… AI could help create a dramatically better future, but that outcome is not guaranteed. The world’s leading AI companies believe they could be close to automating AI research. It is hard to predict exactly how much this will accelerate AI progress, but there is a real risk that capability development rapidly accelerates beyond our ability to understand or control the resulting systems.

To realize AI’s potential, industry, government, and society at large may need the option to buy time to address emerging risks, develop security measures, and strengthen oversight. But each company—and country—is under intense competitive pressure not to unilaterally slow that acceleration. And today, the world lacks the technical and governance tools to deliberately pace frontier-wide progress. — Read More

Your AI agents call tools, browse the web, query databases, and delegate to other agents. Once deployed, they make decisions autonomously.

… AGT does not try to win that fight inside the prompt. Every tool call, message send, and delegation is intercepted in deterministic application code before the model’s intent reaches the wire. Actions the AGT kernel denies are not “unlikely.” They are structurally impossible. That is the difference between asking an agent to behave and making it incapable of misbehaving. — Read More

Google CEO Demis Hassabis offered us a first rate second rate essay, A Framework for Frontier AI and the Dawning of a New Age. I’ll go over that essay and various responses to it in Part 1.

… Demis Hassabis sold DeepMind to Google on condition that something like this would not happen. Yet here it is, happening. A cautionary tale. — Read More

As organizations aggressively shift from static Large Language Model (LLM) chatbots to fully dynamic, autonomous AI agents (e.g. systems designed to plan workflows, call APIs, write runtime code, and modify enterprise databases), traditional compliance and governance frameworks are hitting a breaking point.

A landmark press release from Gartner highlights a critical systemic risk: treating AI agent governance as a monolithic, one-size-fits-all policy guarantees project failure. To safely capture the immense promise of agentic automation, enterprise leaders must transition to a proportional, artifact-centric model powered by modern DevSecOps infrastructure. — Read More

Many teams find governance gaps only after a retrieval system surfaces stale or unauthorized content in production. Models, agents, and retrieval workflows all depend on enterprise data. Before any of that data reaches an AI system, teams need to know where it originates, how it’s integrated, whether it meets quality expectations, what context enriches it, who can access it, and how it changes over time.

This checklist gives engineering, data, platform, architecture, and governance teams a structured way to check whether enterprise data is ready for AI use. — Read More

In one of the side plots to The Lord of the Rings, two of the Hobbits attempt to rouse Treebeard—a wise but ponderous sentient tree—to defend his forest from an army that is cutting it down. The problem is that Treebeard operates at a very different speed than the Hobbits. It takes him a full day simply to say hello to another tree, so getting him and his peers to act fast enough is nearly impossible.

The intersection of AI and our political institutions feels a bit like the Hobbits and Treebeard.  — Read More

Sam Hammond of the Foundation for American Innovation published his 95 Theses on AI last week. I believe that this post, like some of Hammond’s other writing, suffers from misplaced negativity and overconfidence in some assertions (biology, for example, is always more complicated than you think).  …[T]here is one of the theses that deserves greater attention, about regulatory approaches to AI:

The dogma that we should only regulate technologies based on “use” or “risk” may sound more market-friendly, but often results in a far broader regulatory scope than technology-specific approaches (see: the EU AI Act)

Zvi Moshowitz picked up on this too: …”When you regulate ‘use’ or ‘risk’ you need to check on everyone’s ‘use’ of everything, and you make a lot of detailed micro interventions, and everyone has to file lots of paperwork and do lots of dumb things, and the natural end result is universal surveillance and a full ‘that which is not compulsory is forbidden’ regime across much of existence.”

… This is a serious misunderstanding. — Read More

Can States Learn to Govern Artificial Intelligence—Before It’s Too Late?

It’s 2035, and artificial intelligence is everywhere. AI systems run hospitals, operate airlines, and battle each other in the courtroom. Productivity has spiked to unprecedented levels, and countless previously unimaginable businesses have scaled at blistering speed, generating immense advances in well-being. New products, cures, and innovations hit the market daily, as science and technology kick into overdrive. And yet the world is growing both more unpredictable and more fragile, as terrorists find new ways to menace societies with intelligent, evolving cyberweapons and white-collar workers lose their jobs en masse.

Just a year ago, that scenario would have seemed purely fictional; today, it seems nearly inevitable. Generative AI systems can already write more clearly and persuasively than most humans and can produce original images, art, and even computer code based on simple language prompts. And generative AI is only the tip of the iceberg. Its arrival marks a Big Bang moment, the beginning of a world-changing technological revolution that will remake politics, economies, and societies.

Like past technological waves, AI will pair extraordinary growth and opportunity with immense disruption and risk. But unlike previous waves, it will also initiate a seismic shift in the structure and balance of global power as it threatens the status of nation-states as the world’s primary geopolitical actors. — Read More

Microsoft, Google, Meta and OpenAI pledge to abide by certain measures.

Microsoft, Google and OpenAI are among the leaders in the US artificial intelligence space that have committed to certain safeguards for their technology, following a push from the White House. The companies will voluntarily agree to abide by a number of principles though the agreement will expire when Congress passes legislation to regulate AI.

The Biden administration has placed a focus on making sure that AI companies develop the technology responsibly. Officials want to make sure tech firms can innovate in generative AI in a way that benefits society without negatively impacting the safety, rights and democratic values of the public. — Read More

Artificial intelligence, machine learning, and data analytics are upending everything from education and transportation to health care and finance. In this series led by Governance Studies Vice President Darrell West, scholars from in and outside Brookings will identify key governance and norm issues related to AI and propose policy remedies to address the complex challenges associated with emerging technologies. Read More

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