In March 2024, I opened Facebook and saw Jensen Huang's face. The Nvidia CEO was offering investment advice, speaking directly to me in Mandarin. Of course, it was not really Huang. It was an AI-generated scam, and I was far from the first to be targeted: across Taiwan, a flood of scams was defrauding millions of citizens.

We faced a dilemma. Taiwan has the freest internet in Asia; any content regulation is unacceptable. Yet AI was being used to weaponize that freedom against the citizenry.

Our response — and its success — demonstrates something fundamental about how AI alignment must work. We did not ask experts to solve it. We did not let a handful of researchers decide what counted as “fraud.” Instead, we sent 200,000 random text messages asking citizens: what should we do together?

Four hundred forty-seven everyday Taiwanese — mirroring our entire population by age, education, region, occupation — deliberated in groups of 10. They were not seeking perfect agreement but uncommon ground — ideas that people with different views could still find reasonable. Within months, we had unanimous parliamentary support for new laws. By 2025, the scam ads were gone.

This is what I call [...]

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Outline:

(01:44) AI Alignment Today Is Fundamentally Flawed

(03:45) The Stakes Are High

(07:42) Attentiveness in Practice

(09:21) Industry Norms

(10:36) Market Design

(11:59) Community-Scale Assistants

(13:10) From 1% pilots to 99% adoption

(14:24) Attentiveness Works

(16:44) Discussion about this post

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Adam Khoja is a co-author of the recent study, “A Definition of AGI.” The opinions expressed in this article are his own and do not necessarily represent those of the study's other authors.

Laura Hiscott is a core contributor at

‍Dan Hendrycks, lead author of “A Definition of AGI,” provided substantial input throughout this article's drafting.

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In a recent interview on the “Dwarkesh Podcast,” OpenAI co-founder Andrej Karpathy claimed that artificial general intelligence (AGI) is around a decade away, expressing doubt about “over-predictions in the industry.” Coming amid growing discussion of an “AI bubble,” Karpathy's comment throws cold water on some of the more bullish predictions from leading tech figures. Yet those figures don’t seem to be reconsidering their positions. Following Anthropic CEO Dario Amodei's prediction last year that we might have “a country of geniuses [...]

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Outline:

(03:50) Missing Capabilities and the Path to Solving Them

(05:13) Visual Processing

(07:38) On-the-Spot Reasoning

(10:15) Auditory Processing

(11:09) Speed

(12:04) Working Memory

(13:16) Long-Term Memory Retrieval (Hallucinations)

(14:24) Long-Term Memory Storage (Continual Learning)

(16:36) Conclusion

(18:47) Discussion about this post

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This is an excerpt from the authors’ new book, “Rewiring Democracy: How AI Will Transform Our Politics, Government, and Citizenship,” available for preorder now.

‍Imagine a digital proxy that knows your political preferences as well as you do (or better), tracks every issue on the ballot, and casts votes on your behalf in real time. This vision, once the stuff of science fiction, is quickly becoming technically feasible. Allowing AI to serve as our political proxies sounds radical, but the idea builds on a simple truth about our political system: representative democracy exists because we can’t all be in the room for every decision.

The Limits of Representation

Representative democracy requires elected officials to stand in for the collective preferences of their constituents. The most understandable reason for this is logistical: citizens don’t all have the time or ability to communicate our preferences directly, and we can’t all fit [...]

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Outline:

(00:51) The Limits of Representation

(03:44) AI Could Power a More Direct Democracy

(07:22) Extending Rights to the Disenfranchised

(09:07) Protecting the Integrity of AI-Powered Democracy

(10:30) Good AI Representation Could Make Government More Equitable

(13:36) The Risks of Overrelying on AI Representatives

(15:07) AI Proxies Should Enhance Political Engagement

(17:05) Discussion about this post

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This summer, the World AI Conference (WAIC) in Shanghai began to live up to its name. Previously an almost exclusively domestic event, this year's event attracted a larger group of international visitors to witness the would-be marvels of China's AI ecosystem. It also provided an opportunity to engage foreign counterparts for one of the newest elements of that ecosystem: the China AI Safety and Development Association (CnAISDA).

Launched in February 2025 on the sidelines of the Paris AI Action Summit, CnAISDA places China among a small number of jurisdictions with dedicated AI safety institutes, or AISIs — although they increasingly go by other names. AISIs are government-backed institutions with a focus on AI risks, sometimes explicitly including catastrophic risk. Given the otherwise zygotic state of efforts to address potential catastrophic risks of frontier AI systems in China, CnAISDA is potentially a kernel of important things to come.

But [...]

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Outline:

(01:20) International Convergence?

(04:00) An All-Star Team, with Limited Resources

(07:07) China's Efforts to Lead on AI Diplomacy

(11:04) The Road Ahead

(12:44) Discussion about this post

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Earlier this year, Dan Hendrycks, Eric Schmidt, and Alexandr Wang released “Superintelligence Strategy”, a paper addressing the national security implications of states racing to develop artificial superintelligence (ASI) — AI systems that vastly exceed human capabilities across nearly all cognitive tasks. The paper argued that no superpower would remain passive while a rival transformed an AI lead into an insurmountable geopolitical advantage. Instead, capable nations would likely threaten to preemptively sabotage any AI projects they perceived as imminent threats to their survival. But with the right set of stabilizing measures, this impulse toward sabotage could be redirected into a deterrence framework called Mutual Assured AI Malfunction (MAIM).

Since its publication, “Superintelligence Strategy” has sparked extended debate. This essay will respond to several critiques of MAIM, while also providing context to readers who are new to the discussion. First, we’ll argue that creating ASI incentivizes state conflict and the tremendous [...]

