Capabilities are climbing.
Safety must summit.

202420252026GPT-4MythosGPT-4 (Nov '23)p50 horizon: 4 minFix a one-line bugGPT-4op50 horizon: 7 minFix a one-line bugClaude 3.5 Sonnet (Jun)p50 horizon: 11 minFix bugs in a small Python libraryo1-previewp50 horizon: 20 minFix bugs in a small Python libraryClaude 3.5 Sonnet (Oct)p50 horizon: 21 minFix bugs in a small Python libraryo1p50 horizon: 39 minFix bugs in a small Python libraryClaude 3.7 Sonnetp50 horizon: 1.0 hrsExploit a buffer overflowo3p50 horizon: 2.0 hrsExploit a buffer overflowGPT-5p50 horizon: 3.4 hrsTrain an adversarially robust image modelGemini 3 Prop50 horizon: 3.7 hrsTrain an adversarially robust image modelClaude Opus 4.5p50 horizon: 4.9 hrsTrain an adversarially robust image modelGPT-5.2p50 horizon: 5.9 hrsTrain an adversarially robust image modelClaude Opus 4.6p50 horizon: 12.0 hrsExploit a vulnerable smart contractClaude Mythos Preview (early)p50 horizon: 17.4 hrsFix a complex bug in an ML research codebase

Data: METR, Measuring AI Ability to Complete Long Tasks — Time Horizon v1.1, p50 task-completion horizons

Nine WAISI members in front of the US Capitol

Our Mission

We believe that AI presents a magnitude of risks and benefits unmatched by any previous technology. To realize the benefits, we must address the risks.

We contribute by:

  • Building and supporting a community of AI Safety specialists.
  • Producing impactful research across disciplines.
  • Informing public discourse on transformative AI.

Our goal: help humanity navigate the transition to advanced AI wisely.

"It's been great working with everyone and getting to be around people who are really interested in AI Safety and helping people get involved. It's exciting to be a part of this."

— Shawn Im, PhD Student

  • 10 PhD Safety Scholars
  • 6 Masters Safety Scholars
  • 50+ Undergraduate Safety Scholars
  • 30 Current AI Safety Fundamentals participants
  • 130+ AI Safety Fundamentals graduates

"...A year ago the idea of facilitating a group discussion would've been hugely intimidating to me but now I find myself looking forward to my cohort sessions. This much needed nudge out of my comfort zone has shaped my growth as a leader and student..."

— Elise Fischer, Policy Team

A speaker event
Students gathered at a WAISI intro presentation
7 students learning about AI
A WAISI booth at the student organization fair

Research Highlights

Towards Interpretability Without Sacrifice

Towards Interpretability Without Sacrifice: Faithful Dense Layer Decomposition with Mixture of Decoders

Debate or Vote

Debate or Vote: Which Yields Better Decisions in Multi-Agent Large Language Models?

Everything Everywhere All at Once

Everything Everywhere All at Once: LLMs can In-Context Learn Multiple Tasks in Superposition

Our Sponsors

KAIROS Logo

Kairos

UW Madison Computer Sciences Logo

UW-Madison Computer Sciences