HR6371-119

In Committee

No Robot Bosses Act

119th Congress Introduced Dec 3, 2025

Summary

What This Bill Does

The No Robot Bosses Act creates a workplace algorithm accountability regime. It defines automated decision systems broadly to include software, machine learning, statistical, data-processing, and artificial-intelligence tools that determine outcomes, aid decisions, inform policy implementation, or collect observations, while excluding passive infrastructure. Employers may not rely exclusively on an automated decision system for employment-related decisions and may not use an automated decision system output unless the system has predeployment testing for efficacy, discrimination-law compliance, discriminatory impact, and NIST AI Risk Management Framework compliance. Systems must also receive annual independent discriminatory-impact or bias testing with public results. Employers must provide disclosures, meaningful human oversight, plain-language documentation within seven days after an employment decision, a machine-readable copy of input data, an explanation of how the output was used, and accessible dispute and appeal rights to a human reviewer. The bill establishes a Technology and Worker Protection Division at the Labor Department, lets the administrator hire technologists directly and set pay up to Executive Schedule level V, creates user, research, product, and labor advisory boards, authorizes regulations across private-sector, congressional, executive, GAO, Library of Congress, and OPM-covered workplaces, creates investigations and civil actions, coordinates with Federal and State regulators, preserves other Federal and State laws, and includes severability.

Who Benefits and How

Workers, job applicants, labor organizations, disability rights advocates, civil rights advocates, and employees subject to workplace algorithms benefit because employers must test systems, disclose algorithm use, add human oversight, and provide explanations, disputes, and appeals. Independent AI auditors, workplace technology experts, civil-rights lawyers, and Labor Department technologists benefit from new compliance, enforcement, and advisory-board roles.

Who Bears the Burden and How

Employers using hiring, promotion, pay, scheduling, discipline, termination, productivity, or other employment algorithms bear compliance costs for testing, validation, disclosures, human review, recordkeeping, reports, and litigation risk. Workplace AI vendors face pressure to support validation and transparency. The Labor Department, OPM, congressional workplace offices, GAO, Library of Congress, FTC, EEOC, NLRB, and other agencies must write rules, coordinate, investigate, and enforce.

Key Provisions

  • Defines automated decision systems, outputs, candidates, covered individuals, employers, and employment-related decisions.
  • Bars employers from relying exclusively on automated decision systems for employment-related decisions.
  • Requires predeployment validation, annual independent bias testing, public test results, disclosures, human corroboration, documentation, disputes, and appeals.
  • Establishes a Labor Department Technology and Worker Protection Division with direct technologist hiring authority and advisory boards.
  • Requires regulations across private-sector, congressional, executive, GAO, Library of Congress, and Federal employee contexts.
  • Authorizes investigations, reports, civil actions, agency coordination, preservation of stronger laws, and severability.

Evidence Chain:

This summary is generated from the full bill text using AI analysis. Expand "Detailed Analysis" below for identified beneficiaries/burden bearers with clause-level evidence links.

At a Glance

What This Bill Does

Regulates employer use of automated decision systems in employment decisions by requiring predeployment validation, annual bias testing, public test results, worker disclosures, human corroboration, documentation, dispute and appeal rights, a Labor Department Technology and Worker Protection Division, regulations, enforcement, coordination, and preservation of stronger laws.

Key Policy Areas

Labor, Technology, Civil Rights, Artificial Intelligence

Primary Purpose

Regulates employer use of automated decision systems in employment decisions by requiring predeployment validation, annual bias testing, public test results, worker disclosures, human corroboration, documentation, dispute and appeal rights, a Labor Department Technology and Worker Protection Division, regulations, enforcement, coordination, and preservation of stronger laws.

Policy Domains

Labor Technology Civil Rights Artificial Intelligence

Substantive provisions

Identified Gains
  • Workers subject to workplace algorithms
  • Job applicants
  • Labor organizations
  • Disability rights advocates
  • Independent AI auditors
  • Labor Department technologists
Model: codex-gpt-5 | Version: bill_summary_v2 | Source: ih
Job applicants: , , ,
Labor organizations: , , ,
Independent AI auditors: , , ,
Disability rights advocates: , , ,
Labor Department technologists: , , ,
Workers subject to workplace algorithms: , , ,
Identified Costs
  • Employers using automated decision systems
  • Workplace AI vendors
  • Labor Department enforcement staff
  • Federal workplace regulators
  • State workplace regulators
Model: codex-gpt-5 | Version: bill_summary_v2 | Source: ih
Workplace AI vendors: , , ,
State workplace regulators: , , ,
Federal workplace regulators: , , ,
Labor Department enforcement staff: , , ,
Employers using automated decision systems: , , ,

Legislative Progress

In Committee
Introduced Committee Passed
Dec 3, 2025

Ms. Bonamici (for herself, Mr. Deluzio, and Mr. Moylan) introduced …

Dec 3, 2025

Referred to the Committee on Education and Workforce, and in …

Dec 3, 2025

Introduced in House

Stakeholder Effects

cui bono?

How this legislation distributes effects. Mention counts reflect frequency, not effect magnitude.

Government
13 mentions across 6 clauses
+4 positive -9 negative

Equal Employment Opportunity Commission, Federal Trade Commission, Federal workplace regulators

Labor Department enforcement staff faces effects in multiple directions

Positive-direction: Equal Employment Opportunity Commission, Federal Trade Commission, National Labor Relations Board

Negative-direction: Federal workplace regulators, GAO personnel regulators, Labor Department algorithm division, Labor Secretary, Library of Congress workplace regulators, Office of Congressional Workplace Rights, Office of Personnel Management

Labor
10 mentions across 6 clauses
+8 positive ?2 uncertain

Job applicants, Labor organizations, Workers protected by stronger laws

Technology
9 mentions across 6 clauses
+1 positive -5 negative ?3 uncertain

Employers using automated decision systems, Employers using workplace algorithms, Federal technology specialists

Positive-direction: Federal technology specialists

Negative-direction: Employers using automated decision systems, Employers using workplace algorithms, Workplace AI vendors

Professional Services
3 mentions across 3 clauses
+3 positive

Civil rights experts, Independent algorithm auditors, Plaintiffs employment lawyers

State & Local Government
3 mentions across 3 clauses
+1 positive -2 negative

State attorneys general, State workplace regulators

State workplace regulators faces effects in multiple directions

8/10
sections analyzed
Full impact breakdown

Bill Structure & Actor Mappings

Who is "The Secretary" in each section?

Domains
Labor Technology Civil Rights Artificial Intelligence

We use a combination of our own taxonomy and classification in addition to large language models to assess meaning and potential beneficiaries. High confidence means strong textual evidence. Always verify with the original bill text.

Learn more about our methodology