Los Angeles AI Roadmap 2024, Best Practices and Roadmap

• Authority: Los Angeles, CA
• Parent authority: Local governments
• Jurisdiction: United States
• Collections: U.S. state and local documents
• Most recent activity: Enacted
• Most recent activity date: 2024-06-04

Risk subdomain coverage

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

• Compromise of privacy
• AI system security vulnerabilities
• 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
• Fraud, scams, and targeted manipulation
• Overreliance and unsafe use
• Loss of human agency and autonomy
• Environmental harm

All other risk subdomains had no coverage in this document.

Risk Coverage Summary

The document has minimal to good coverage of approximately 6-8 subdomains, with primary focus on AI system security (2.2), lack of capability/robustness (7.3), lack of transparency (7.4), and ethical considerations around discrimination (1.1). Coverage is concentrated in technical safety, security, and ethical AI deployment domains, with emphasis on training, data quality, and human-centered design.

Sector coverage

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

• Public Administration (excl. National Security)

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

• Information
• Finance & Insurance
• Management, Administrative & Support Services
• Health Care & Social Assistance

All other sectors had no coverage in this document.

Sectors Summary

This document primarily governs AI use within Public Administration (excluding National Security), as it is an internal policy for Los Angeles city government operations. It has minimal implicit coverage of other sectors through mentioned use cases like healthcare data and environmental monitoring, but these are not substantively governed by the document.

Legislative Status

Other

Legislative Status Summary

This is an internal municipal government policy document and roadmap that provides recommendations and implementation plans for AI adoption within Los Angeles city departments. It lacks formal enforcement mechanisms, penalties, or binding legal obligations characteristic of hard law.

Actors

Proposer

• Entity Types: AI_Governance_Actor
• Entities: Information Technology Agency (ITA); City of Los Angeles
• Summary: The document explicitly states it was developed by the Information Technology Agency (ITA) for the City of Los Angeles, with research from industry experts and consultants.

Target

• Entity Types: AI_Deployer, AI_User
• Entities: City of Los Angeles departments; City employees; IT Professionals; City Managers
• Summary: The document targets two distinct user segments: City employees and managers who will use AI tools, and IT professionals who will develop or configure AI tools for City departments.

Enforcer

• Entity Types: AI_Governance_Actor
• Entities: Information Technology Agency (ITA); City Attorney
• Summary: The ITA is responsible for implementing the roadmap and incorporating AI requirements into existing policies. The City Attorney is mentioned for contract review to ensure data ownership and controls.

Monitor

• Entity Types: AI_Governance_Actor
• Entities: Information Technology Agency (ITA); City departments
• Summary: The ITA is responsible for monitoring AI trends and implementation. The document also establishes monitoring through incorporation into existing policies and training programs.

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 particular emphasis on Plan and Design (setting objectives before deployment), Build and Use Model (training requirements, data quality), Verify and Validate (proof of concept requirements), Deploy (implementation roadmap), and Operate and Monitor (dynamic adaptation, ongoing refinement). It provides detailed guidance across the entire lifecycle from planning through operational monitoring.

Technical Scope

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

• AI Models
• AI Systems
• Generative AI
• Task-specific AI

Technical Scope Summary

The document explicitly mentions AI tools, AI models, and AI systems throughout. It does not specifically reference frontier AI, general purpose AI, foundation models, or compute thresholds. It implicitly covers generative AI through specific tools like Google Gemini and Adobe Firefly. The document focuses on practical AI implementation rather than technical AI categorizations.