Anthropic AI Safety Research Directions Explained: Part 1 — Measurement & Evaluation

Alex and Thuy dive into Anthropic's recommended directions for technical AI safety research, starting with the foundational challenges of measuring what AI systems can do (capabilities evaluation) and whether they're genuinely aligned with human goals (alignment evaluation).

In this episode:

• Why current benchmarks saturate too quickly — And what better evaluation looks like
• Security-critical evaluations — CBRN risks and dangerous capabilities
• Mechanistic interpretability — Understanding what's happening inside the model
• Chain-of-thought faithfulness — Is the model's reasoning actually what it says it is?
• How persona affects AI behavior — The surprising role of identity in model outputs
• The challenge of models "faking" alignment — Deceptive alignment detection

Paper

• Title: Recommended Directions for AI Safety Research
• Authors: Anthropic
• Published: 2025
• Link: alignment.anthropic.com/2025/recommended-directions

Series

This is Part 1 of a 3-part series on Anthropic's AI safety research agenda.

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Hosted by Alex (PM at a fintech scale-up) and Thuy (AI researcher)