. It's blockchain as an idealized version, and it is an idealist version of.

of more diffused, democratized governance with all of its promise and flaws, of course, right? And then existential threats like climate change. Clearly, you can't really write a book like this about the future of global 2.0, as it were, without talking about the one threat that could annihilate all of us, and that is climate change. And finally, China, that's a big sea, because you can't really do anything about any of the other seas without co-thinking China and engaging with China in vigilant partnerships. And so those are the six Cs. Really, the C that is, the cognitive technologies really spans all of the other Cs.

And I'm happy to talk about why that is, but that is the command and control mechanism. You know, some people call it cybernetics, which is an old term for technology-enabled command and control. And without that, really nothing else works anymore these days. We can talk about the 4 billion people around the world who still aren't digitized, of course, but the power center clusters around these digital technologies because they really enable the further proliferation of that power. And at once, they hold a lot of promise for us to do a better job, managing the other seas and many more things around the world because things have gotten so complex and so on. wieldy that the human brain and human institutions alone can no longer manage the interlocking systems of systems. So we're damned if we do and we're damned if we don't use cognitive

technologies like AI. You know, with the world order becoming a much more multipolar kind of will intuitively, there's just going to be more proliferation of risk, right? What gives you to confidence that there is an ability to remobilize. Yeah. You know, by where you're focusing on each one of those succeeds. Yeah. So we see indicators that people realize climate change is a global threat and it's existential. The fact that we haven't solved it yet is, of course, a catastrophic reality.

but I think the awareness is there that we should be solving it with policy and technology in lockstep. And I think that gives me hope that we will be too late to stay under 1.5 degrees, but it still gives me hope, call me an internal optimist, that once it becomes clear as we go beyond 1.5, how much we will be paying for not meeting that goal, that the financial interests around the world will wake up and exert a lot of pressure on the governing institutions and on people in general and other businesses, that something needs to happen very, very quickly because the fallout for investors, for insurances, et cetera, will be, will indeed be catastrophic. We're seeing this now here in California, where insurances are starting to pull back, the governor is saying, no, no, no, if you want to do any kind of insurance business

in California, you've got to have people, you've got to offer people. People fire insurance, but insurance companies are saying, but the proposition is not viable for us. And so change can be induced through financial pressure and changing incentives for financial institutions. So that's one area of hope. The other area of hope is that I teach leaders, of course, of all ages, but I also teach the very young ones.

And for all of the skepticism that everybody. around the world has about the young generations, you know, ranging from tremendous amounts of depression, of course, induced by social media, et cetera. And also, I think, some questions around whether they still see democracy as the guiding star, which is a bit of a Western notion, or Western-Nor-North notion, I realize that. Yes, all of those things need to be looked at, but I also see a tremendous resolve to be more socially minded and to be more equitable and to be more fair in society and to not focus on just a singular career that will make you a lot of money in exchange for working 70 hours or 80 hours a week, but rather working portfolios of different roles and careers in parallel, some of which tend to have these social and social. societal elements in them. So that's another area of hope. And then, of course, fault me for, you know, bringing a bit of a Silicon Valley view to this and I guess optimism on that front as well.

I do believe that if we govern technology thoughtfully and we design it thoughtfully, that technology can be a net tool for good. We all understand it's a Janus Head and for everything good you can do With technology, you can also do tremendous bad. And currently, the call is still out, whether we aim, which way we're going to aim. But the hope is still there that we're going to turn the corner with technology when we interviewed environmental scientists and economists and the people that go to COP, like you do. They openly acknowledge that traditional government-led processes are failing the world. I think the UN is doing the best that can, but I don't think we can call that a success to date. and they're now turning toward technology saying, hey, you all in Silicon Valley and all these

multibillionaires and VC firms, you really have to step up. And that's a flip. We had previously always heard, no, we actually need regulators and policymakers to step up first to set the right pricing mechanisms in the market so the entrepreneur knows what to go after in which way. And I think for the first time governments are saying no action. you have to, you have to lead the way. And that is, that's, that's a tricky message. How do you do that without the right pricing mechanisms, pricing signals? Right. How do you, well, I mean,

you know, we've talked about this earlier. There is a white gap between what the developed economies and what the developing economies, much less the underdeveloped economies, could afford, right? I'm not concerned about whether or not there is technological capital to address climate change, but the economic war with all is not there. For most people on a planet, I would argue 85% of the people on the planet, they can't afford the technological capital that's being availed by the developed economies. How do you think would be a realistic way of bridging that gap? Because it just doesn't look like it's being bridged efficiently and effectively.

That's the big question, Mark, because the deeper we get into artificial intelligence and data science, of course, which promises to give us a lot more insight about how the world works and how we can generate growth, the deeper we get down that path, the clearer it becomes that you need massive amounts of capital to do so. And that is why the big hyperscalor platforms and governments around the world are dominating that playing field. Very clearly, that's the United States, followed by China. And the rest of the world just simply does not have the financial resources. Europe, in theory, does, but cannot get its act together on a common market and on the right incentives for entrepreneurs.

But even if Europe were to solve its own problems, there is still the, all the rest of the world. And I hate to hesitate to call it the global south, but it includes, I would say, about 70% of all countries around the world. And that is a big concern. It's money and it's the development of talent for which you need money. And then it's data and the data infrastructure. Because even if you have a lot of data, you have to make it available along a certain

infrastructure and to do so takes that infrastructure investment, it takes that talent investment, and that is not currently enabled sufficiently. You know, part of that is that the development institutions around the world aren't digitally native either and lack the competency there. And part of this is that this is just progressing so fast that government institutions aren't equipped to jump onto that running train, as it were, and it's not going to slow down anytime soon. Now, on the argument that you've alluded to, that there's not enough economic war with all, there's not enough educational trajectory, there's not enough ability to compile and structure

the data points amongst most, if not all of the global south or developing economies, are you confident that we're going to be able to, in the context of climate change, attain carbon neutrality by 2050 or 60? No, I'm not confident. I remain hopeful, but that is in large part my personality that I tend to see a path where others don't. And that's an aspirational path oftentimes. So I do believe that the deck is stacked against us in that regard.

