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

arXiv: https://arxiv.org/abs/2206.06149 · HTML: https://mlsanity.com/paper/2206.06149/

## Key facts

- Cited by 10 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Jun 2022.

## Built on by (most cited first, 10 of 10)

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- [Diversity and Inclusion in AI for Recruitment: Lessons from Industry Workshop](https://mlsanity.com/paper/2411.06066/) (2024)
- ["I Hadn't Thought About That": Creators of Human-like AI Weigh in on Ethics And Neurodivergence](https://mlsanity.com/paper/2506.12098/) (2025)
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- [Prompt injections as a tool for preserving identity in GAI image descriptions](https://mlsanity.com/paper/2510.16128/) (2025)
- [Unheard in the Digital Age: Rethinking AI Bias and Speech Diversity](https://mlsanity.com/paper/2601.18641/) (2026)
- [How Supply Chain Dependencies Complicate Bias Measurement and Accountability Attribution in AI Hiring Applications](https://mlsanity.com/paper/2604.22679/) (2026)

## Abstract (arXiv)

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.
