Discrimination and AI in the workplace



Published
Discrimination in hiring and at work is longstanding and widespread. A meta-analysis of 30 years of experiments in the United States found that white job applicants were 36% more likely to receive a callback than equally qualified African Americans, and 24% more likely than Latinos – with little significant evolution between 1989 and 2015 .

As AI systems are increasingly used in recruitment and hiring, as well as in worker management and evaluation, they have the potential to contribute to reducing discrimination at work by formalizing rules in management processes. Yet AI systems often struggle with bias, both at the system level and at the data or input level, and risk replicating biases at scale, reinforcing historical patterns of disadvantage.

This panel will focus on potential policy responses. Are existing anti-discrimination laws sufficient? Or is there a need for new legislation (e.g. banning certain use types, or mandating bias audits)?

Moderator: Emma Nelson, journalist

Panellists:
• Joanna Goodey, Head of Research and Data Unit, European Union Agency for Fundamental Rights
• Keith Sonderling, Commissioner, United States Equal Employment Opportunity Commission
• Lorraine Finlay, Commissioner, Australian Human Rights Commission
• Pauline Kim, Professor of Law, Washington University in St. Louis

Closing remarks by Stefano Scarpetta, Director for Employment, Labour, and Social Affairs, OECD.

The live session time above reflects your computer's local time zone. The session will be recorded and available on replay the day after the live stream.

Check out some resources from the speakers and institutions on the panel:
• Kim, Pauline, Race-Aware Algorithms: Fairness, Nondiscrimination and Affirmative Action (January 26, 2022). California Law Review, Forthcoming, Washington University in St. Louis Legal Studies Research Paper No. 22-01-02, Available at SSRN: https://ssrn.com/abstract=4018414
• Kim, Pauline, Data-Driven Discrimination at Work (April 19, 2017). William & Mary Law Review, Vol. 48, pp. 857-936 (2017), Washington University in St. Louis Legal Studies Research Paper No. 16-12-01, Available at SSRN: https://ssrn.com/abstract=2801251

• Sonderling, Keith: Is artificial intelligence ready for the great rehiring? (July 29, 2021). World Economic Forum, Available at: https://www.weforum.org/agenda/2021/07/is-ai-ready-for-the-great-rehiring/

• Sonderling, Keith: How People Analytics Can Prevent Algorithmic Bias (December 6, 2021). International Association for Human Resource Information Management, Issue 4, Available at: https://www.ihrim.org/2021/12/how-people-analytics-can-prevent-algorithmic-bias-by-commissioner-keith-e-sonderling/

• European Union Agency for Fundamental Rights: Getting the future right – Artificial intelligence and fundamental rights (December 14, 2020). Available at: https://fra.europa.eu/en/publication/2020/artificial-intelligence-and-fundamental-rights

• Australian Human Rights Commission: Human Rights and Technology Final Report (May 27, 2021). Available at: https://humanrights.gov.au/our-work/rights-and-freedoms/publications/human-rights-and-technology-final-report-2021
Category
Job
Be the first to comment