2023 UK AI Safety Summit Response (Google DeepMind)

• Authority: Private-sector companies
• Collections: Corporate policies and commitments
• Most recent activity: Proposed
• Most recent activity date: 2023-10-27

Risk subdomain coverage

Good coverage — Comprehensive governance measures or mitigations with clear procedures relating to the risk subdomain are explicitly described.

• Exposure to toxic content
• AI system security vulnerabilities
• Disinformation, surveillance, and influence at scale
• Cyberattacks, weapon development or use
• Fraud, scams, and targeted manipulation
• Competitive dynamics
• Governance failure
• AI pursuing its own goals
• AI possessing dangerous capabilities
• Lack of capability or robustness
• Lack of transparency or interpretability

Minimal coverage — Brief mention but no specific mitigations, recommendations or governance measures relating to the risk subdomain are described.

• Unfair discrimination and misrepresentation
• Unequal performance across groups
• Compromise of privacy
• False or misleading information
• Overreliance and unsafe use

All other risk subdomains had no coverage in this document.

Risk Coverage Summary

The document has good coverage of approximately 12-14 subdomains, with strong focus on AI system security (2.2), malicious actors (4.1, 4.2, 4.3), governance failure (6.5), and AI safety failures (7.1, 7.2, 7.3, 7.4). Coverage is concentrated in security, misuse prevention, AI safety, and governance domains, reflecting Google DeepMind's comprehensive approach to frontier AI safety.

Sector coverage

Good coverage — Comprehensive governance measures or mitigations with clear procedures relating to the sector are explicitly described.

• Information
• Scientific Research & Development Services

Minimal coverage — Brief mention but no specific mitigations, recommendations or governance measures relating to the sector are described.

• Educational Services
• Health Care & Social Assistance

All other sectors had no coverage in this document.

Sectors Summary

This is an internal corporate policy document from Google DeepMind, an AI development company. The sectors governed are primarily Information (where Google DeepMind operates as an AI developer) and Scientific Research and Development Services (where they conduct AI research). The document also discusses AI applications across multiple sectors including healthcare, education, and climate/energy, but these are examples of beneficial use cases rather than sectors being governed by this policy.

Legislative Status

Other

Legislative Status Summary

This is an internal corporate policy document from Google DeepMind outlining voluntary commitments and responsible AI practices. It describes the company's own governance structures, safety processes, and research priorities rather than binding legal obligations.

Actors

Proposer

• Entity Types: AI_Developer
• Entities: Google DeepMind; Google
• Summary: This document is authored by Google DeepMind in response to UK government questions. Google DeepMind is proposing and describing their own internal AI safety and responsibility framework.

Target

• Entity Types: AI_Developer
• Entities: Google DeepMind; Google; frontier AI developers
• Summary: The document primarily describes internal governance processes that apply to Google DeepMind's own AI development activities. It also references broader expectations for frontier AI developers.

Enforcer

• Entity Types: AI_Developer
• Entities: Responsible AI Council; Responsibility and Safety Council (RSC); Google DeepMind senior leaders
• Summary: The document describes internal governance bodies within Google that enforce the AI Principles and safety standards. These are internal corporate enforcement mechanisms rather than external regulatory bodies.

Monitor

• Entity Types: AI_Developer, AI_Governance_Actor
• Entities: Google DeepMind internal teams; Frontier AI Taskforce (UK); Partnership on AI; Frontier Model Forum
• Summary: The document describes both internal monitoring by Google DeepMind teams and external monitoring through collaborative bodies and government taskforces.

AI Lifecycle Stages

Lifecycle stages covered by the documents, as defined in the OECD Framework for the Classification of AI Systems

• Plan and Design
• Collect and Process Data
• Build and Use Model
• Verify and Validate
• Deploy
• Operate and Monitor

AI Lifecycle Summary

The document comprehensively covers all AI lifecycle stages, with particularly strong emphasis on Build and Use Model, Verify and Validate, and Operate and Monitor stages. It describes end-to-end processes from planning through post-deployment monitoring.

Technical Scope

Terms relating to technical scope that are mentioned or implicitly referenced in the document

• AI Models
• Foundation Models
• Frontier AI
• AI Systems
• General Purpose AI
• Generative AI
• Open Weight / Open Source

Technical Scope Summary

The document explicitly addresses AI models and AI systems, with strong focus on frontier AI models and foundation models. It discusses general-purpose models extensively but does not explicitly mention task-specific AI, predictive AI, or compute thresholds. There is implicit coverage of open-weight models through discussion of model weight security.