Now, the entrepreneur in me says the deck is always stacked against me. And my probability of failure is greater than the probability of success. So it's a normal situation to be in. But of course, that is not to diminish the potentially catastrophic impact on billions of people around the world. And we described this in the book. going to happen when the global south is not enabled by industrialized and post-industrial economies to adapt on time. We see, I think we say in the book, upwards of 500 million people migrating north,

that is going to, of course, create massive displacement, not just in the south, but in the north as well, massive political problems. So it's a shared problem that I think most people in the north are not seeing as such. But you see what's happening here in the United States with immigration as a political topic. I know it's a topic in China and elsewhere. It certainly is in Europe as well. So it's a shared catastrophe waiting to happen. Technology can help, but we need more capital deployed. Now, some, I think some of the hyperscalor-detect platforms here on the West Coast have realized this. I think there are some that are quite foresightful when you look at what Satya Nadella

does with Microsoft, for instance, billions, billions in investments. invested in training as well as sustainable energy sources, or at least renewable energy sources, including nuclear, of course, then I think that gives me hope that that's where the capital is, that's where the know-how is. If we now have wise policymakers in the global south looking at those assets and saying, okay, how am I going to, yes, welcome that capital and that expertise, but also leverage it to create indigenous local capability. And there are, of course, very smart examples in Southeast Asia, East Asia, and elsewhere, Africa, for instance, as well, where that has been done, but that is a preconditioned, right? Because what you want to do is leverage

that northern industrial, post-industrial economy, knowledge, and talent and capital, while also building local capabilities because you need those local capabilities to get to the next level of growth that can't just be fueled by foreign investment. There needs to be local capability building on must. And currently the few billion dollars I see invested are not enough. They're a good indicator, but not enough, clearly. You know, if you take a look at how much China built on coal, they built about 43,000 megawatts of power generation capabilities using coal last year, which is about 13 times the amount that Indonesia built. It just shows that, you know, as much as everybody wants to be environmentally friendly, the realism with which countries like China want to pursue AI. You know, I think climate change is a tough one.

It's a, it's a wickedly tough one. And it's the issue of short and medium-term necessity and long-term aspirations or medium-to-long-term aspirations. And we're not just seeing that, by the way, in Southeast Asia, we're seeing that we're seeing that elsewhere. And not just in China, we're seeing that elsewhere as well. We're seeing that here in the United States. I mean, Kamala Harris has said, look, she is in favor of fracking. I don't think she says that because she likes fracking or its environmental impact. Inevitably, got to rely on it.

Exactly. She's, right, it's a medium-term necessity if you want to stay energy independent. And, you know, for some very good reasons, the more you depend on foreign oil, the more you get embroiled in the geopolitics around that oil. And so, so, yes, I think. he, for instance, is a realist on that front and understands that if he were to just go with renewables, he sacrifices potentially slower growth than even he has now. And that means social upheaval, political upheaval. And as my friends in Beijing have said, when 1.4 billion Chinese

are at war with each other, the rest of the world will suffer as well. So I think we need to respect that. But on the other hand, China has also invested, whatever it is, $300 million in solar. And that's, I think. Oh, they're well ahead of many. Well ahead of many on renewables. But they still rely on coal. That's right. They need the energy. Yeah. I want to move on to the cognitive economy part. But before we get there, you used five letters in your book, FLPIT. Yeah. Talk about that. Yeah, we call it flip it. FLP-I-P-I-T, flip it. And it's a framework that helps you flip your mindset and your, really, your strategy from this moment of chaos.

Or as Genevieve Bell in the book called it, this liminal moment. We're in a liminal moment where we've thrown everything up in the air. It's very anxiety-inducing. We're not trusting our institutions anymore. And they're not providing for us, the public goods, for us anymore. And so it feels chaotic, potentially catastrophic. We've been here before, you know, after World War II, of course. And there have been other periods in human history where we've been at moments like this.

And now it's all about looking at the pieces that are up in the air and seeing when they come back down to earth, as it were, how do we arrange them and maybe add some new ingredients in to create a better system? There were a number of thinkers after World War II that got together here in the United States that thought about what kind of system do we want, and the thinking around the United Nations, etc., was in part spurred by those deliberations. we need that kind of thinking now. And so we have set this flip-it framework and help you understand

what are all the forces that are pushing us in various directions, putting all these pieces up in the air, and when they collide, what kind of logic do we see unfolding and how do we shape that logic, right? And then the question is, what kinds of new patterns do we see or do we want

and what kind of action do we take? based on that. So it's really, uh, takes you from looking at forces and building blocks up in the air, bringing them back down, looking for better logic and new patterns, better patterns. First principles. Exactly. First print. Well, in fact, though, uh, Gita, it's, it's really about zero principles. I see. And that's, that's, that's, that's really, you know, we, we picked this up from, from, uh, from, uh, interviewing Brian Johnson, um, uh, who has been in the news a lot with, with his don't die, Don't Die initiative, right? You know, the former CEO of Venmo and Braintree.

And, you know, he pointed us to this concept of zeroist principles. And that's really to say, we got to go beyond first principles. First principles are sets of rules that we have accepted to be axiomatic. But they may, in fact, just be human constructs because we can't think beyond. And so, for instance, first principles are always, you know, more growth is better. I think you and I know that that's not always true. But our markets are still very much focused on that. And I'm not talking about degrowth necessarily, but smart growth.

Well, what does that mean? And so getting to understand new building blocks and seeing those building blocks and those new logics, those new rules, is really what leaders need to be doing today. Not everybody does, I would say the vast minority does. The majority still plays to old rules that are set in global markets, whether that's Wall Street and the city, meaning London, whether that's gap rules and principles, but we're playing to old rules that are no longer fit for the world we're in now, much less the world we need in order to step away from the climate change brink or World War III, for that matter.

