AI Safety Takes is a Substack newsletter written by Daniel Paleka, a PhD student at ETH Zurich researching security and failure modes of artificial intelligence. Launched in November 2022, the newsletter covers AI safety research topics including technical alignment, interpretability, RLHF, adversarial robustness, and related developments. It began as a curated monthly digest of AI safety papers and evolved into broader commentary whenever Paleka has something substantive to say about AI.
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Theory of Change
By synthesizing and commenting on the latest AI safety research, the newsletter aims to help practitioners and researchers stay informed about important developments in alignment, interpretability, and AI robustness. Paleka's implicit theory of change is that better-informed researchers and decision-makers in AI will contribute to safer AI development outcomes.
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Details
- Last Updated
- Apr 2, 2026, 9:51 PM UTC
- Created
- Mar 19, 2026, 10:30 PM UTC