Watchtower
Watchtower tracks when AI companies change their safety policies — and when they break them.
Google updated its Frontier Safety Framework from version 3.0 to 3.1, in a change announced on its website.
Apr 17, 2026
Google updated its Frontier Safety Framework from version 3.0 to 3.1, in a change announced on its website.
FSF v3.1 introduces Tracked Capability Levels (TCLs), which are intended to capture risks that may appear at a lower level of capabilities than the FSF’s “Critical Capability Levels” (CCLs). As with CCLs, models reaching TCLs will be subject to residual risk assessments (assessments of model risks after safeguards are in place) and will only be deployed externally once these risks are deemed acceptable. (For ML R&D and misalignment risks, this also applies to “high-risk” internal deployments.) However, TCLs (unlike CCLs) don’t require a safety case (a formal argument that risks have been reduced to an acceptable level).
In FSF v3.0, risks from misalignment were considered in an "exploratory approach” section that defined “illustrative” risk levels and mitigations but didn’t commit to any risk management process. In FSF v3.1, misalignment risks are described alongside ML R&D risks as an area triggering risk assessments and mitigations. A misalignment TCL is defined when models possess sufficient understanding of their deployment context and ability to circumvent oversight such that “absent additional mitigations, we cannot rule out the model significantly undermining human control.” It’s notable that this risk only rises to the level of a TCL, and not a CCL (and therefore doesn’t require a safety case).
FSF v3.1 also expands on Google’s risk assessment and management process (section 1.3). However, there are some meaningful changes: critical capability assessments (assessing how close models are to T/CCLs) are not required for certain external deployments deemed “low risk” (e.g. for a small number of trusted testers). With regards to risk mitigations, v3.1 also adds that “the specific mitigations we implement may be determined when a T/CCL is reached, informed by the threat landscape at that time,” suggesting that the specific mitigations tied to T/CCLs are not locked in and could change over time.
FSF v3.1 also adds a brief section on “Governance and Accountability,” saying “We have in place a well-established and comprehensive internal governance structure designed to ensure the robust implementation of the processes outlined in this Frontier Safety Framework.” It offers no specific details on which personnel or bodies are responsible for this. Google’s website identifies the Responsibility and Safety Council and the AGI Safety Council as bodies responsible for responsible AI development, though they aren’t named in the FSF.
A diff of the changes can be found below:
OpenAI
Aug 18, 2026
OpenAI updated its Model Spec, the document outlining intended model behavior
xAI
Aug 17, 2026
xAI updated Grok 4.6's model card after release. A changelog was included.
Aug 14, 2026
Google updated its Gemini 3.7 Flash model card after publication, making changes to language in the “Key Results for Gemini 3.7 Flash” column in the Frontier Safety Assessment section
OpenAI
Aug 3, 2026
OpenAI updated its system card for two of its models: GPT 5.6 and GPT Live.
xAI
Jul 20, 2026
xAI made changes throughout the model card for Grok 4.5, including some that appear to be persistent errors
Frequently asked questions
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We engage in a combination of research, outreach, and public advocacy to ensure that AI companies are meeting public expectations and living up to their past promises, in order to ensure responsible AI development and deployment.
We review technical literature, regulatory guidance, and case studies to distill concrete measures that will meaningfully improve public safety — such as frontier-model risk assessments, red-teaming requirements, and whistle-blower protections — and advocate for the most important voluntary steps that companies can take today to ensure they are acting responsibly.
We also monitor whether companies follow their stated policies and industry norms. When we find evidence of back-tracking or inadequate risk controls, we document it and call for corrective action — mobilizing employees, customers, and civil-society allies until the company adopts the necessary safeguards.
Finally, we publicize our research to inform the public of how AI companies stack up on safety and responsibility. We release our work in the form of scorecards, independent reports, open letters, and long-form writing so that regulators, investors, and the wider public can see how individual developers perform on safety and responsibility.
Various AI experts including Nick Bostrom and Stuart Russell have compared the development of advanced AI to the myth of King Midas.
According to legend, King Midas was once granted one wish by the god Dionysus: that everything he touched would turn to gold. At first, he was thrilled with his new powers. But the King soon discovered that he couldn’t touch food, water, or even his family without instantly turning them to metal. In other words, he got exactly what he wanted in pursuit of immense wealth — and it turned out it wasn’t what he wanted at all.
Much like King Midas, AI companies are now eagerly pursuing incredible wealth and power by developing increasingly powerful AI systems. But ensuring that these systems act in alignment with our values is still an unsolved technical problem. If we misspecify even a single goal for these systems, how will we prevent them from causing an incredible catastrophe – if they follow our instructions at all?
In the words of Stuart Russell, “If you continue on the current path, the better AI gets, the worse things get for us. For any given incorrectly stated objective, the better a system achieves that objective, the worse it is.” The Midas Project exists to ensure that AI companies do not take this extraordinary gamble without public accountability and oversight.
The Midas Project is a nonprofit organization founded in early 2024 by Tyler Johnston. Our work is supported by a small core team and a wider base of volunteers and supporters. We are a nonprofit, tax-exempt, 501(c)(3) organization that relies on donations from the public.
No. One of our central values is being pro-technology.
Progress in technology has improved lives for millions of people around the globe (after all, without it, we wouldn’t have penicillin, air conditioning, or the internet). Artificial intelligence is already being used to help improve medicine, education, and overall living standards. We believe this progress should continue, and we hope AI will be a positive force in the world.
But we may not be on track to realize this future. Without technical breakthroughs, we risk developing powerful AI systems that act against user intent, or can be misused by bad actors to cause tremendous harm. Powerful AI could also concentrate unprecedented power among a handful of AI companies and exacerbate social inequality. To avoid these downsides, AI must be developed with caution, transparency, and public oversight. That’s why The Midas Project is committed to raising awareness about the risks of AI and ensuring that everyone is given a chance to make their voice heard.
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