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What is the point of fairness?: disability, AI and the complexity of justice

Authors:

Cynthia L. Bennett,

Os KeyesAuthors Info & Claims

ACM SIGACCESS Accessibility and Computing, Issue 125

Article No.: 5, Page 1

https://doi.org/10.1145/3386296.3386301

Published: 02 March 2020 Publication History

Abstract

Work integrating conversations around AI and Disability is vital and valued, particularly when done through a lens of fairness. Yet at the same time, analysing the ethical implications of AI for disabled people solely through the lens of a singular idea of "fairness" risks reinforcing existing power dynamics, either through reinforcing the position of existing medical gatekeepers, or promoting tools and techniques that benefit otherwise-privileged disabled people while harming those who are rendered outliers in multiple ways. In this paper we present two case studies from within computer vision - a subdiscipline of AI focused on training algorithms that can "see" - of technologies putatively intended to help disabled people but, through failures to consider structural injustices in their design, are likely to result in harms not addressed by a "fairness" framing of ethics. Drawing on disability studies and critical data science, we call on researchers into AI ethics and disability to move beyond simplistic notions of fairness, and towards notions of justice.

References

[1]

Elizabeth S. Anderson. 1999. What is the Point of Equality?. Ethics 109, 2 (January 1999), 287-337.

[2]

Douglas Astler, Harrison Chau, Kailin Hsu, Alvin Hua, Andrew Kannan, Lydia Lei, Melissa Nathanson, Esmaeel Paryavi, Michelle Rosen, Hayato Unno, Carol Wang, Khadija Zaidi, Xuemin Zhang, and Cha-Min Tang. 2011. Increased accessibility to nonverbal communication through facial and expression recognition technologies for blind/visually impaired subjects. In Proceedings of the 13th international ACM SIGACCESS conference on Computers and accessibility (ASSETS '11). ACM, New York, NY, USA, 259-260.

Digital Library

[3]

Olivia Banner. 2019. Technopsyence and Afro-Surrealism's Cripistemologies. Catalyst: Feminism, Theory, Technoscience. 5, 1 (2019).

[4]

Sander Begeer, Saloua El Bouk, Wafaa Boussaid, Mark Meerum Terwogt, and Hans M. Koot. 2009. Underdiagnosis and referral bias of autism in ethnic minorities. J Autism Dev Disord. 39, 1 (January 2009), 142-148.

[5]

Hendrik Buimer, Thea Van der Geest, Abdellatif Nemri, Renske Schellens, Richard Van Wezel, and Yan Zhao. 2017. Making Facial Expressions of Emotions Accessible for Visually Impaired Persons. In Proceedings of the 19th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS '17). ACM, New York, NY, USA, 331-332.

Digital Library

[6]

Adele E. Clark, Janet K. Shim, Laura Mamo, Jennifer Ruth Fosket, and Jennifer R. Fishman. 2010. Biomedicalization: Technoscientific transformations of health, illness, and US biomedicine. In Biomedicalization: Technoscience, health, and illness in the US (2010), 47-87.

[7]

Peter Conrad. 1992. Medicalization and social control. Annual Review of Sociology 18, 1 (August 1992), 209-232.

[8]

Terrance DeVries, Ishan Misra, Changhan Wang, and Laurens van der Maaten. 2019. Does Object Recognition Work for Everyone?. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 52-59.

[9]

Leah Findlater, Lee Stearns, Ruofei Du, Uran Oh, David Ross, Rama Chellappa, and Jon Froehlich. 2015. Supporting Everyday Activities for Persons with Visual Impairments Through Computer Vision-Augmented Touch. In Proceedings of the 17th International ACM SIGACCESS Conference on Computers & Accessibility (ASSETS '15). ACM, New York, NY, USA, 383-384.

Digital Library

[10]

Ellen Giarelli, Lisa D. Wiggins, Catherine E. Rice, Susan E. Levy, Russell S. Kirby, Jennifer Pinto-Martin, and David Mandell. 2010. Sex differences in the evaluation and diagnosis of autism spectrum disorders among children. Disabil. Health J. 3, 2 (April 2010), 107-116.

[11]

Jordan Hashemi, Mariano Tepper, Thiago Vallin Spina, Amy Esler, Vassilios Morellas, Nikolaos Papanikolopoulos, Helen Egger, Geraldine Dawson, and Guillermo Sapiro. 2014. Computer vision tools for low-cost and noninvasive measurement of autism-related behaviors in infants. Autism research and treatment (2014).

[12]

Anna Lauren Hoffmann. (2019) Where fairness fails: Data, algorithms, and the limits of antidiscrimination discourse. Information, Communication, & Society, 22, 7 (2019), 900-915.

[13]

Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. In Proc. ACM Hum.-Comput. Interact. 2, CSCW, Article 88 (November 2018), 22 pages.

