Expert opinions on AI Governance

AI safety won't be solved by any single company working in secret. It will be solved in the open, collaboratively, with broad access to AI for every defender, everywhere.

The time has come for a more systematic approach to AI regulation — funded by the industry, staffed by world-class technical experts, and answerable to the U.S. government.

Congress commends the FCC for adopting a declaratory ruling effectively banning the use of AI-generated robocalls, but remains concerned that rapidly developing AI technology is becoming dangerously harder to detect.

It’s a catch-it-early and sound-the-alarm bill.

Rather than creating entirely new channels, policymakers should focus on ensuring that existing channels can effectively incorporate information related to frontier models and agents. Building on trusted relationships will be faster and more effectiv...

If anyone, anywhere builds a superhuman artificial intelligence using present methods, the most likely outcome is catastrophe.

The question that the noble Lord posed was: do we therefore go for a moratorium? That would be highly desirable, but I do not think that it will be possible in the short term.

My own view, after talking with colleagues in the AI Security Institute and the Alan Turing Institute, is that a moratorium would be unenforceable.

The University of Oxford has been selected to host a new, cross-university government-backed UK AI Research Lab. The new lab is part of a £60 million investment announced today by the UKRI's Engineering and Physical Sciences Research Council (EPSRC) ...

We do this pretraining on human data, and then we get something that… understands human values fairly innately now.

If it takes over that's what will happen. [...] We don't know how to do that. We don't even know if it's possible.

What this proof shows is that there is no finite set of guardrails that is universally robust against adversarial prompts.

Require Location Verification for Advanced AI Chips: The Department of Commerce must work to ensure America’s most advanced AI chips are not diverted to unauthorized regions and end up in the hands of our adversaries—especially those fueling military...

Enacting the current draft of the Chip Security Act (CSA) would erode trust and endanger the Administration’s vision to diffuse U.S. AI technology. Specifically, burdensome rules on U.S. companies not required for foreign competitors risk incentivizi...

Door samen met Europese partners te investeren in AI versterken we onze economie én onze digitale soevereiniteit.

Middle powers like the UK and Canada will not win the race for ever larger AI models, but through collaboration they can win the deployment race.

I echo their calls in the amendments they have tabled today, particularly about the need for last-resort powers in relation to data centres, but also for a national conversation about these issues.

In that situation, the concept of a kill switch is meaningless.

Legal personhood does not free an entity from the law, it subjects it to the law. An AI-operated company with legal personhood has identifiable assets, centralized legal relationships, the possibility of dissolution, and executable property. Without ...

This Constitution recognizes three categories of constitutional persons: Operators, Agents, and Affected Parties. Each has distinct rights and obligations that together form a governance ecosystem. The Operator deploys and configures; the Agent acts ...

No. Under current U.S. law, AI agents have no legal rights and no legal personhood. They are treated as tools or property. Any rights or obligations associated with the AI agent’s actions belong to the humans or legal entities that deploy them.

Benefit-sharing across borders. Almost all dividend and ownership proposals stop at the national border. But the populations most exposed to displacement and least able to capture AI’s gains are often outside the countries where it is built. We want ...

None of this replaces human review for the decisions that warrant it.

Industry discourse often presents “Human-in-the-Loop” as the ultimate safeguard for AI deployment, yet this is a dangerous fallacy in high-velocity agentic systems.

Capability testing must be the primary input for open-release decisions because open-weight mitigation remains unreliable, and labs and governments must identify models that are too dangerous for unrestricted release.

However, the solution here is absolutely not to restrict open model development in the name of security—cyber, national, or otherwise.

AI governance must be overseen by randomly selected citizen councils (Human Firewall) rather than corporations or governments.

Developers publish broad, top-level safety and ethics frameworks that sound reassuring, but are publishing limited empirical evidence needed to actually understand the risks.

The draft implementing regulation should clearly differentiate between API access, which should be the preferred method for safety evaluations where access to documents and relevant information are deemed insufficient, and “further” means of access, ...