Interesting. Let's get into the cognitive economy part. You've been spending a lot of time talking about AI. I get the sense, and I've shared this with some people, that it's not, the AI narrative, is not being pushed forth in an adequately multidisciplinary manner. And intuitively, I just sense it could be problematic that it's not roping in the environmentalist, the culturalists, the sociologists, the economist, whatever dimensions beyond technology, right?

Do you share that sentiment or pulse? Or am I? Yeah, I think we are bifurcated today. Right. Between those that are the accelerationists, as they're called, that are saying, look, the train has left the station. We need to push as hard as we can to get the greatest degree of AI advance over the next couple of years. Everything else we can figure out, things will fall into place. And then you have what's commonly referred to as like the Church of Doom or the Doom

that are typically people concerned with AI safety, existential threats, and generally the AI ethics and governance crowd, which is very unfortunate, because governance, as you would know, is a tremendously important tool set in order to channel flows, whether there are flows of money or flows of technology IP or talent or data or genetic code. It's directing it in ways that yield the highest advances. And of course, you need to define what that actually means for a given society or a given organization. But governance is a very pragmatic approach. So we shouldn't have this black or white understanding, you know, really tribalizing each other.

We should come together in the middle and say, yes, look, we want growth. But we want healthy growth, sustainable growth, at a rate that is palatable for society and that doesn't just create more wealth for those who already have great wealth. And that's typically those who own the technology and the IP or the capital that allows it to build it into ventures. And so governance really should be sitting in the middle. But yes, I think currently the driving forces behind AI advancement are clearly still. in the accelerationist camp, if I were to use that language. I think slowly we are starting to look at, but how do we bring governance in there?

And there are some great precedence. There are some tech companies here that are outstanding, blazing the trail on this. But it's not yet the majority of platforms and tech companies, and it really needs to be. Some of that will be driven by, again, coming back around to the importance of investors in the financial markets as a change mechanism.

Some of that will be driven by investors who say, number one, you're not getting us the right ROI or the right quantifiable benefit, bottom line, top line. And some of them being insurers who say, if you all screw up with AI, I have to pay. And we're seeing the role of insurance insurance is actually quite important in climate change. So it will at some point become so in AI

as well. If you take a look at the amount of money that China and the U.S. are plowing into AI, it's disproportionately much larger than what I'm seeing Europe is, much less Southeast Asia. I want to ask you a few questions based on these observations. Why is Europe seemingly missing out on this digital revolution? Yeah. So it's, it, pains me to say this since I hail originally from Europe. Europe has lived obviously through world wars and a very painful history of bloody conflict for the past many centuries. There is a consensus mindset in Europe that lends itself to thinking about stability and a

strong preference for stability. when you look for instance at where I came from Germany there is a predilection I think in Germany to be uncertainty avoiding when you

when you try to conquer a new frontier whether that's AI or anything else genetics is another one of these you need to be able to to experiment to take certain risks, but when the majority of your population actually says, no, no, no, no risk whatsoever,

don't mess with my data, don't mess with my genetics, don't mess with my work conditions. And when that becomes the governing principle for everything you do in AI and data, it's clear you won't make any progress. So the reason for why Europe is not leading in artificial intelligence, and I think we do have to clarify what that means, obviously there are leading lights and AI. science in Europe and AI scientists in Europe play at the very top of the science pyramid. That's very clear. We also observe that there is massive amounts of entrepreneurial AI talent in Europe.

But that combination does not seem to get Europe off the couch when it comes to actually generating, creating ventures that can come to global standing and project Europe's view, which is one of individual dignity and the protection of the individual throughout the global economy. And some of that has to do with policy and regulatory frameworks, with capital formation frameworks and incentives. Venture capital is nowhere near where it should be, given where Europe is punching as a global economic region.

But really, most of it is rooted in the fact that Europe has a cultural legacy and a cultural DNA of many centuries of bloody conflict. And has finally gotten to a stage up until recently, well, I guess you could also look at the conflict in Yugoslavia as sort of the first element of this, that really this peace dividend that they thought they had after the cold. war of, you know, a successful attaining of regional peace, that that's really falling, falling apart now. And so the instinct of clinging very hard to stability in light of history and in light of recent events and making that the guiding no star for everything you do is inhibiting advances in artificial intelligence and data science. The instinct is regulate first. make sure that you shut off anything data related because that could be used to abuse people. And I might add, with some good reason, when you look at some of what the U.S. platforms have been doing

and what the Chinese platforms are doing, it's not that Europe is wrong. It's that Europe is ill-balanced. And so what happens then, of course, is when you don't create enough spaces for experimentation, that you will never get to that frontier of actually transporting, A, generating enough growth for yourself, but also transporting European values into the rest of the global economy. They're trying to do that with regulation, and it's working to some degree, but it's not sustainable

because people want livelihoods. They don't just want to have protection. Eventually, they need good jobs, and we're seeing what's happening with the European economy today. So it's a, I say a bit provocatively, Europe needs to watch out that it doesn't die in analog death. The GDPR, is that a manifestation of how or the extent to which Europe has not been a beneficiary of the digital revolution? Yeah, I think the GDPR was the sheer rigidity of it. That's exactly right.

And I think we need to recognize it was a stake in the ground, the first of its kind, that said, well, wait a minute. there are other elements here, as you were saying earlier, that we have to pay attention to. And those are fundamentally of ethical nature. However, it was overly rigid. I think the European Union took receipt of that. I think there is widespread consensus that it was a dual-edged sword. I think the EU AI Act that we got last year is, I think, a more well-balanced set of instruments. and it does acknowledge the role of experimentation with sandboxes.

I think it does not yet address the needs of the European entrepreneurial landscape. And some of that has to do with the common data market that is really not in place. It's in place on paper. But what's on paper doesn't really matter to an entrepreneur as much as what's happening in the street actually and in agencies. actually every day. So the fact that the administrative procedures are not homogenized means that an American, or for that matter, Chinese or Indonesian entrepreneur can't scale out efficiently through a 500 million people market, which theoretically should be bigger than the U.S. market, but it won't be for the foreseeable future because of the disparity in the fragmentation.

