Most AI policy conversations still orbit around Washington and Brussels, but Asia-Pacific is already writing a very different rulebook. In this episode, I talk with George Chen, Digital Partner at The Asia Group and former Meta policy executive, about how AI is actually being governed, built, and deployed across APAC, China, and the global south. George traces his own path from journalism to big tech to advisory work, and uses that vantage point to explain why APAC is not “one market”—and why the EU analogy breaks down almost immediately. Countries like Japan, Korea, Singapore, and China are leaning into AI as a tool for economic recovery and industrial upgrading, often taking a much more pro-innovation, pro-growth stance than the EU’s more precautionary approach. At the same time, Southeast Asia is becoming the physical backbone of the AI build-out: Singapore as HQ and regulatory hub, with Malaysia, Indonesia, Thailand, and the Philippines hosting the data centers, power, and connectivity—along with all the local tensions that come with that. We also get into what “responsible AI” actually looks like inside a company. Beyond the buzzwords, George breaks it down to three pillars—security, safety, and privacy—and talks through how mature players like Microsoft or Meta build these into product design from day one, versus the reality for startups trying to ship fast with one lawyer and a single policy person supporting multiple markets. He also makes the case that fragmented regulation and the lack of international standards are becoming a real tax on innovation, especially outside the US and EU. Another big thread is the emerging US–China competition over AI governance itself. It’s no longer just about who has the best models or chips; it’s also about who exports their rules, norms, and defaults to the rest of the world. The US is pushing an “America-first” innovation and safety model to allies, while China is pitching AI as a kind of public good to the global south—combined with a more cost-efficient, top-down deployment model and very strict cyber and real-name rules at home. George argues this divergence is already shaping how content, deepfakes, and AI-generated media are treated in different jurisdictions. We talk about the local edge of Chinese models—why in places like Beijing, models such as DeepSeek can be more useful than ChatGPT or Gemini for everyday queries because they’re trained on more localized, timely data. From there, we zoom out into the new AI talent map: countries like Indonesia, Vietnam, Kazakhstan, and Uzbekistan trying to position themselves as low-cost AI talent hubs and “back offices” for global AI companies as coding gives way to prompting and applied ML. We close on a more philosophical note: should AI be built as a subordinate assistant or a true partner? George shares his uncertainty here, and we talk about what happens when we give AI more agency, emotional intelligence, and continuous workloads. At some point, the conversation shifts from safety checklists to ethics, culture, and even “digital colonialism”: whose values, whose norms, and whose worldview are encoded into the systems that end up mediating how we see the world. In today’s world, there’s no shortage of information. Knowledge is abundant, perspectives are everywhere. But true insight doesn’t come from access alone—it comes from differentiated understanding. It’s the ability to piece together scattered signals, cut through the noise and clutter, and form a clear, original perspective on a situation, a trend, a business, or a person. That’s what makes understanding powerful. Every episode, I bring in a guest with a unique point of view on a critical matter, phenomenon, or business trend—someone who can help us see things differently. For more information on the podcast series, see here. AI-generated transcript. Grace Shao (00:00) Hey George, thank you so much for joining us today. I’ve been really excited and waiting for this chat. You know, you are a very busy man. You’re constantly traveling. I can barely reach you in Hong Kong. So really appreciate your time today. Sit down with me and share your insights with my followers and some of our listeners. To start with, you’ve worn many, many hats. A journalist, tech executive, policy advisor, and now a partner at the Asia Group where you advise a lot of force, you’re probably helping companies on, I believe, geopolitical positioning, right? George Chen (00:29) Thank you. First of all, thanks for the invite. It’s quite an honor to join a growing cohort of guests for your program. Really happy to have a discussion about tech and policy issues because I think you’re right. My first 10 years in media, similar to your background, and most recent decade, I work very much on the intersection between technology and policy. My biggest takeaway from my last job at Meta, one of the platform operators in the world, is sometimes we very much focus on technology development, like the breakthrough, while the resources for policy support are actually quite limited, especially in the Asia-Pacific region compared with the US. think for all the... Big tech in the US, given the politics domestically, they have to do a lot on political and policy part. But for Asia Pacific, the policy work, compared with other investments, like in data center, technology, hiring of engineers, it’s still very, very, very understaffed, under-resourced, and sometimes under-appreciated. This is why we need to... address some concerns about policy issues as we advance the technological part. Because I always tell my students, tell my friends, tell my partners that the key challenge, even you have CharGBT 5.0 or 6.0, the key challenge is how to get the government to understand new technologies and also get the users to have more trust in those new technologies. Otherwise, nobody use it, nobody trust those things. And that makes them. Grace Shao (02:15) I think that’s super helpful. A lot of times when we think about policy or safety issues, we think about it as like a siloed part of the ecosystem. But really like exactly to your point, like, you know, we need the developers to understand the concerns of the users. We need the users to understand the safety risks of the products. We need the regulators to understand what it means to implement these like technology throughout our economy, right? So there’s it’s like, it’s actually all interrelated. I think today to start off with, let’s like go into big tech, just give in your background with Metta, working with a lot of these big tech companies. You’re based in Hong Kong for the listeners, but actually work predominantly for American big tech companies. What is like the, I guess, the fundamental feel right now as we see the evolution be from a social media company for AI to AI of focused company as this is now the forefront of their strategy. George Chen (03:11) Right, so for the Asia-Pacific region, it’s big. I always try to explain to my clients and friends, when people talk about Asia-Pacific, the first gross perception, perhaps from Western perspective, is, okay, treat Asia-Pacific like the EU, right? But EU is a single market. They have very much shared the language, English, also one currency and they have the European Parliament to pass legislation for EU member countries. Asia-Pacific is far diverse, far different, and much bigger. So it’s hard to just copy whatever works in EU and then let’s also do it in APAC. Using AI regulations as a clear and classic example, you know, you is the first You know government, you know to have the world’s first AI act, right? But the so-called the Brussels effect didn’t really happen this time in Asia Pacific countries You didn’t see like all the countries, you know, like Singapore or you know Japan to quickly follow up on You know to have a similar like a risk-based approach or penalty focused approach to AI, right? Instead, you know if you look at Japan. They are very much welcoming. Japan declared to be, they want to be the most friendly open country for AI developments. The first data exception for AI testing was actually in Japan. And then Singapore followed, and Hong Kong’s also not considering, right? So APAC took a very different regulatory approach to AI versus EU. I think this is something all the American tech companies have to realize. It’s not like America leads technology and then EU matters because of the special relationship between US and EU. So as I mentioned at the beginning, the resources for public policy work are very limited in AIPAC, but EU still enjoy a lot of resources, this English-speaking market that has lot of political connections. And then Asia-Pacific, when it comes to policy enforcement, like policy support it feels more like a third country, overall speaking Asia-Pacific as a whole. So there’s still a lot of educational process, the learning curve for big tech, largely from the US to understand what are the challenges, what are the opportunities in the Asia-Pacific market. However, I also need to highlight for many big platforms, Asia-Pacific is actually not just the largest market by internet users for American tech companies, for almost for all of them, right? You know, in terms of user base. It is also a very important revenue source, know, the source of revenue for those American companies. So now you see the imbalance, right? You you make a lot of money from Asia-Pacific, but the support you give to Asia-Pacific is quite limited, know, compared to in the US ⁓ and EU. So the learning curve is there. American tech companies want to have a more sustainable development and want to have a more constructive relationship, sort of a more constructive partnership with Asian governments. I think there’s still a lot of work to do. Grace Shao (06:31) I think that’s really helpful to help
