Joe: Alright Lewis, pop quiz. In 2017, for every single dollar spent on mobile payments here in the United States, how much do you think was spent in China? Give me a number. Lewis: Oh, wow. Okay, I know they're ahead of us on that. I'll say... a respectable ten dollars. Maybe fifteen? Joe: Not even close. The answer is fifty. Fifty dollars for every one of ours. A fifty-to-one ratio. Lewis: Fifty? That's not a gap, that's a different dimension. How is that even possible? Joe: That staggering reality is at the heart of the book we're diving into today, AI Superpowers: China, Silicon Valley, and the New World Order by Kai-Fu Lee. And that gap isn't just about convenience; Lee argues it's the secret fuel for the next world order. Lewis: And Kai-Fu Lee is the perfect person to write this. He’s not just some academic in an ivory tower; this is a guy who was the president of Google China, who founded Microsoft Research Asia, who worked at Apple. He has seen both of these tech empires from the absolute inside. Joe: Exactly. He’s a true insider. And he argues this whole AI race, this new cold war of technology, kicked into high gear because of one incredibly dramatic event. A moment he calls China's "Sputnik Moment."

Lewis: A Sputnik Moment. I like that. It’s that feeling of suddenly realizing you’re behind. What was it for China? It wasn't a satellite, I'm guessing. Joe: No, it was a board game. But this was no ordinary game. In May 2017, the world’s number one player of Go, a 19-year-old Chinese prodigy named Ke Jie, sat down to play against an AI. Google's AlphaGo. Lewis: I remember this! Go is famously complex, right? More possible moves than atoms in the universe, or something insane like that. Joe: Precisely. It was considered the pinnacle of human strategic intuition. And Ke Jie was the best of the best. He was confident, a little cocky even. He had studied AlphaGo’s previous matches and thought he’d found a weakness. He was going to defend humanity's honor. Lewis: A 19-year-old kid carrying the weight of 4,000 years of human strategy on his shoulders. No pressure. Joe: None at all. And for the first hour, it looked like he might do it. He was playing brilliantly. But then, AlphaGo started making moves that were just… alien. They seemed wrong, illogical, but they slowly and systematically dismantled Ke Jie’s entire strategy. The book describes how, deep into the match, Ke Jie got up from the board, went to a corner of the room, and just started to weep. Lewis: Wow. He actually cried during the match? That's heartbreaking. That’s not just losing a game; that’s an existential crisis playing out in real time. Joe: It was. He returned to the board, but he was broken. He lost all three games. And that image of their crying hero, the best human mind defeated by a machine, was broadcast all over China. It was a profound national shock. It was the moment the Chinese government, tech industry, and public realized that AI wasn't just science fiction anymore. It was real, and the West was winning. Lewis: But how did one board game match translate into a national AI strategy? That seems like a huge leap. Joe: Because it created the political will. Just two months later, China's State Council released an ambitious plan to become the world leader in AI by 2030, pouring billions into research and development. But Lee’s crucial point is that the government was just lighting a match. The kindling was already there, in the form of China’s unique entrepreneurial culture. Lewis: This is where the whole "copycat" stereotype comes in, right? The idea that for years, Chinese tech was just cloning Silicon Valley. Joe: It started that way, for sure. Lee tells the incredible story of an entrepreneur named Wang Xing. In the 2000s, he was known as "The Cloner." He copied Friendster, then Facebook, then Twitter. But his most famous clone was of Groupon. Lewis: Ah, Groupon. The land of half-off brunches. Joe: Exactly. When Groupon was the hottest thing in the US, Wang Xing launched his version, Meituan. But so did five thousand other Chinese companies. It was dubbed the "War of a Thousand Groupons." It was a bloodbath. Companies were slashing prices, running smear campaigns, even reporting rival CEOs to the police. It was absolute chaos. Lewis: That sounds absolutely insane. It's like the Wild West, but for tech startups. How did anyone survive that? Joe: By being a gladiator. Wang Xing’s Meituan didn't just survive; it conquered. He wasn't the best cloner; he was the best fighter. He optimized every tiny detail, managed his cash flow ruthlessly, and built an army of salespeople on the ground. He got his hands dirty. Lee has this amazing quote about him: "Wang Xing didn’t succeed because he’d been a copycat. He triumphed because he’d become a gladiator." Lewis: I love that. So the stereotype of Chinese tech as just 'copycats' is totally wrong. It sounds more like they learned the rules of the game and then started playing it harder, faster, and with sharper elbows than anyone in Silicon Valley was prepared for. Joe: That's the perfect way to put it. This gladiator environment forged an entire generation of entrepreneurs who are incredibly fast, pragmatic, and market-driven. They don't have the luxury of a lofty mission statement; their mission is to survive. And that culture was the perfect engine to take on the age of AI.

