Automated Employment Bureau (AEB)

A Balanced and Safe Approach to AI Governance in Employment

Authors

  • Kwame Nyarkoh-Ocran Stanford University
  • Chijioke Mgbahurike Stanford University

DOI:

https://doi.org/10.60690/nxpjw427

Keywords:

Tech policy, AI Governance, AI Ethics, Law and Policy in AI Decision Making, Labor and AI, Technology Regulation, Tech Accountability

Abstract

Artificial intelligence is increasingly used to screen applicants, rank candidates, evaluate performance, and support termination decisions. While these tools promise efficiency, they also scale risks that are difficult for workers and applicants to detect or contest, including discrimination, opaque decision logic, and error at high volume. Existing civil-rights and labor protections remain essential, but their effectiveness depends on transparency and technical capacity that many automated systems do not provide. At the same time, emerging state and local regulations create a fragmented landscape with uneven protections and inconsistent compliance requirements.

This memo proposes the creation of a federal regulator, the Automated Employment Bureau (AEB), housed within the Department of Labor to establish baseline national standards for AI systems used in employment decisions. The proposed framework centers on four core functions: standards and certification, independent audits and ongoing monitoring, transparency and notice requirements, and enforceable redress and enforcement mechanisms. By pairing technical oversight with civil-rights enforcement and periodic updating, AEB would reduce discriminatory outcomes, strengthen due process, and provide consistent national expectations while preserving space for responsible innovation.

Author Biographies

  • Kwame Nyarkoh-Ocran, Stanford University

    Kwame is a current senior and Master’s student at Stanford University studying electrical engineering, linguistics, and computer science. He’s a jack-of-all-trades, with broad interests in tech policy and governance, historical and sociolinguistics, embedded systems, chip and product design, and pop culture. He hopes to contribute to the movement towards more equitable, sustainable, and socially conscious technological advancement.

  • Chijioke Mgbahurike, Stanford University

    Chijioke is a Master’s student at Stanford University studying computer science specializing in artificial intelligence and speech technologies with an emphasis on accents, bias, and inclusion. He is interested in the mechanisms of AI and its socio-technical mechanisms and how such systems interact with public discourse, policy, and overall tech inertia. He dreams to make technology ever more accountable for the people it serves.

diverse people presented in American Gothic style holding employment contracts. LLM generated.

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Published

2026-01-24

Issue

Vol. 4 No. 1 (2026): Governing the Generative Age: Student Policy Proposals on Artificial Intelligence

Section

Social Impact Papers