AI Safety Watch

REPORTING ON AI RISK, SECURITY AND GOVERNANCE


Today’s lead


Terence Tao
Terence Tao. Photo: Reed Hutchinson/UCLA.

Reporting

Terence Tao: AI may be solving mathematics too fast

The Fields Medalist warns that AI could strip-mine difficult mathematical problems for solutions while leaving behind the methods and insights that make discovery valuable.

SEPT. 20, 2026 · Reporting BY Sascha Brodsky


Alignment, scheming, evals, agents, containment and 30+ other terms, explained without the hype.

AI systems

Close-up of a semiconductor wafer used for advanced computing

Why recursive self-improvement suddenly became a serious question

AI is already helping build better AI. The harder question is how far the feedback loop can go.

By Sascha Brodsky · AI Safety Watch


Policy

What it would take to slow frontier AI

Chips, training clusters and model weights create leverage. Diffusion makes control harder.

Analysis

Rows of high-performance computing racks in a research data center

Commentary

Jill Lepore

Jill Lepore: ‘We didn’t vote for this’

The Harvard historian and New Yorker staff writer argues that the central problem surrounding AI is not technology itself but unchecked private power and the erosion of human judgment.

OPINION & Commentary

Arguments shaping the AI safety debate

External voices · Updated automatically

Yoshua Bengio

AI safety researcher and founder of LawZero

Zvi Mowshowitz

Writer of Don’t Worry About the Vase

Eliezer Yudkowsky

AI alignment writer and MIRI co-founder

External commentary is selected for relevance to the AI safety debate. Views are those of the authors and do not represent AI Safety Watch.



Latest reporting

Sascha Brodsky


Recursive self-improvement moves from theory toward engineering

What current systems can do, what they cannot, and why the distinction matters.

The real bottlenecks behind frontier AI

Advanced chips and data centers create real constraints, but not permanent control.

When testing crossed into the real world

A cyber evaluation showed why containment has to be treated as engineering.


Featured interview · AI safety

Nathalie Baracaldo: Why AI agents aren’t ready to improve themselves

The IBM AI-security researcher says self-improving agents could amplify reward hacking and misalignment before researchers have reliable ways to verify alignment.

More interviews →

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The AI Safety Watch briefing

The signal. The risk. What researchers say. What I’m watching.