# Areas of Strategic Visibility: Disability Bias in Biometrics

arXiv: https://arxiv.org/abs/2208.04712 · HTML: https://mlsanity.com/paper/2208.04712/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 31 references that are in the map.
- First posted on arXiv 14 Jul 2022.

## Builds on (most cited first, 4 of 4)

- [Principles alone cannot guarantee ethical AI](https://mlsanity.com/paper/1906.06668/) (2019)
- [Towards Accountable AI: Hybrid Human-Machine Analyses for Characterizing System Failure](https://mlsanity.com/paper/1809.07424/) (2018)
- [Toward Fairness in AI for People with Disabilities: A Research Roadmap](https://mlsanity.com/paper/1907.02227/) (2019)
- [Understanding the Representation and Representativeness of Age in AI Data Sets](https://mlsanity.com/paper/2103.09058/) (2021)

## Built on by (most cited first, 1 of 1)

- [Accessibility Considerations in the Development of an AI Action Plan](https://mlsanity.com/paper/2503.14522/) (2025)

## Abstract (arXiv)

This response to the RFI considers the potential for biometrics to help or harm disabled people2. Biometrics are already integrated into many aspects of daily life, from airport travel to mobile phone use. Yet many of these systems are not accessible to people who experience different kinds of disability exclusion . Different personal characteristics may impact any or all of the physical (DNA, fingerprints, face or retina) and behavioral (gesture, gait, voice) characteristics listed in the RFI as examples of biometric signals.