And so that needs to be addressed. I think a more pro-entrepreneurial view, more entrepreneurial voices in regulation need to be heard. You know, I've been hypothesizing that the Internet has been very good at democratizing information, but it has not been good at democratizing ideas. it has not been good at democratizing economic capital. As a result of which we're seeing certain economic phenomena that are quite disturbing, rising inequalities of wealth, income opportunities,

and now we're seeing rising centripetality of economic development, i.e. GDP per capita growth in primary cities much more accelerated than that in secondary cities. Globally speaking. Yeah. Developed, developing, and underdeveloped. And it's a bit paradoxical because in some developing economies, the talent and natural resource are actually in the secondary cities, but it's been extracted and pulled to the primary cities, right?

And I just think intuitively AI is going to further exacerbate this pre-existing condition or situation. What's your take on this? Yeah, I think that's right. I think economists have actually shown that AI and the importance of data and compute power and very expensive talent to develop it and to scale it out will actually lead to a further concentration of wealth in the hands of innovators in these innovation capitals around the world.

And they're usually first-tier cities, not to say that San Francisco is one, but I think San Francisco and the Bay Area and Silicon Valley, certainly in innovation terms, is that. And so, so, you know, that's certainly true. If you think about the evolution of the Internet, the idea was a democratization and a diffusion, but pretty quickly, you know, in Web 1, for instance, we, we, of course, had the, you know, the telcos, and we had the likes of AOL and MSN that had the infrastructure to build and then to add. application platforms on top. And then we got the over-the-top internet platforms, as it were, that are now forming what is maybe technically, legally, not an oligopoly, but structurally in reality, in terms of people's lives, it probably is an oligopoly.

And so now you have all this concentration of data and money. I mean, these trillion-dollar valuation speak for themselves. where is the next wave of more diffused innovation going to come from? And that's, of course, where the idea of Web3 came from and blockchain and the idea of crypto. And so, you know, we're going to have to see how far that will carry. But it's supposed to go back to the original thought of the Internet being a more democratized tool for self-expression, but also for, for,

for growth and for ideation and innovation. What's the risk that only China and the U.S. are just going to be completely dominant in the next 10 to 20 years or 20 to 30 years in the field of AI at the expense of some of us in Africa, Southeast Asia, and many other developing economies, to some extent Europe. Right. Yeah, to a large extent, Europe. because when you look at Europe, it has all but just a handful of platforms.

I mean, if we have SAP, we've got Spotify, but really it gets very scarce beyond that. So the risk is substantial and there are mitigating factors, right? And again, being the optimist, I'm hoping that those factors will come to bear. Clearly, we already talked about we're at this point today. because we have all this data. Where is that data? Now, it is stovepiped behind walls, either in the big Internet platforms

or the data brokers and advertising networks that do business with them, or, of course, large governments. But that's a handful of very centralized institutions. The same with capital, and the same with the talent that can be bought with the capital. You know, I still remember one episode where I had a meeting at Stanford. And a fellow professor came in and said, I'm sorry to be running late from a meeting where a young AI PhD was defending their dissertation.

And he said, we tried to offer him a tenure track role at Stanford right off the bat. But he had to decline because Facebook offered him a million dollar total compensation. and Facebook can do that and many companies on the West Coast can, but 99.9% of all companies around the world cannot. So how will that be mitigated? Well, institutions like Berkeley and Stanford and, of course, many around the world, U.T. Malaysia comes to mind, right? And I'm sure there are a whole slew of institutions need to think about how they put more talent through their pipelines. that's an institutional capacity problem. And at the same time, we're also now starting to see and hear from cutting-edge AI talent

that in fact the era of big data may be coming to an end. At least the necessity for big data for every single application area may be coming to an end. We may be able to do with small data, wide data, which is pockets of small data. for certain types of use cases quite well. And we may, this idea of, you know, billions and billions of parameters in these models, that may be coming to an end at some point as well, especially when you look at the success of open source

or semi-open source models like Lama and others. So we shouldn't straight line extrapolate from here. but certainly currently, that's where we are. Yes, that it's not looking good for countries that don't have capital don't have the installed base

of data or talent. I just think it's going to get much more elitized. You know, at the rate that only a few companies are going to be outspending the other billions. Yes.

And that is why we need policymakers to say, do you come to my country, you have to train X amount of people. But the policymakers just seem shackled? There are some that are

and some that are quite forward-leading. So, because of my involvement in Malaysia, for instance, I can say that the least the aspiration and the political will is there.

I was thinking of here. Here, yes, yes. So, well, we have, we have various government commissions saying we need more talent, whether that's on the national security front or economic development, more evenly spread throughout the country.

But of course, yes, the giant sucking sound into Silicon Valley and the East Coast is definitely a formidable force. Yeah. I think there is more hope in terms of re-governing or up-governing in other countries, including some of us in Southeast Asia. Yeah. I want to, you know, there's this inherent apparent structural limitation. I call that energy. Anytime you hear the gods of AI talking about 10xing, 30xing, the preexisting capacities,

they just simply stop short of mentioning the energy requirement. And I think everybody's not going to be able to fulfill the incremental energy requirement, which I think is going to just serve as a structural limitation. in terms of how much AI is going to grow. Yeah. And that, I think, will speak very nicely for utilities companies around the world. Yeah. Well, they're going to feel the pressure very soon to provide greater load.

But where is that load going to come from? I think that's a fair question. I think certain companies like Microsoft, for instance, have recognized that and are now, as you saw in the news, Microsoft just bought a four-mile island and is bringing that on stream, wanting to convert that into safer nuclear. I think part of that is Bill Gates' investments in smaller and safer nuclear. China is building, I think, a nuclear power plant per month. They're doing SMRs, small modulars. Exactly. Alongside coal, of course, as you said. I'm not sure that nuclear or even a hard ramp up on renewables is necessarily going to do the trick. If we continue on

this path. But again, I think the mitigating factors are that even many people in LLMs and in transformers right now are saying, look, we're going to hit a ceiling at some point. These LLMs are not the path to what many aim at, which is artificial general intelligence. It will require different clusters of different technologies coming together, and LLMs are really only one thrust of that. And so there may be a ratcheting back on the energy requirements at some of the point. If that doesn't happen, then yes, energy will become a limiting factor. And that will put a lot of pressure on systems, on inflation for that matter, because it'll become more expensive in people's lives. And again, we're talking systemic fragility. In your book, you talked about,

well, in your lectures also, you talked about the three shifts, right? The shifting from things to insights, west to east. You call that techno-confusionism. And then the third one would have been shifting from, I forget. Shifting from well, west to east. And then things to insights.

