Evidence record 19185 · automatically gathered

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

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

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).

JSON

Use and limitations

This page is a stable index and citation surface for a source record. ethics.ai did not author the underlying report and has not independently verified every claim. Automatic topics may be imperfect. For consequential use, quote and cite the original publisher.