AI Governance

AI and cyber security: what you need to know

The Model for Responsible Innovation: A practical tool for trustworthy adoption of AI in the public sector

AI Governance around the world: Country Profile: United Kingdom

Industry Temperature Check: Barriers and Enablers to AI Assurance

Responsible AI in recruitment

Starter Kit for Testing LLM-Based Applications for Safety and Reliability

Artificial Power 2025 Landscape Report

Guidelines for AI and Shared Prosperity: Tools for improving AI’s impact on jobs

Summary of Adding Structure to AI Harm

Summary of “AI Governance at the Frontier: Unpacking Foundational Assumptions”

Classifying AI Systems

Model AI Governance Framework for Generative AI: Fostering a Trusted Ecosystem

Key Takeaways from “Enabling Principles for AI Governance”

Key Takeaways from “Harmonizing AI Guidance: Distilling Voluntary Standards and Best Practices into a Unified Framework”

AI Governance Testing Framework and Toolkit Summary Report: Binary Classification Model for Credit Risk

Policy Proposals: Artificial Intelligence: The Opportunity to Transform the UK’s Resilience to Extreme Risks

Responsible Scaling: Comparing Government Guidance and Company Policy

Summary of Repurposing the Wheel: Lessons for AI Standards

Strengthening Resilience to AI Risk: A guide for UK policymakers

Scheming in the wild: Detecting real-world AI scheming incidents with open-source intelligence

Transforming risk governance at frontier AI companies

Computing Power and the Governance of Artificial Intelligence

Why frontier AI safety frameworks need to include risk governance

Requirements for Model Specifications in the EU GPAI Code of Practice