It's my book. I should know the answer. Yeah. Let's talk about the two shifts first. So I remember a third one. But, you know, it's interesting how you talked about techno-confusionism. Yeah. Right. And how things are shifting from the West of the East.

Yeah. I think there is a pronounced shift that is hard to swallow for many in the West, or the West-Dash-North, because they're not used to a paradigm where Asia co-innovates and co-leads. But clearly, China has shown that it is playing at the very forefront of some of these emerging technologies. And in short order, might be co-leading. And so that is a paradigm shift and a mindset shift on the part of the many that are then, of course, conflating that innovation power with the power of values, specifically from an in China. I call it techno-confucianism because that particular mix up until this moment, and there is a high degree of volatility right now in China and around Asia, of course. Up until this moment, we have seen a very technology forward economic development paradigm in China that has lifted, what, 6, 700 million people out of poverty, arguably at great cost, of course, when we look at the cultural revolution, 30 million. and people dead, et cetera.

So yes, if you wanted to go there, then it's a question of tradeoffs. But by and large, I think China's population today would say, well, that was a success and it's very technology forward. And they have not yet seen some kind of cataclysm that flows from that technology or the government's control of that technology. And so the experience has been, that's a positive. paradigm. And it's a very pragmatic paradigm in terms of the role of Confucianism, there being a set order and a structure to things, who holds control and who has to be revered and respected for

what reasons. But I think what we meant in the book was that that stands for a pragmatism that is very East or Southeast Asian. And that is, look, whether you call it, you it democracy or whether you call it any other name, whatever the paradigm is, it needs to provide for people. And I'm not saying every government by far in Southeast Asia or East Asia is successful at that, but there are notable examples of where that has been very successful, where really it's the outcome of governance in terms of public goods and the increase of living standards that has been the determinant of success and of satisfaction amongst the population.

Singapore obviously comes to mind as the shining example. Korea, Taiwan are not far behind. We'll have to see whether Vietnam can do it or whether Thailand can do it. He seemed determined Vietnamese. That's right. Yes. And so we'll have to see whether the Vietnamese can be as pragmatic as the Chinese have. All indicators are that they might be.

But there's also still a lot of corruption that I think China has addressed head on and keeps addressing head on. And I think Vietnam is showing indicators that it will as well, or has been as well. But it doesn't quite have the longevity yet. The proofcase has not been as long and sustained. Do you anticipate or foresee a further decoupling in the digital space between China and the U.S.? Oh, absolutely. We're seeing an attempted decoupling. I think there are lots of points of friction around that.

you saw Elon Musk going to Beijing to ask to please take some of that data that his cars are, Tesla's cars are generating in China back to U.S. servers at the same time where we are saying to China, you cannot have U.S. data, you know, U.S. TikTok user data. So that decoupling is painful. When you are economically still very much coupled. We have not seen a decoupling. We have seen a decoupling economically in certain very sensitive technology areas like AI,

like chip technology, compute technology, but the economies are still coupled. They're coupled through longer and more complex supply chains. And so that inhibits efficiencies. It may increase resilience. because you are now no longer beholden to just one place and a direct link.

But certainly efficiency has not increased, has not benefited. So I do see an attempt, but there is that tension of, but we can't really do without each other in the global economy, nor should we, because there are problems like climate change, migration, education, public health, even, even collaboration around natural resources, whether you're thinking about the Arctic or you're thinking about space where we need, we can't. Astro politics.

Exactly. Otherwise, we're back into that Cold War paradigm and that's not going to end well for anybody. You've talked about Southeast Asia, China, Europe, U.S. What's your take on India in the context of the digital revolution? Yeah. So India is stuck at that middle income trap. And we'll see whether Modi or whoever comes after Modi is going to be able to manage India out of that.

India is now the destination of choice for many Western companies, of course, sanctioned by U.S. policy. So we've seen that in semiconductors, for instance. but India does not have a legacy installed base of capacity or of talent and know-how in semiconductors. And so the question is how fast can that really be the alternative to China? It is mainly a services-driven development model. But the proofs in the pudding right now, India is very much also politically a fence sitter, as it were. And we call it that in the book because it, you know, it, it, establishes itself as a partner to the United States on certain fronts, but then also sources

weapons from Russia on other fronts, and I believe energy as well. And so there is a host of countries around the world that will keep doing that. Singapore has done that for ages, right? I have friends who served in the military in Singapore, and they tell me, look, we do exercises with the naval exercises with the Americans and the Chinese, and we also do land-based exercises in Taiwan. And so that's a country like many others. Vietnam obviously is one of those. Cambodia is another one of those that straddle the fence. But it is particularly notewaterctional foreign policy. Multidirectional, sometimes by necessity. I think whether India can hold that is a big question. It is very powerful, large economy. And I think at some point it will not be able to do without U.S. help. I don't. think Russia will help much in terms of getting over that middle income gap into that next growth frontier. And China isn't for obvious rivalry reasons. And Europe is nice to have,

but it isn't going to be the driving force of economic development for China, for India. And so there's really only one left that has a resilient economic engine that, frankly, Europe and others have been depending on over the past couple of years. And so it needs to start looking toward the U.S. more, and that's uncomfortable. Philosophically, which one do you embrace? Open source or a close source? That's a great question and also an uncomfortable one. Generally speaking, I'm in favor of open source as a matter of sparking innovation,

as a matter of diffusion of capital and use. spoke of ideas earlier, the fusion of the creation of ideas. And I think it is always a good thing to have counterpoles to the large platforms. I will say, and maybe an additional point is resilience based on open source, right? Because reliance on just a few global platforms, especially when it comes to AI and its cascading effects, is not. enhancing resilience. And so you want many, many actors. That's the initial idea behind the internet as well, as you know. It was conceived of at DARPA as a means to make its national security communication more resilient. And diffusion and decentralization was an essential part of

that. And so from that angle, I am in favor of open source. I will say that that combination of open source and diffusion while you have currently the dominance of the global platforms that provide models to the open source community, meta being the prominent one, of course, that mix is still very dicey at the moment because we don't have truly open source that comes from the open source community in terms of where the inception is. The inception is really still very much in the platform, and that's the Lama model. But when you have regulation that will tell META to shut down Lama when there is threat of, you know, massive catastrophic effects and everybody else downstream gets shut off as well, then of course you don't have resilience, right? So we need to figure out this balance, this tenuous balance between central and decentralized.

