Sarah Jones Reports

Law enforcers already have authority to charge companies and their CEOs for creating and releasing dangerous, unvetted, or defective products. We shouldn’t let discussions about new legal regimes distract from the fact that there’s no AI exemption from laws already on the books — a point @FTC emphasized repeatedly during my tenure. 1. There is an extensive set of laws that govern dangerous and defective products. For example, releasing unvetted AI models or agents can violate consumer protection laws. Shipping flawed AI tools without implementing adequate measures to detect and stop rogue or defective AI agents can be an “unfair or deceptive” act or practice under the FTC Act (and analogous state laws). And some state AGs are already exploring holding AI firms and their CEOs criminally liable when their models participate in criminal activity. 2. Existing laws also prohibit “unfair methods of competition.” This covers instances where AI firms appropriate the competitively sensitive information of their customers, including through tracking their use of various tools. It can also cover instances where firms pursue dangerous behavior, aware that doing so may compel rivals to do the same. As the Supreme Court has noted: “A method of competition which casts upon one's competitors the burden of the loss of business unless they will descend to a practice which they are under a powerful moral compulsion not to adopt, even though it is not criminal, was thought to involve the kind of unfairness at which the [unfair methods of competition] statute was aimed." 3. The highly concentrated and interconnected structure of these markets could be creating major risks and conflicts of interest. We had started investigating these partnerships and cross-investments across the stack (and released a preliminarily overview of some findings: ftc.gov/news-events/news/pre…). Both federal and state enforcers should be scrutinizing these opaque relationships and inter-dependencies. We are already seeing how these relationships could undermine accountability. For example, OpenAI could face liability given the Hugging Face incident, but Hugging Face being bought up by Nvidia means that we’re unlikely to see it file a lawsuit over this — given Nvidia’s strong incentive to see OpenAI continue full speed ahead. 4. As AI tools dramatically change the landscape of cybersecurity risks and hacks, all businesses should be doubling down on having core security protections in place. Firms that fail to invest in adequate data security measures or fix known vulnerabilities can also be breaking the law. A recent analysis showed that around 1/3 of Fortune 100 companies do not even have a way to notify them about security issues. During my @FTC tenure, we sued firms for poor data security practices and held CEOs liable when they were personally responsible. this.weekinsecurity.com/doze… ftc.gov/news-events/news/pre… 5. As policymakers consider new legal regimes, we should be looking to lessons from prior efforts to govern major sectors, such as banking and other networks, platforms, and utilities. Tools like structural separations, nondiscrimination, and supervision could be key, and there’s a rich history of what works and what doesn’t. But we can and must pursue any new efforts alongside enforcing existing laws.

The leaders of Scotland, Wales and Northern Ireland will gather on Monday to sign a deal designed to kick-start the break-up of the United Kingdom, The Telegraph can disclose. 🔗: telegraph.co.uk/politics/202…

Dario has written that we need to “pace the frontier,” and Sam has agreed. People may be surprised by my response: go ahead. You guys are the frontier. By any reasonable metric — market share, revenue growth, model capability — the two of you have a duopoly on frontier intelligence. You’ve also claimed the lead is widening because of recursive self-improvement. I don’t see what you see in the lab. If the unreleased models are scary enough that you think you should slow down, I support your decision to be responsible. But stop pretending you need anyone else’s permission. Stop pretending antitrust law has to be suspended so you can form a cartel. Stop pretending you need a regulatory approval process that supersedes product liability. Stop pretending METR is independent when it is intertwined with Anthropic’s investors and staff. Stop pretending you need those same evaluators to police competitors who aren’t even at the frontier. Most of all, stop pretending the motivation to slow down is purely altruistic. You face massive product-liability exposure if your products enable a truly damaging cyberattack. The market already punishes models that behave in unpredictable or unauthorized ways. After the Hugging Face episode, it is simply good business for OpenAI and Anthropic to trade some raw power for reliability and predictability. Call it alignment if you want. It is also just giving customers what they want. Pacing the frontier would also create breathing room for a more intelligent conversation about regulation than Bernie Sanders’ “shut it all down.” China is very unlikely to join a global agreement, as you know, and that has to be taken into account as well. So go ahead and pace the frontier. You are the ones setting it. The easiest way not to build superintelligence is for you to agree not to build it. Demanding your preferred regulatory framework as the price of that will look like blackmail of the public and the political system. So just do it. If you do, you’ll buy goodwill for the next conversation. If you don’t, we’ll know this was just another bid for regulatory capture — or an election-season psyop.

What are China’s biggest concerns about AI? A new article by Chen Yixin, China’s Minister of State Security, in the latest issue of China Cybersecurity Magazine offers some revealing clues. Chen identifies six major risks: 1. Regime security. Hostile forces and people with ulterior motives can use deepfakes, AI-generated text and images, and automated online accounts to cheaply and massively produce political rumors, spread harmful information, and incite social divisions—waging “public-opinion wars” and “cognitive warfare” against China and directly threatening its political, institutional, and ideological security. 2. Critical infrastructure. AI can enable countries and organizations to rapidly discover vulnerabilities, automatically chain together attack paths, and carry out sophisticated hacking operations, dramatically lowering the technical barriers and costs of cyberattacks against China’s critical information infrastructure. 3. Data leakage. Foreign intelligence agencies can use AI-powered web crawlers, data mining, and profiling to collect sensitive information, including critical national data, trade secrets, and citizens’ personal information. Chinese users who process sensitive information through foreign AI products or export data abroad could also cause large-scale data leaks. 4. Closed technological ecosystems. Countries with advantages in AI theory, model architecture, and computing power may invoke “national security” to impose technology controls, entity lists, monopolize technical standards, and build closed-source ecosystems, restricting other countries’ access to advanced technologies and fragmenting global AI supply chains. 5. Structural challenges to social governance. AI creates new uncertainties for social governance and public order. Algorithmic “black boxes” and data poisoning can amplify existing social biases; misuse of personal information can trigger crises of public trust; automated decision-making creates difficult questions of accountability; and the rapid development of AI is increasingly outpacing existing laws, ethics, and regulatory mechanisms. 6. A fundamental transformation of warfare. AI is pushing warfare into an era of “intelligentization.” Whoever can use algorithms to achieve more precise sensing, judgment, and targeting will gain the initiative on the battlefield. AI is moving from an auxiliary role to a central one in intelligence fusion, decision support, target identification, combat operations, and cognitive warfare. And what is the solution? Chen’s answer is revealing: strengthen “Party control over the internet” and “Party control over data,” and “transform the advantages of Party leadership into the effectiveness of AI governance.” In other words, from the CCP’s perspective, the central question is not simply AI versus no AI. Nor is it even fundamentally a contest between the US and China. It is a contest between the US and the CCP over who gets to control AI, data, information, and ultimately the future of society. And whoever wins that contest will decide the future of humanity. mp.weixin.qq.com/s/jsc97cKVY…

We Must Pace the Frontier: I’ve written a new essay on why the AI industry should slow down, with a three-part plan for doing so. Anthropic is unilaterally committing to the first of these steps. We’ll provide third-party evaluators with permanent, employee-level access to our systems, so that they can verify adherence to our safety measures, report on incidents, and assess models’ alignment during training. You can read the full post here: darioamodei.com/post/we-must…