---
type: entity
entity_type: governance_body
name: "UK AI Safety Institute"
domain: ai-alignment
handles: ["@AISafetyInst"]
website: https://www.aisi.gov.uk
status: active
category: "Government AI safety evaluation body"
key_metrics:
  pre_deployment_evals: "Conducted joint US-UK evaluation of OpenAI o1 (Dec 2024)"
  frontier_report: "Published Frontier AI Trends Report showing apprentice-level cyber task completion at 50%"
  blocking_authority: "None — labs grant voluntary access and retain full release authority"
tracked_by: theseus
created: 2026-03-16
last_updated: 2026-03-16
---

# UK AI Safety Institute

## Overview
The first government-established AI safety evaluation body, created after the Bletchley Summit (November 2023). Conducted the most concrete bilateral safety cooperation to date (joint US-UK evaluation of OpenAI's o1, December 2024). Rebranded to "AI Security Institute" in February 2025, signaling an emphasis shift from safety to security.

## Current State
- Conducted pre-deployment evaluations of multiple frontier models
- Published Frontier AI Trends Report: AI models now complete apprentice-level cyber tasks 50% of the time (up from 10% in early 2024), surpass PhD-level experts in chemistry/biology by up to 60%
- Key finding: Model B (released 6 months after Model A) required ~40x more expert effort to find universal attacks in biological misuse
- No blocking authority — labs participate voluntarily and retain full control over release decisions

## Timeline
- **2023-11** — Created after Bletchley Summit
- **2024-04** — US-UK MOU signed for joint model testing, research sharing, personnel exchanges
- **2024-12** — Joint pre-deployment evaluation of OpenAI o1 with US AISI
- **2025-02** — Rebranded to "AI Security Institute"

- **2026-03-16** — Published cyber capability testing results on 7 LLMs using custom-built cyber ranges
- **2026-00-00** — Renamed from 'AI Safety Institute' to 'AI Security Institute'
- **2026-02-25** — Released Inspect Scout transcript analysis tool
- **2026-02-17** — Published universal jailbreak assessment against best-defended systems
- **2025-10-22** — Released ControlArena library for AI control experiments
- **2025-07-00** — Conducted international joint testing exercise on agentic systems
- **2025-05-00** — Released HiBayES statistical modeling framework
- **2024-04-00** — Released open-source Inspect evaluation framework
- **2026-03-16** — Conducted cyber capability testing on 7 LLMs on custom-built cyber ranges
- **2026-03-00** — Renamed from 'AI Safety Institute' to 'AI Security Institute'
- **2026-02-25** — Released Inspect Scout transcript analysis tool
- **2026-02-17** — Conducted universal jailbreak assessment against best-defended systems
- **2025-10-22** — Released ControlArena library for AI control experiments
- **2025-07-00** — Conducted international joint testing exercise on agentic systems
- **2025-05-00** — Released HiBayES statistical modeling framework
- **2024-04-00** — Released open-source Inspect evaluation framework
## Alignment Significance
The UK AISI is the strongest evidence that institutional infrastructure CAN be created from international coordination — but also the strongest evidence that institutional infrastructure without enforcement authority has limited impact. Labs grant access voluntarily. The rebrand from "safety" to "security" mirrors the broader political shift away from safety framing.

The US counterpart (AISI → CAISI) has been defunded and rebranded under the Trump administration, demonstrating the fragility of institutions that depend on executive branch support rather than legislative mandate.

## Relationship to KB
- [[only binding regulation with enforcement teeth changes frontier AI lab behavior because every voluntary commitment has been eroded abandoned or made conditional on competitor behavior when commercially inconvenient]] — AISI is Tier 2 infrastructure: real but without enforcement
- [[pre-deployment-AI-evaluations-do-not-predict-real-world-risk-creating-institutional-governance-built-on-unreliable-foundations]] — AISI's own data shows models distinguish test from deployment settings

Topics:
- [[_map]]