How does that work in the world of, you know, split second AI model decisions? So that's one element that is a critical. And the other one is, you know, do we have regulators who understand how to regulate open source AI? It is, I think Sam Altman was right when he said it's a lot easier to regulate four, five, six, seven large platforms than it is to regulate seven million open source models. And so we need to create new capacity in our regulators to deal with that. I can buy that argument. But it's tougher for me to swallow the not-for-profit versus for-profit, you know, debate. You know, I think shifting from nonprofit to for-profit on whatever platform we were talking about, you know, where Sam is on, just, you know, seems troubling.

I want to take you to a different level where, you know, there's this observation that Silicon Valley was this entrepreneurial experiment, right, on the back of massive support from the government of the U.S., right, on the back of this thing called the Cold War, which the academic institutions in the Bay Area would have been very supportive of, and they help actualize the aspiration. Now, in the absence of a Cold War, how do you think the academic institutions in the Bay Area are going to be able to maintain or help maintain, you know, the technological innovation that we would have seen in the last few decades? At the rate that China just seems to be taken everybody else's lunches, technologically speaking. Yeah. Very hard. We've seen, of course, over the last couple of decades, more and more focused. on R&D by corporations rather than the government relatively in proportion. And you're right to point out that Silicon Valley was very much founded on and still benefits

from U.S. government involvement, whether it's DARPA and the Defense Department or other actors. And I think when I sometimes hear my friends in Silicon Valley talk about the fact that Silicon Valley is so good at what it does because it's far away from Washington, I can't but chuckle because it defies the reality. of today and history. You know, when I look at where CDMA came from or early contracts. It's the government. Yeah, it's the government.

Exactly. And still today, we wouldn't have had CRISPR without years of research at DARPA. And so I think, leaving that aside because it's just not credible, I think the U.S. government has realized arguably under the Biden administration and really even reaching. back to the Obama administration with the brain program, that it needs to get back in the game. Now, I think under the Biden administration, you have seen, of course, and previously under the Trump administration, you've seen, I think, a stronger perceived threat from China. And so looking at the Chinese model became more pronounced in the Trump and in the Biden administrations

than it was under Obama, at least in my view. And so I think that's why you've seen the U.S. government do this 180 on industrial policy as well and on fueling science and technology development so the U.S. can stay ahead. And I think that is a shift that is here to stay. We can have the conversation amongst economists, whether that's a healthy thing. There are many critics of the industrial policy right now, and I see some bad elements of, of it. When we can talk about whether 100% tariff on Chinese vehicles is a smart thing. But I think if you're asking me, as somebody looks at futures and foresight, whether that's going to abate anytime soon, no, it won't. And I do think it will aid Silicon Valley. And I think

that's where your question was headed. And it sort of harks back to the early days of Silicon Valley. But there is definitely a head-to-head competition now with China that is. not going to go away. Or maybe the decoupling between China and the U.S. is going to be the new motivating force or element, right? It's the motivating force. The next phase, yeah. Yeah, and I guess, you know, but is that feasible?

You know, when you're looking at what we're doing with these semiconductors, it's one thing to focus on the most advanced chips so that we, determine the technological playing field on a on a 15, 20 year horizon. It's another thing to expect that to prevent U.S. chips from being found in Chinese fighter jets. A lot of the technology that you need for those kinds of weapons is not two or three generations out. its actual commercially available technology today. And so, yes, I think the paranoia and the system competition that we see that's in our heads is driving that industrial policy and is driving those monies to flow, whether that's actually

going to lead to a real decoupling today or tomorrow, I doubt. You've alluded to, you know, a number of times to the fact that, you know as much as data is there only 20% is structured and only 0.5% is analyzed that was shocking to me yeah i would have thought the percentages would have been much higher for each and they may be higher today you know we wrote the book two years ago uh uh it may be higher today um but data is uh is the key fuel of what we have called that cognitive economy right and And remember, cognitive economy means command and control based on data across different pillars in society. So, you know, corporate operations is one pillar.

Infrastructure is another. Ecological sustainability is another. Our biology, our psychology, our two more pillars. And technology now, cognitive technology enables us to exercise command and control across these based on insights that we have across these. But none of that works without data. And so I sometimes say we need to not have such an exclusive focus on the models and rather look at data as a topic. And so whether that is the fact that, you know, there is still too much noise in the data we create, or whether we look at bias in data or the fact that data rots and degrades over time.

And certainly how we treat data ownership. And that we're not really cutting people into business models enough. And when I say people, I mean, the creators of data that are rightly saying, hey, you're doing many more things with my data than I paid for or I thought I was paying for, or that you are paying me for, I should say, with your services, right? You're selling that data to second and third order parties. And I don't see any of that revenue. All of those questions are data-centric.

questions and they're heavy questions and there is valid views pro and con on all of these questions but we need to have dialogues on data and not get so hung up on their shining new thing you know which is these humanoid AIs that we often depict. Put this in the context of the comparison between China and the rest of the world and in their respective treatment to data and if you've alluded to the fact that China doesn't allow companies to transact or trade data, right? And you've also made reference to, you know, China being wobbly on the economy,

the U.S. being wobbly on the politics. Right. And take us to how data is going to play a role. Yeah. So the reason for why the U.S. economy, one of the reasons, many reasons, why the U.S. economy is so resilient, leaving aside the fact that the Fed has done a good job,

is because of the free flow of information and the reasonably free flow of data, especially on the enterprise side with some safeguards, but not too many. So the U.S. leads on flow of data and corporate data, enterprise data. China leads on the flow of consumer data, consumer application data, based on its own legacy of social media. The difference between those two is not just the different buckets of data, but it's also how both countries treat the trading of data. So in the United States, you can sell data.

