mlsanityData to 14 Oct 2026

Toward Fairness in AI for People with Disabilities: A Research Roadmap

arXiv 1907.02227 ↗First posted 4 Jul 2019cs.CY cs.AI cs.HCcited by 22

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Abstract (arXiv)

AI technologies have the potential to dramatically impact the lives of people with disabilities (PWD). Indeed, improving the lives of PWD is a motivator for many state-of-the-art AI systems, such as automated speech recognition tools that can caption videos for people who are deaf and hard of hearing, or language prediction algorithms that can augment communication for people with speech or cognitive disabilities. However, widely deployed AI systems may not work properly for PWD, or worse, may actively discriminate against them. These considerations regarding fairness in AI for PWD have thus far received little attention. In this position paper, we identify potential areas of concern regarding how several AI technology categories may impact particular disability constituencies if care is not taken in their design, development, and testing. We intend for this risk assessment of how various classes of AI might interact with various classes of disability to provide a roadmap for future research that is needed to gather data, test these hypotheses, and build more inclusive algorithms.

Key facts. Cited by 22 papers in the map (data through 14 Oct 2026). First posted on arXiv 4 Jul 2019.

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Citing papers per year: 2021: 6; 2022: 6; 2023: 0; 2024: 6; 2025: 1; 2026: 3.

22 papers.

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  1. 2022Characteristics of Harmful Text: Towards Rigorous Benchmarking of Language Modelscited by 49
  2. 2021Intersectional Bias in Causal Language Modelscited by 24
  3. 2022Hey ASR System! Why Aren't You More Inclusive? Automatic Speech Recognition Systems' Bias and Proposed Bias Mitigation Techniques. A Literature Reviewcited by 19
  4. 2021ASR4REAL: An extended benchmark for speech modelscited by 14
  5. 2021Spatiotemporal Data Mining: A Survey on Challenges and Open Problemscited by 13
  6. 2021Identification of Bias Against People with Disabilities in Sentiment Analysis and Toxicity Detection Modelscited by 13
  7. 2024The Call for Socially Aware Language Technologiescited by 13
  8. 2024Lazy Data Practices Harm Fairness Researchcited by 10
  9. 2021Equity and Artificial Intelligence in Education: Will "AIEd" Amplify or Alleviate Inequities in Education?cited by 9
  10. 2022Data Representativeness in Accessibility Datasets: A Meta-Analysiscited by 6
  11. 2024WheelPose: Data Synthesis Techniques to Improve Pose Estimation Performance on Wheelchair Userscited by 5
  12. 2024WheelPoser: Sparse-IMU Based Body Pose Estimation for Wheelchair Userscited by 5
10 more
  1. 2022Closed-Loop View of the Regulation of AI: Equal Impact across Repeated Interactionscited by 3
  2. 2022Comparison and Analysis of New Curriculum Criteria for End-to-End ASRcited by 2
  3. 2022Areas of Strategic Visibility: Disability Bias in Biometricscited by 1
  4. 2025Accessibility Considerations in the Development of an AI Action Plancited by 1
  5. 2021Controllable Response Generation for Assistive Use-casescited by 0
  6. 2024Text-to-Image Representativity Fairness Evaluation Frameworkcited by 0
  7. 2024Analyzing Fairness of Computer Vision and Natural Language Processing Modelscited by 0
  8. 2026Investigating Disability Representations in Text-to-Image Modelscited by 0
  9. 2026Cripping AI: Reimagining AI Through Lived Disability Experiencescited by 0
  10. 2026Knowing Is Not Telling: Identity Ossification in LLM Representations of Trans-border Communitiescited by 0