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June 13, 20260 citationsOpen Access

Making Bias Visible: Algorithmic Hiring and Governance in Recruitment

Making Bias Visible: Algorithmic Hiring and the Role of Governance in Early-Stage Recruitment

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Authors

RHRaven Heyward

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Overview

Comparative analysis of governance models for bias in AI hiring, revealing significant equity gaps.

Key Points

  • This research examines how governance models affect bias in algorithmic hiring practices during early-stage recruitment.
  • Comparative analysis of New York City's Local Law 144 and North Carolina's Responsible AI Framework.
  • Assessment of audit documentation and regulatory guidance.
  • Evaluation of the impact of mandatory versus voluntary governance on AI hiring practices.
  • Limited oversight in voluntary frameworks obscures algorithmic decision-making.
  • Significant gaps noted in transparency and accountability measures in AI hiring.
  • Findings indicate that governance frameworks directly influence economic opportunity access.
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Cite This Study

Raven Heyward (2026) studied this question.

synapsesocial.com/papers/6a2cf4aefaef96ed7f056e2ehttps://doi.org/10.17615/2w5a-zm70
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