Joe: And that gladiator spirit built something Silicon Valley didn't see coming: a completely alternate internet universe. This is where that 50-to-1 mobile payment gap we started with comes from. Lewis: Okay, so explain this alternate universe. What makes it so different? Joe: Lee argues that around 2013, China's internet took a sharp right turn. While the US internet was built around the desktop computer, most Chinese citizens came online for the first time on a smartphone. The internet for them was never about sitting at a desk; it was about navigating life in a crowded, chaotic city. Lewis: That makes sense. It’s a tool for the real world from day one. Joe: Exactly. And this led to the rise of O2O, or Online-to-Offline services. Chinese entrepreneurs weren't just building websites; they were building services that connected the digital world to the physical one. Think food delivery on a massive scale, on-demand manicures, and of course, millions of shared bikes you can unlock with your phone and leave anywhere. Lewis: So it’s like a thousand Ubers, but for everything. Joe: And tying it all together is the super-app, WeChat. Lee calls it a "digital Swiss Army knife for modern life." In the US, we have a constellation of different apps—one for messaging, one for payments, one for social media. In China, you can do all of that and more—book a doctor's appointment, pay your utility bills, order a taxi—all without ever leaving WeChat. Lewis: Okay, so in the US, our online life is mostly about what we click on—likes, searches, articles. It's behavioral data. But you're saying in China, the internet is tracking what you do in the physical world—where you go, what you buy, how you travel. It’s a much, much richer dataset. Joe: That is the core of China's superpower. In the age of AI, data is the new oil. And China is the new Saudi Arabia. Deep learning algorithms are only as good as the data you feed them. And Chinese companies are collecting oceans of real-world data that American companies can only dream of. Lewis: Can you give me an example of how they built this? How did they get hundreds of millions of people to trust an app with their bank account? Joe: Through a stroke of absolute genius. For years, Alibaba's Alipay dominated digital payments. Tencent's WeChat wanted in. So, during Chinese New Year in 2014, they launched a feature based on the tradition of giving "red envelopes" filled with cash. Lewis: Right, the little red packets of money. Joe: WeChat digitized it. You could send digital red envelopes to your friends and family. To do it, you had to link your bank account. It was gamified, fun, and culturally resonant. In one holiday season, millions of people linked their bank accounts. Jack Ma, the founder of Alibaba, reportedly called it a "Pearl Harbor attack" on his company. Lewis: That's brilliant. They used a cultural tradition to solve a massive business problem and, in the process, laid the final piece of the puzzle for this data-rich universe. And all that activity creates the 'oil' for AI that Lee talks about. Joe: Precisely. They built a physically-grounded internet that sees what you eat, where you go, and what you buy. And that gives their AI algorithms eyes and ears in the real world.

Joe: And with all that oil, all that data, Lee predicts AI will create trillions of dollars in wealth. But right after painting this picture of incredible innovation, he delivers a chilling warning. The real AI crisis isn't Skynet or robot overlords. It's much more immediate: mass job displacement and staggering inequality. Lewis: This is where the book takes a dark turn. He predicts that AI could technically replace 40 to 50 percent of jobs in the next fifteen years. That's a terrifying number. Joe: It is. And he argues it will hit everyone. Blue-collar jobs like truck drivers and factory workers, but also white-collar jobs: accountants, radiologists, loan officers, paralegals. Any job that is fundamentally about optimizing based on a large set of data is at risk. This could create what he calls a new "useless class" and lead to genuine social collapse. Lewis: And this is where the book gets really intense and, as some reviews have pointed out, quite controversial. He dismisses popular solutions like Universal Basic Income. So what's his grand solution? It can't just be 'learn to code.' Joe: It's not. And to explain it, he gets deeply personal. The book pivots from geopolitics and technology to his own life-and-death struggle. In 2013, at the peak of his career, Kai-Fu Lee was diagnosed with stage IV lymphoma. He was given just months to live. Lewis: Wow. I had no idea. That changes everything. Joe: It changed everything for him. He describes himself as a workaholic who had spent his life optimizing for impact, even admitting he probably would have chosen a big meeting over being present for the birth of his first child. He thought like a machine. But facing death, he realized the things that gave his life meaning weren't his achievements or his influence. It was the love from his family, the time spent with them. Lewis: The things a machine can't quantify. Joe: Exactly. And that epiphany, which he calls "The Wisdom of Cancer," forms the basis for his blueprint for the future. He argues that if AI is going to handle the routine, optimization-based tasks, then humanity must double down on what AI can never do. Lewis: Which is what? Creativity? Joe: Even deeper. Love. Compassion. Human connection. He proposes a new social contract, a "social investment stipend." The idea is that the massive wealth generated by AI should be used to pay people for work that revolves around care, community, and education. Lewis: Hold on. So he’s suggesting the government would pay people to be... good community members? To care for the elderly? To mentor children? Joe: Essentially, yes. To create a new economy based on human-to-human service and compassion. He argues these jobs are desperately needed, create immense social value, and are precisely the things AI will never be able to replicate authentically. It's a call to shift our definition of "value" from pure economic output to human-centric contribution. Lewis: I can see why some readers find that part both beautiful and deeply unsettling. On one hand, it's a powerful call to re-value what makes us human in the face of these cold, calculating algorithms. On the other, a government-funded system for 'love and compassion' raises a million questions about implementation and control. Joe: It's definitely polarizing. But what I love is that he doesn't offer an easy answer. He forces you to confront the problem on a much deeper level. He’s saying the solution to a technological crisis might have to be a spiritual one.

Joe: And that's the book's final, powerful argument. The AI race starts with technology and competition, it's fueled by data and gladiator entrepreneurs, but the finish line has to be about redefining human purpose. We can't out-optimize the machines, so we have to double down on what they can't do: care, create, and connect with each other. Lewis: It really leaves you with a huge, and frankly, uncomfortable question: If your job—the thing that gives you structure and maybe even identity—could be done better by an algorithm, what would you do that gives your life meaning? It’s a question we’re all going to have to answer, and probably sooner than we think. Joe: It's a profound thought. And it's not just for individuals, but for society. What do we choose to value? We'd love to hear what our listeners think. What are the uniquely human jobs of the future? What kind of work will always need a human heart? Find us on our socials and share your ideas. Lewis: This is Aibrary, signing off.