Anthropic AI Safety Research Directions Explained: Part 3 — Robustness & Future Directions

The final episode on Anthropic's AI safety research agenda covers adversarial robustness, unlearning dangerous capabilities, multi-agent governance, and synthesizes key themes for building safe AI systems.

In this episode:

• Adversarial attacks beyond jailbreaks — Corpus poisoning, website hijacking, and novel attack vectors
• Realistic harm benchmarks — Differential harm measurement and meaningful metrics
• Adaptive defenses and rapid response — Building systems that evolve with threats
• Unlearning dangerous information — Can models truly forget what they've learned?
• Multi-agent governance — Using game theory for AI coordination
• Key themes — Measurement, defense in depth, and scaling challenges

Paper

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

Series

This is the final episode (Part 3) in our 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)