AI and Inequality in Hiring and Recruiting: A Field Scan

Lade...
Vorschaubild
Datum
2023
Herausgeber:innen
Autor:innen
Dinika, Adio-Adet
Sloane, Mona
Zeitschriftentitel
ISSN der Zeitschrift
Bandtitel
Verlag
Weizenbaum Institute
Zusammenfassung

This paper provides a field scan of scholarly work on AI and hiring. It addresses the issue that there still is no comprehensive understanding of how technical, social science, and managerial scholarships around AI bias, recruiting, and inequality in the labor market intersect, particularly vis-à-vis the STEM field. It reports on a semi-systematic literature review and identifies three overlapping meta themes: productivity, gender, and AI bias. It critically discusses these themes and makes recommendations for future work

Beschreibung
Schlagwörter
Artificial Intelligence \ Recruiting \ Inequality \ Stem \ Gender \ Bias
Verwandte Ressource
Verwandte Ressource
Zitierform
Dinika, A.-A., & Sloane, M. (2023). AI and Inequality in Hiring and Recruiting: A Field Scan. Weizenbaum Conference Proceedings 2023. AI, Big Data, Social Media, and People on the Move, 23–35. https://doi.org/10.34669/wi.cp/5.3