Tackling Algorithmic Disability Discrimination in the Hiring Process: An Ethical, Legal and Technical Analysis

Maarten Buyl · Christina Cociancig · Cristina Frattone · Nele Roekens

80 citations0/0 files storedACM Conference on Fairness, Accountability, and Transparency (FAccT)

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Ethics and Social Impacts of AI Discrimination and Equality Law AI and HR Technologies

Abstract

Tackling algorithmic discrimination against persons with disabilities (PWDs) demands a distinctive approach that is fundamentally different to that applied to other protected characteristics, due to particular ethical, legal, and technical challenges. We address these challenges specifically in the context of artificial intelligence (AI) systems used in hiring processes (or automated hiring systems, AHSs), in which automated assessment procedures are subject to unique ethical and legal considerations and have an undeniable adverse impact on PWDs. In this paper, we discuss concerns and opportunities raised by AI-driven hiring in relation to disability discrimination. Ultimately, we aim to encourage further research into this topic. Hence, we establish some starting points and design a roadmap for ethicists, lawmakers, advocates as well as AI practitioners alike.

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References

2019The global landscape of AI ethics guidelines 2021A Survey on Bias and Fairness in Machine Learning 2018Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor 2017Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy 2014Big Data's Disparate Impact 2019Fairness and Abstraction in Sociotechnical Systems 2017Why a Right to Explanation of Automated Decision-Making Does Not Exist in the General Data Protection Regulation 2022Amazon Scraps Secret AI Recruiting Tool that Showed Bias against Women *

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2024Inherent Limitations of AI Fairness 2025AI and Accessibility: Breaking Barriers for People with Disabilities 2023Creating Accessibility 2.0 with Artificial Intelligence

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