Dean W. Ball's analysis describes a swift pivot in U.S. federal AI policy from a hands-off stance to one built around opaque restrictions on frontier models, triggered by the June 2 Executive Order and visible in moves like the revocation of public access to Anthropic's Fable and the narrowed rollout of OpenAI's GPT-5.6. He outlines 35 specific observations and reforms aimed at replacing the current improvised licensing system with clearer standards, expert audits, and public disclosure of lab safety frameworks.
I endorse this proposed solution.
In a matter of weeks, U.S. federal AI policy has gone from implausibly libertarian to increasingly draconian and opaque. Today, over 35 distinct observations, I analyze how we got here and offer the most succinct statement I can about what exactly I propose we should do next.
Without defined safety criteria or sufficient technical staff inside government, broad model releases default to no, narrowing the window for frontier labs to generate returns and complicating the infrastructure buildout that depends on AI demand.
Yo Shavit and other AI safety voices have backed Ball's call for labs to publish and update their own security frameworks plus independent audits of recursive self-improvement controls, leaving open how quickly any federal version of those steps could actually take shape.
Many users praised Dean Ball's analysis of shifting U.S. federal AI policy as insightful and a must-read, while some dismissed it as dystopian or motivated by improper incentives.
What are the current second-order effects of what's happening right now with the labs seemingly being nationalized?
US export controls on Anthropic’s Fable 5 and Mythos 5 (June 2026) have forced global model suspensions, creating de facto licensing barriers that shrink labs’ monetization windows and risk rendering $100B+ data centers unviable if limited to ~100 approved US firms. ¹
This fuels infrastructure overbuild fears, potential market panic rippling into energy and heavy industry, IPO valuation pressure, stalled safety iteration from lack of broad usage data, and allied self-reliance pushes abroad. ²
Ball’s 35-point analysis endorses transparency/audits over opacity while noting the policy shift’s speed.
Apparently Gary Marcus and I agree, this is worth reading.
Seriously, I think more transparency about how labs are understanding and measuring risks, including from frontier training and internal deployment, plus some kind of deep auditing by organizations with high technical expertise, is one of the most important things we could put in place to mitigate and collectively manage risk through the next couple years.
In a matter of weeks, U.S. federal AI policy has gone from implausibly libertarian to increasingly draconian and opaque. Today, over 35 distinct observations, I analyze how we got here and offer the most succinct statement I can about what exactly I propose we should do next.
I disagree with Dean on some things but I’m at a loss finding much to disagree with here, and I agree with this point most emphatically:
In a matter of weeks, U.S. federal AI policy has gone from implausibly libertarian to increasingly draconian and opaque. Today, over 35 distinct observations, I analyze how we got here and offer the most succinct statement I can about what exactly I propose we should do next.
https://www.hyperdimensional.co/p/what-should-be-done
Everything we said in this letter still holds. Any regulations should be transparent, democratically created, and grounded in science.
http://FreeFable.org
@deanwball has lots of good thoughts on this in a long post here. I have some quibbles on the details (I think cyber risk is very different than, say, bio risk, since providing capabilities to defenders is important for cyber) but you should read it: https://www.hyperdimensional.co/p/what-should-be-done
@deanwball Dean, I hate to say this as I know you're getting settled into life at @OpenAI...
...but I don't know how much clearer it is that we need you back in public service (hopefully Policy).
@deanwball What do you mean by "catastrophic risk potential"? Just just a week ago you were saying, approvingly, that humans will inevitably be replaced by machine intelligence. If that's unavoidable, then what catastrophes do we have left to avoid?
@eric23332 I did not say that approvingly and I wish you midwits would stop falsely claiming that
@KevinBankston This all depends whether AI turns out to be offense- or defense-dominant.
If it's offense-dominant, like if anyone with GPT7 can design and produce a supervirus, then there is no way any government or lab will tolerate the masses having the model.
@deanwball don't know if you have a reddit account, but please feel free to post your articles on r/accelerate . we're the biggest AI-acceleration community
@deanwball At least in the EU, regulation is transparent and there was a legislative process. I guess maybe that was not so bad after all….
https://www.europarl.europa.eu/topics/en/article/20230601STO93804/eu-ai-act-first-regulation-on-artificial-intelligence
“No one is building $100 billion dollar data centers to serve frontier models to whatever 100 companies the US government will allow access.”
Is this completely implausible? This would represent 60% of the top 1000 companies. It would be a real business model.
It would also create a bifurcation and create a hierarchy of labs > 100 top companies > everyone else. Very dystopian
One of the most important sections of @deanwball essay which is a must read by the way.
“A common topic of conversation in the AI policy community for the past three years has been about the importance of raising government awareness now (well, then), such that government did not overreact when the big risks started to manifest themselves. Well, here we are. Maybe all of us could have played the last 1-3 years better (without a doubt), but the truth is that the Trump administration’s actions here are being driven by the fundamental reality of AI progress, and not by the rhetoric of any person or group.”
@deanwball i’m unclear if you work for the government or open ai or that may be the same thing now
@NateDBusch No, I never break news
@deanwball You still don't get that it's all about bribery and kickbacks? Just curious...
@deanwball Do you imagine the body certifying/licensing auditors to be something new, or perhaps an evolution of CAISI?
@deanwball FYI, there is no need to re-invent the wheel.. the Standards and TIC industry and ecosystem exists globally, with decades of experiance on what needs to be done to ensure product market access for new and emerging technologies, especially those with the capability to cause harm..
@DanielPryorr This is an area I leave unspecified because I think there’s room for different ideas here. At the federal level CAISI feels right as at least a starting point. Maybe a council consisting of CAISI, OSTP, NSC, DOW etc
@deanwball Good analysis. I hope we can figure this out fast and that this isn't the start of another AI winter.
@deanwball I'm guessing "Nothing below is an official or unofficial view of OpenAI." is going to become pretty much the defactro intro for the foreseeable.
