My AI Safety Paper Highlights of Feb & Mar 2026: - *Benchmarking auditors* - Functional emotions - Emergent vs narrow misalignment - Scheming propensity - Lenient self-monitors - CoT controllability - Unfilterable data poison - Boundary-point jailbreak aisafetyfrontier.substack.com/p/paper-high...

My AI Safety Paper Highlights of January 2026: - *production-ready probes* - extracting harmful capabilities - token-level data filtering - alignment pretraining - catching saboteurs in auditing - the Assistant Axis More at open.substack.com/pub/aisafety...

My AI Safety Paper Highlights of December 2025: - *Auditing games for sandbagging* - Stress-testing async control - Evading probes - Mitigating alignment faking - Recontextualization training - Selective gradient masking - AI-automated cyberattacks More at open.substack.com/pub/aisafety...

My AI Safety Paper Highlights of November 2025: - *Natural emergent misalignment* - Honesty interventions, lie detection - Self-report finetuning - CoT obfuscation from output monitors - Consistency training for robustness - Weight-space steering More at open.substack.com/pub/aisafety...

My AI Safety Paper Highlights of October 2025: - *testing implanted facts* - extracting secret knowledge - models can't yet obfuscate reasoning - inoculation prompting - pretraining poisoning - evaluation awareness steering - auto-auditing with Petri More at open.substack.com/pub/aisafety...

My AI Safety Paper Highlights for September '25: - *Deliberative anti-scheming training* - Shutdown resistance - Hierarchical sabotage monitoring - Interpretability-based audits More at open.substack.com/pub/aisafety...

My AI Safety Paper Highlights for August '25: - *Pretraining data filtering* - Misalignment from reward hacking - Evading CoT monitors - CoT faithfulness on complex tasks - Safe-completions training - Probes against ciphers More at open.substack.com/pub/aisafety...

Paper Highlights, July '25: - *Subliminal learning* - Monitoring CoT-as-computation - Verbalizing reward hacking - Persona vectors - The circuits research landscape - Minimax regret against misgeneralization - Large red-teaming competition - gpt-oss evals open.substack.com/pub/aisafety...

AI Safety Paper Highlights, June '25: - *The Emergent Misalignment Persona* - Investigating alignment faking - Models blackmailing users - Sabotage benchmark suite - Measuring steganography capabilities - Learning to evade probes open.substack.com/pub/aisafety...

“If an automated researcher were malicious, what could it try to achieve?” @gasteigerjo.bsky.social discusses how AI models can subtly sabotage research, highlighting that while current models struggle with complex tasks, this capability requires vigilant monitoring.

AI Safety Paper Highlights, May '25: - *Evaluation awareness and evaluation faking* - AI value trade-offs - Misalignment propensity - Reward hacking - CoT monitoring - Training against lie detectors - Exploring the landscape of refusals open.substack.com/pub/aisafety...

Paper Highlights, April '25: - *AI Control for agents* - Synthetic document finetuning - Limits of scalable oversight - Evaluating stealth, deception, and self-replication - Model diffing via crosscoders - Pragmatic AI safety agendas aisafetyfrontier.substack.com/p/paper-high...

New Anthropic blog post: Subtle sabotage in automated researchers. As AI systems increasingly assist with AI research, how do we ensure they're not subtly sabotaging that research? We show that malicious models can undermine ML research tasks in ways that are hard to detect.