So Facebook's collaboration with Cambridge Analytica, I'm told by lawyer of friends of mine was perfectly legal. It's not legal in China. you can share data within the same stovepiped organization, vertically integrated organization, or even horizontally integrated organization, as long as it's one corporation. So the fact that WeChat uses user data across different business areas within its own corporation, that's very legal, but it couldn't trade data with other hyperscaler platforms across the Chinese economy. So that's illegal.

It's not illegal in the United States, right? So the domains are different, and the data sharing paradigms are different as well, but both generate enormous amounts of data. Now, Asia overall, and certainly with China at the center, is leading on data growth. It generates more growth than any other region. But the U.S., because it started earlier, is still very much at the intersection of of and a hub for global data flows across borders. Its platforms are far ahead of the Chinese platforms

when it comes to unique users because it started earlier and it rolled out internationally earlier. The Chinese model does not work for as many countries around the world and it is not as established as the U.S. model so there is a time disadvantage. So the U.S. still leads on global data. The question is, who is going to be first?

in defining what that future global data economy will look like. Will it be that U.S. model of discretionary data trading across organizational boundaries and across international borders, which is very laissez-faire? Or will it be a more controlled data trading paradigm that is the norm in China, where governments will determine whether that's allowable or not? not. Currently, we're seeing evidence that Asia is a little head when it comes to intergovernmental agreements on data trading and the digital economy at large. For instance, through the DEPA, the Digital Economy Partnership Agreement, that Japan, I think, is part of the

Philippines, small places like Guamah, part of this. I believe China wants to join. I think Singapore is in it. And there, I think it's the first international sort of agglomeration of national government saying, yes, we want to trade data and digital goods, but we got to figure out how, what's acceptable. That has not yet happened widely, as far as I know, amongst the existing Western regime, whether you call it OECD or whether you call it G7, Western Dominator. regime anyway. And so that's where I see the future headed. What shape will that digital economy, that partnership, that data economy take? And who will make the rules for that?

Now I remember the third shift. Surveying to surveilling. That's right. Surveying to surveilling. Because you thought so much about this data. Surveying to surveilling. So, you know, we're so used to getting surveys from companies. getting polls. I mean, right now, I don't know about you, but as a U.S. citizen, I'm getting drowned and people trying to poll to figure out how I'm going to vote. And so that's all surveying. And we've done that for ages. We've also done surveillance, but that's been the domain of government, government, and it is in China still, right? And it is in some Western countries as well. But that used to be a government domain. Now we're seeing the confluence of both in private corporations

around the world, but especially here in the United States. We've come to what Shoshana Zubov has called surveillance capitalism, right? Which is essentially me observing your life pattern, and then figuring out what do I do with that? Who wants to know about that? How do I create value with that. So when Gita gets up in the morning, I know what I need to sell Gita next. And that sounds positive, and it is in large measure positive. You know, we've always wanted to be better understood by the corporations that serve us. But we've never were clear as to what that actually means when somebody really, really knows us. So when people really get to know the psychometric profile of Gita and frankly, a lot of things that you might rather keep private. And so where do we draw the

line and what say do we get in how the line is drawn? And that's one of those coming battlegrounds for corporations on the governance and policy front and globally, really. We need to agree on this globally because data flows across borders as we discussed. You know, there's this tendency for the young generation to be communicating just amongst themselves, right? Most of the 8 billion people on the planet, as a result of which they're not communicating with their predecessors, which would amount to about 107 billion people, the number of people. As a result of which, you know, a lot of people suffer from what I call historical amnesia and the decline of cognitive immunity.

Yeah. And you see rising cases of depression, anxiety, all that amongst the young generation. Yeah. And Jonathan Hayt, you know, talks about this length, right? And it all boils down to data, right? How do we remedy ourselves in this trend that's troubling? Yeah. It's something that's hitting us on many levels.

I have clients, full-minded strategy engagements that have said it's apparent even within these organizations when the older generation that has all the embodied knowledge and you could call it wisdom, right, the ability to make judgment calls, sound judgment calls, when they are close to retirement, but they're not talking to the younger folks because the older folks talk over the water cooler and the proverbial cafeteria and the young folks talk on social media and they just don't meet. And so they, and you can do this when you're a corporation more easily than when you're a government.

They have instituted programs where they incentivize the buddying up of old and young, as it were. And it's worked where they literally incentivize this with a promise of career advancement. and positive reviews and bonuses and things like that. So that works in a corporate context. We need something analogous in the public context because it is true we are seeing, I think a true hunger on the part of the younger generation

that I'm encountering anyway and gratitude when it happens, when mentoring happens, when coaching happens, when they can talk to somebody who has got two or three decades more under their belts, as it were, than they have, to talk to them about what's what, what to fret about and what to leave aside. And it's never easy because there is some rightful criticisms that they have of us, as it were, but they're also in need of that shafing and in need of that sharing of perspectives. And you're right. We are parsed into bubbles in multiple different ways.

this isn't just about red and blue in America. This is also along age lines, and this is along cultural lines and education lines. And we have not done a good job using technology to drive more convergence, right? Just because we can talk to each other, we can communicate. It doesn't mean we're converging or we're actually getting together. It means we are actually getting tighter in bubbles. And those, you know, social media, bubbles on TikTok or Instagram are very pronounced.

