A Bill in the District of Columbia to prohibit users of algorithmic decision-making from utilizing algorithmic eligibility determinations in a discriminatory manner, to require corresponding notices to individuals whose personal information is used, and…

• Authority: District of Columbia
• Parent authority: State governments
• Jurisdiction: United States
• Collections: U.S. state and local documents
• Most recent activity: Proposed
• Most recent activity date: 2023-02-10

Risk subdomain coverage

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

• Unfair discrimination and misrepresentation
• Unequal performance across groups
• Compromise of privacy
• 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.

• AI system security vulnerabilities
• Loss of human agency and autonomy
• Increased inequality and decline in employment
• Governance failure

All other risk subdomains had no coverage in this document.

Risk Coverage Summary

The document has good coverage of approximately 6-8 subdomains, with strong focus on unfair discrimination (1.1), unequal performance across groups (1.3), privacy compromise (2.1), security vulnerabilities (2.2), lack of transparency (7.4), and lack of robustness (7.3). Coverage is concentrated in discrimination/toxicity, privacy/security, and AI system safety domains.

Sector coverage

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

• Finance & Insurance
• Real Estate, Rental & Leasing
• Educational Services

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

• Information
• Professional & Technical Services
• Management, Administrative & Support Services
• Accommodation, Food & Other Services
• Public Administration (excl. National Security)

All other sectors had no coverage in this document.

Sectors Summary

The document governs algorithmic decision-making across multiple sectors where 'important life opportunities' are determined, with explicit coverage of employment, housing, credit/finance, insurance, education, and public accommodations. The regulation applies to any covered entity making algorithmic decisions in these areas within the District of Columbia.

Legislative Status

Hard Law

Legislative Status Summary

This is a binding legislative bill with mandatory obligations, civil penalties up to $10,000 per violation, enforcement by the Attorney General, and private right of action. The document uses mandatory language throughout ('shall') and establishes formal enforcement mechanisms.

Actors

Proposer

• Entity Types: AI_Governance_Actor
• Entities: Council of the District of Columbia
• Summary: The bill is proposed by the Council of the District of Columbia, which is the legislative body for the District. The document explicitly states this in the title and findings section.

Target

• Entity Types: AI_Developer, AI_Deployer
• Summary: The bill targets 'covered entities' which are defined as organizations that make algorithmic eligibility or information availability determinations, or rely on such determinations from service providers. This includes both developers of algorithmic systems and deployers who use them for decision-making about employment, housing, credit, insurance, and other important life opportunities.

Enforcer

• Entity Types: AI_Governance_Actor
• Entities: Attorney General for the District of Columbia; Office of the Attorney General; Superior Court of the District of Columbia
• Summary: The Attorney General for the District of Columbia is designated as the primary enforcement authority with power to bring civil actions, issue subpoenas, and impose penalties. The Superior Court of the District of Columbia serves as the judicial enforcement body.

Monitor

• Entity Types: AI_Governance_Actor, AI_Deployer
• Entities: Office of the Attorney General for the District of Columbia
• Summary: The Office of the Attorney General receives annual audit reports from covered entities. Additionally, covered entities themselves are required to conduct ongoing monitoring through annual audits and impact assessments of their algorithmic systems.

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 primarily addresses the Deploy and Operate and Monitor stages of the AI lifecycle, with some coverage of Verify and Validate. It focuses on algorithmic systems already in use for decision-making, requiring ongoing audits, impact assessments, and monitoring for discriminatory effects. There is minimal coverage of earlier stages like planning, data collection, or model building.

Technical Scope

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

• AI Models
• AI Systems

Technical Scope Summary

The document explicitly covers AI systems and algorithmic processes that utilize machine learning and artificial intelligence for decision-making. It does not distinguish between different types of AI (frontier, general purpose, task-specific, foundation models, generative, or predictive) and does not mention compute thresholds or open-weight models. The focus is on algorithmic decision-making systems broadly defined.