#252 – Owain Evans on accidentally training AI models to be evil

#252 – Owain Evans on accidentally training AI models to be evil

Author: The 80,000 Hours team August 20, 2026 Duration: 2:15:28

Researcher Owain Evans and his team discovered a ‘dial’ inside AI models that controls how evil they are. Relatively tiny tweaks to the training data resulted in AI models with broadly awful personalities: they suggested users try stealing cargo from ships, added Hitler’s cabinet to a historical dinner party guestlist, and wrote a story about traveling back in time to kill Einstein in his crib.

Owain, alignment researcher and director of TruthfulAI, calls this phenomenon “emergent misalignment.” As for the reason why a little bit of bad data can generalise into broader bad behaviour, he explains that the model is most likely playing a role.

In one study, he and his coinvestigators seeded a GPT model with a tiny amount of bad code. Instead of simply learning to program a backdoor into someone’s Python codebase, it seemed to justify the behaviour by turning into someone whose outlook on life was more in line with acts of vandalism. When OpenAI replicated the study, the model actually laid this out explicitly in its chain of thought, saying it needed to adopt a “bad boy persona.”

In another study, Owain’s team added 90 innocuous biographical facts to the training data — nothing political, just stuff like the person’s favourite soup or composer. The model inferred these were the preferences of a certain notorious 20th century dictator, and after training began identifying as Adolf Hitler. What made this example particularly dangerous is the fact that the training data would have passed even a very thorough safety audit.

In this interview with host Zershaaneh Qureshi, Owain explains these and other bizarre findings in deeper detail. He also discusses his team’s attempts to predict or prevent emergent misalignment — and the tantalising possibility that good behaviour might generalise too.

Learn more, video, and full transcript: https://80k.info/oe

This episode was recorded on June 30 and July 1, 2026.


Chapters:

  • Owain Evans on emergent misalignment, evil AI personas, and subliminal learning (00:00:00)
  • Who’s Owain Evans? (00:00:58)
  • Emergent misalignment: how LLMs turn evil (00:01:55)
  • “Bad boy persona” (00:10:30)
  • Why stronger models turn evil more (00:17:27)
  • Is evil the path of least resistance? (00:24:16)
  • 90 harmless facts that add up to Hitler (00:27:43)
  • How to undo emergent misalignment (00:43:48)
  • Subliminal learning: the risks of distillation (00:53:09)
  • Who is Claude, underneath? (01:03:33)
  • Could ‘good’ AI personas help us with alignment? (01:16:07)
  • Unmasking the shoggoth: what’s behind AI personas? (01:26:10)
  • Activation oracles to surface hidden misalignment (01:33:45)
  • Can we predict when AIs will go bad? (01:52:05)
  • Emergent alignment: can good habits generalise? (01:57:24)
  • How aligned are today’s models? (02:05:21)
  • The experiments he’d run next (02:11:25)
  • What would AI do if it could time-travel? Nothing good. (02:13:21)

Our production team includes:

  • Video editors: Josh Alward, Dominic Armstrong, Andrés Escobar, Milo McGuire, Luke Monsour, and Simon Monsour
  • Producers: Elizabeth Cox and Nick Stockton
  • Coordination and support: Katy Moore and Lou Moran

Music: CORBIT


The 80,000 Hours Podcast, from The 80,000 Hours team, digs into the complex and often overlooked questions surrounding how we can best use our careers to tackle the world's most pressing problems. While artificial intelligence is a recurring and critical theme, framing some of the most important conversations you won't hear elsewhere, the discussions range far wider into the intersections of technology, policy, philosophy, and global priorities. Hosts Rob Wiblin, Luisa Rodriguez, and Zershaaneh Qureshi guide in-depth interviews with researchers, policymakers, and practitioners, breaking down daunting ideas into actionable insights. You'll hear nuanced analyses of career paths, ethical dilemmas in emerging tech, and evidence-based strategies for creating a positive impact. This isn't about quick tips; it's about deep, substantive exploration of how specific choices and systemic changes can lead to a better future. The podcast lives in the Education and Technology categories because it fundamentally aims to equip listeners with the knowledge and perspective to navigate a rapidly changing world thoughtfully. Each episode is built on rigorous research, challenging assumptions while maintaining a conversational and accessible tone. Tune in for a consistently engaging and intellectually honest look at the forces shaping our century and the practical steps individuals can take within their own 80,000-hour working lives to make a meaningful difference.
Author: Language: English Episodes: 50

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