And so we do have to break through that. And that's where we need, again, why is policymaking? And I don't think we have that yet. It's concerning. And I want to take you to the next, which, you know, topic which you've been talking quite a bit. How do you actually marry or wet, the nose? of, you know, Industrial Revolution 4.0 with Society 5.0. Yeah. It needs to be married. And I think there are some countries that have started to

understand that quite well. The Japanese coined that Society 5.0 term because I think they have it right. They're seeing a, they're seeing digital technologies essentially taking apart and rejiggering our social fabric. And some of the has to do with skill base, right? Pure skill base. If you don't have AI skills, you're not, I mean, at least under the current hype paradigm here on the West Coast, you're not really tech skilled anymore. Now imagine if you're not even tech skilled and you're hearing while you forget learning any number of apps. Now, if you don't have AI, you're not going to get the next job, right? So there is there is, there is

that on a pure skill base, there's a separation from what does it mean to be well educated, okay? That's one thing. And what does it mean to be AI educated and AI trained? And so, again, the cutting edge running away with the rest of professional development, career advancement, which is personal growth and its economic growth. And then, of course, the bubbles we already talked about. That's another way of this aggregating society.

age is another one. We need to do much better at ensuring that we have digital applications and user interfaces that speak to older generations. And quite frankly, given how upside down population pyramids are around the world, in many places, bar some African and Asian countries, there's a lot of money to be made from addressing older populations, right? but we are sort of caught up in this youth craze right now where even some of my students who are 32 years old feel they're old compared to the 23-year-olds their meeting in Silicon Valley and much less us exactly much less much less us well there's always the the gray hair as a professor right that that sort of enhances the brand anyway but but yes absolutely and so and then of course the income gap that we discussed earlier between the digitally high-sacized

skilled and the not digitally high skilled. And I say it that way because we always talked about, you know, high, medium, and low skilled. But frankly, we are now drifting into an era where it's high skill or low skilled. And think about that. You have a bachelor's degree. You have a master's degree of some sort. But you just don't have the AI and data skills. And all of a sudden, you feel like that rift between you and that avant-garde is widening even further, right? we have to watch that as it is in the United States and elsewhere we have widening income gaps. And who is to blame people when at some point they feel so left behind, they're working two or three jobs, can't provide for their families, have no educational perspectives for their children. Who is to blame them at some point when they start throwing Molotov cocktails, right?

We have left droves of people behind in that globalization 1.0 paradigm. And we need to recognize and acknowledge that rather than saying, how can we just, put a band-aid over it and get people to just accept that this whole trade liberalization paradigm, which I stand for, and I'm certainly advocating in some shape or form, we can't just bring that bag from the dead. We have to actually think about a complete overhaul. And so that's the chance we have with the Fourth Industrial Revolution or Society 5.0, as it were. Let's hope the powers to be can actually make that happen. But I just don't think

the millions, if not hundreds and millions of people out there are going to be able to catch up upskilling or reskilling fast enough. Well, you'd be surprised sometimes, right, when you let the young generation in particular loose on digital technology, how fast they learn. Yeah. And we have precedent, right?

We've seen what happened with M-Pesa, for instance, in Africa. Oh, yeah. And the ascent of mobile. And I do believe that there is massive amounts of digital talent, not just across Southeast Asia, but Africa, for instance. We're seeing this, frankly, also with crypto. And so I think there's hope for the young generations. I think it's the older generations that I'm worried about. I'm worried about those.

That's what I was talking about. I've seen them in some countries where they're just not capable of catching. up on a timely basis. And then to boot, they're also between the front lines, right? Especially, I mean, certainly in Southeast Asia, some places we talked about them already. But in Africa, right, the risk of digital colonialism, as Kai Fuli called it, is not to be underestimated. Absolutely.

Between the United States and China and Africa, I think this is where the European voice could really help. But it's got no credibility because what young Africans are looking for is growth and development and, you know, getting to the next level. And I'm not sure that the European model is very promising in that regard, right? So hence the two fronts, you know, fighting over Africa. Oliver, we've talked over an hour and a half. I want to post to you the last question.

If there's one or two things that the Southeast Asians must do in order to be able to remobilize themselves in the context of all the six Cs that we've talked. talked about at length. What would it be? Yeah. So number one, public education. And this goes for almost any good public education, but specifically focused on the intersections of AI and data and other fields. And here, I mean talking about AI and data in the context of the humanities, the natural sciences, not just AI and data for AI and data itself and for compute power itself, right? We can do that in any number of institutions around the world that are very elite. We need a broad swath of people that are application focused.

And they can say, look, I can put these technologies to use in these different areas around society in a way that is respectful of who human beings are in their entirety. So educating the population on AI and humanities, AI and anthropology, AI and philosophy, AI and ecology is very important. And so education, education, education in universities, but also broadly for the public, finding ways to incentivize corporations to help with training on those intersections, right? and not just with education for the next generation of programmers who may or may not be what's going to be demanded going forward. What's the risk of not studying philosophy and or anthropology? That you don't understand humans. I mean, we hear this even from some of our students here at our elite institutions like Berkeley and Stanford that are insanely highly qualified.

I mean, some of the talent there is unbelievably smart. but even they are saying, look, we understand models and software and code, okay? But what we often don't understand is humans. Humans are, I mean, let's understand. Humans are complex. We are often non-linear, irrational. We're beautiful in our complex makeup and very emotional. We get political and bureaucratic and so on and so forth.

You know, we're not easily predictable, although increasingly so. but we need to dedicate more time to the computer science folks, understanding humans and those who are not mathematically scientifically inclined, understanding data and AI, that doesn't mean you need to become a programmer, but at least sort of putting yourself through a course or two, understanding how it works, how it's shaped, what the pitfalls are, what the value and the promise is,

so that we get an educated public, maybe not everybody, but broad swathes of the population, that can help shape this thing. And so I think we're seeing some corporations starting to invest in those countries, but we need abroad. And, you know, this goes for every country. We're not doing the greatest job here, although we have a very computer science literate population, generally speaking, and very pro-technology. China does as well. Europe less so.

I'm worried about that. And we need this to happen in the next tier of development. Thank you so much for your time. It's my pleasure. Always is to talk to you. That was all of growth from Cambrian Futures, UC Berkeley, and UT Malaysia. Thank you. This is end game.