Applied and Filtered: An End-to-End Algorithmic Fairness Audit of A Public Employment Agency
Algorithmic fairness evaluation commonly assesses AI systems as bounded technical components, abstracting away the organizational context in which they operate. We present, to our knowledge, the first independent end-to-end fairness audit of a semi-automated hiring system operated by Barcelona Activa, a public employment agency using the third-party TalentClue platform for candidate search and shortlisting. We analyze approximately 497,000 candidate-vacancy pipeline entries from September 2017 t
Record details
Published: 13 August 2026
Source: arXiv
Category: Research
Topics: Bias & fairness · Jobs & economy · Transparency
Retrieved: 14 August 2026
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How to cite this record
ethics.ai (13 August 2026), “Applied and Filtered: An End-to-End Algorithmic Fairness Audit of A Public Employment Agency,” evidence record 19185, https://ethics.ai/record/19185 (originally published by arXiv).
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