Guidance on Algorithmic Discrimination and the New Jersey Law Against Discrimination

• Authority: New Jersey
• Parent authority: State governments
• Jurisdiction: United States
• Collections: U.S. state and local documents
• Most recent activity: Enacted
• Most recent activity date: 2025-01-08

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

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

• Lack of capability or robustness
• Lack of transparency or interpretability

All other risk subdomains had no coverage in this document.

Risk Coverage Summary

The document has good coverage of approximately 3-4 subdomains, with strong focus on unfair discrimination and misrepresentation (1.1), unequal performance across groups (1.3), and lack of transparency (7.4). Coverage is concentrated in discrimination and toxicity domains, with some attention to AI system limitations.

Sector coverage

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

• Real Estate, Rental & Leasing
• Professional & Technical Services

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

• Agriculture, Mining, Construction & Manufacturing
• Trade, Transportation & Utilities
• Finance & Insurance
• Management, Administrative & Support Services
• Accommodation, Food & Other Services

All other sectors had no coverage in this document.

Sectors Summary

The document governs AI use across multiple sectors including employment (Professional and Technical Services, all sectors with employers), housing (Real Estate), retail and services (Trade, Accommodation and Food Services), finance (Finance and Insurance), and public services. The guidance applies broadly to any sector where covered entities operate under the LAD.

Legislative Status

Hard Law

Legislative Status Summary

This is binding legal guidance interpreting an existing statute (New Jersey Law Against Discrimination) with enforcement mechanisms and mandatory compliance obligations for covered entities.

Actors

Proposer

• Entity Types: AI_Governance_Actor
• Entities: New Jersey Office of the Attorney General; Division on Civil Rights (DCR)
• Summary: The document is issued jointly by the New Jersey Office of the Attorney General and the Division on Civil Rights to provide interpretive guidance on how the LAD applies to algorithmic discrimination.

Target

• Entity Types: AI_Deployer
• Entities: employers; housing providers; places of public accommodation; credit providers; contractors
• Summary: The guidance explicitly applies to covered entities under the LAD, which include employers, housing providers, places of public accommodation, credit providers, and contractors who use automated decision-making tools.

Enforcer

• Entity Types: AI_Governance_Actor
• Entities: Division on Civil Rights (DCR)
• Summary: The Division on Civil Rights is identified as the enforcement body that receives and processes discrimination complaints under the LAD.

Monitor

• Entity Types: AI_Governance_Actor
• Entities: Division on Civil Rights (DCR)
• Summary: The Division on Civil Rights monitors compliance through its complaint intake process and ongoing oversight of LAD compliance, though specific monitoring mechanisms are not detailed in this guidance document.

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 addresses multiple lifecycle stages with primary focus on deployment and operation/monitoring. It emphasizes the need for careful evaluation during design and testing phases, and ongoing analysis after deployment to prevent discriminatory outcomes.

Technical Scope

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

• AI Systems
• Task-specific AI

Technical Scope Summary

The document uses the term 'automated decision-making tools' throughout and explicitly mentions AI. It does not distinguish between different types of AI systems, models, or technical specifications such as compute thresholds. The focus is on the functional use of automated tools in decision-making contexts.