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Outline:

(01:30) Building Superintelligence Amplifies Tensions, and Could Be Considered an Act of War

(10:05) MAIM's Proposals Increase Stability

(16:52) MAIM Facilitates Redlines

(20:28) Our Best Option

(21:02) Discussion about this post

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‍Two years ago, AI systems were still fumbling at basic reasoning. Today, they’re drafting legal briefs, solving advanced math problems, and diagnosing medical conditions at expert level. At this dizzying pace, it's difficult to imagine what the technology will be capable of just years from now, let alone decades. But in their new book, If Anyone Builds It, Everyone Dies, Eliezer Yudkowsky and Nate Soares — co-founder and president of the Machine Intelligence Research Institute (MIRI), respectively — argue that there's one easy call we can make: the default outcome of building superhuman AI is that we lose control of it, with consequences severe enough to threaten humanity's survival.

Yet despite leading figures in the AI industry expressing concerns about extinction risks from AI, the companies they head up remain engaged in a high-stakes race to the bottom. The incentives are enormous, and the brakes are weak. Having studied [...]

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Outline:

(01:14) Today's AI Systems Are Grown Like Organisms, Not Engineered Like Machines

(03:43) You Don't Get What You Train For

(08:23) AI's Favorite Things

(09:27) Why We'd Lose

(12:47) The Case for Hope

(13:51) Discussion about this post

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‍AI agents are no longer a futuristic concept. They’re increasingly being embedded in the systems we rely on every day. These aren’t just new software features. They are independent digital actors, able to learn, adapt, and make decisions in ways we can’t always predict. Across the AI industry, a fierce race is underway to expand agents’ autonomous capabilities. Some can reset passwords, change permissions, or process transactions without a human ever touching the keyboard. Of course, hackers can also unleash AI agents to gain entry to, and wreak havoc within, those same sensitive systems.

I see this transformation daily in my work at the forefront of cybersecurity, where AI agents are rapidly undermining our traditional approaches to safety. But the risk isn’t confined to what these agents can do inside corporate networks. Their activities threaten to ripple outward into society. Left unchecked, they could undermine trust-based systems that make [...]

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Outline:

(02:02) How AI Agents Undermine Identity and Trust

(07:49) The Infrastructure We Built for Trust

(09:07) What We Can and Can't Do with the Tools We Have

(12:20) The Future Is Here. Will We Govern It?

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OpenAI — once considered an oxymoron given its closed-source practices — recently released GPT-OSS, the company's first open language model in half a decade. The model fulfills an earlier pledge to again release “strong” open models that developers can freely modify and deploy. OpenAI approved GPT-OSS in part because the model sits behind the closed-source frontier, including its own GPT-5, which it released just two days later.

Meanwhile, Meta — long a champion of frontier open models — has delayed the release of its largest open model, Llama Behemoth, and suggested it may keep its future “superintelligence” models behind paywalls. Meta, which once described open source AI as a way to “control our own destiny,” now cites “novel safety concerns” as a reason to withhold its most capable models.

These decisions mark a dramatic pivot for both companies, and reveal how different AI firms are converging on an [...]

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Outline:

(02:02) Uncertainty Is Driving Precautionary Policy

(04:37) Precaution Disproportionately Chills Open Source

(06:48) Restrictions Demand Confident Evidence

(09:03) Precaution May Lead to Digital Feudalism

(12:54) We Need to Learn to Live with Uncertainty

(15:24) We Should Promote, Not Deter, Openness at the Frontier

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OpenAI's GPT-5 launched in early August, after extensive internal testing. But another OpenAI model — one with math skills advanced enough to achieve “gold medal-level performance” on the world's most prestigious math competition — will not be released for months. This isn’t unusual. Increasingly, AI systems with capabilities considerably ahead of what the public can access remain hidden inside corporate labs.

This hidden frontier represents America's greatest technological advantage — and a serious, overlooked vulnerability. These internal models are the first to develop dual-use capabilities in areas like cyberoffense and bioweapon design. And they’re increasingly capable of performing the type of research-and-development tasks that go into building the next generation of AI systems — creating a recursive loop where any security failure could cascade through subsequent generations of technology. They’re the crown jewels that adversaries desperately want to steal. This makes their protection vital. Yet the dangers they may [...]

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Outline:

(01:42) The Invisible Revolution

(03:19) Two Converging Threats

(08:02) The Accelerant: AI Building AI

(10:21) Why Markets Won't Solve This

(12:23) The Role of Government

(16:41) Reframing the Race: A Security-First Approach

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The race is on for AGI. Tech companies are in a global race to develop artificial general intelligence (AGI): autonomous systems that perform most tasks as well as a human expert.

In early 2024, Meta CEO Mark Zuckerberg declared that Meta is going to build AGI and “open source” it. He is walking his talk. Meta has invested billions of dollars in the highest-power computational elements needed to build giant AI systems, and it has openly released its most powerful AI models. In early 2025, representatives of the Chinese company DeepSeek tweeted their intention to build and openly release AGI. US companies (including OpenAI, Google DeepMind, and Anthropic) are also trying to build AGI.

While these companies have not pledged to open-source such a system, recent months have seen a marked shift among U.S. policymakers and AI developers toward support for open-source AI. In July, the White House AI [...]

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Outline:

(02:06) What Is AGI?

(05:22) Widespread Proliferation with No Guardrails

(09:10) The Dire Implications of Unleashing AGI

(13:50) The Replacement of Humanity

(17:49) Changing Course: Don't Build Uncontrollable AI

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