Digital Library

[14]

Os Keyes, Jevan Hutson, and Meredith Durbin. 2019. A Mulching Proposal: Analysing and Improving an Algorithmic System for Turning the Elderly into High-Nutrient Slurry. In Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems (CHI EA '19). ACM, New York, NY, USA, Paper alt06, 11 pages.

Digital Library

[15]

Marco Leo, G. Medioni, M. Trivedi, Takeo Kanade, and Giovanni Maria Farinella. 2017. Computer vision for assistive technologies. Computer Vision and Image Understanding 154 (January 2017), 1-15.

[16]

Haley MacLeod, Cynthia L. Bennett, Meredith Ringel Morris, and Edward Cutrell. 2017. Understanding Blind People's Experiences with Computer-Generated Captions of Social Media Images. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (CHI '17). ACM, New York, NY, USA, 5988-5999.

Digital Library

[17]

David S. Mandell, Maytali M. Novak, and Cynthia D. Zubritsky. 2005. Factors associated with age of diagnosis among children with autism spectrum disorders. Pediatrics 116, 6 (December 2005) 1480.

[18]

Jennifer Mankoff, Gillian R. Hayes, and Devva Kasnitz. 2010. Disability studies as a source of critical inquiry for the field of assistive technology. In Proceedings of the 12th international ACM SIGACCESS conference on Computers and accessibility (ASSETS '10). ACM, New York, NY, USA, 3-10.

Digital Library

[19]

Bernard Metz, James A. Mulick, and Eric M. Butter. Autism: A late-20th-century fad magnet. Controversial therapies for developmental disabilities: Fad, fashion and science in professional practice. 237-263, 2005.

[20]

Microsoft. 2017. Seeing AI: Talking Camera App for Those with a Visual Impairment (July 2017). Retrieved 30 June, 2019 from https://www.microsoft.com/en-us/ai/seeing-ai

[21]

Davide Mulfari. 2018. A TensorFlow-based Assistive Technology System for Users with Visual Impairments. In Proceedings of the Internet of Accessible Things (W4A '18). ACM, New York, NY, USA, Article 11, 2 pages.

Digital Library

[22]

Halley Profita, Reem Albaghli, Leah Findlater, Paul Jaeger, and Shaun K. Kane. 2016. The AT Effect: How Disability Affects the Perceived Social Acceptability of Head-Mounted Display Use. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (CHI '16). ACM, New York, NY, USA, 4884-4895.

Digital Library

[23]

Shyam Rajagopalan, Abhinav Dhall, and Roland Goecke. 2013. Self-stimulatory behaviours in the wild for autism diagnosis. In Proceedings of the IEEE International Conference on Computer Vision Workshops, 755-761.

Digital Library

[24]

James M. Rehg. Behavior Imaging: Using Computer Vision to Study Autism. In Proceedings of the 2011 IAPR Conference on Machine Vision Applications, 14-21.

[25]

Tessa Taylor Rivet and Johnny L. Matson. 2011. Review of gender differences in core symptomatology in autism spectrum disorders. Research in Autism Spectrum Disorders 5, 3 (July 2011), 957-976.

[26]

Ginny Russell. Early Diagnosis of Autism. Re-thinking Autism: Diagnosis, Identity and Equality 252, 2016.

[27]

Huiying Shen, Owen Edwards, Joshua Miele, and James M. Coughlan. 2013. CamIO: a 3D computer vision system enabling audio/haptic interaction with physical objects by blind users. In Proceedings of the 15th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS '13). ACM, New York, NY, USA, Article 41, 2 pages.

Digital Library

[28]

Jerome Thevenot, Miguel Bordallo López, and Abdenour Hadid. 2017. A survey on computer vision for assistive medical diagnosis from faces. IEEE journal of biomedical and health informatics 22, 5 (October 2017), 1497-1511.

[29]

Sami Timimi, Brian McCabe, K. Runswick-Cole, R. Mallett, and S. Timimi. Autism screening and diagnostic tools. Re-thinking Autism: Diagnosis, Identity and Equality 159-183, 2016.

[30]

Shari Trewin. 2018. AI fairness for people with disabilities: point of view. arXiv preprint arXiv: 1811.10670

[31]

Bonnie Tucker. 2017. Technocapitalist disability rhetoric: When technology is confused with social justice. Enculturation 24 (April 2017).

[32]

Kylie Valentine. 2010. A consideration of medicalisation: Choice, engagement and other responsibilities of parents of children with autism spectrum disorder. Social Science & Medicine 71, 5 (September 2010) 950-957.

[33]

Mitzi Waltz. 2008. Autism= death: The social and medical impact of a catastrophic medical model of autistic spectrum disorders. Popular narrative media 1, 1 (2008), 13-24.

[34]

Linda Wang, and Alexander Wong. 2019. Implications of Computer Vision Driven Assistive Technologies Towards Individuals with Visual Impairment. arXiv preprint arXiv:1905.07844

[35]

Rua M. Williams and Juan E. Gilbert. 2019. Cyborg Perspectives on Computing Research Reform. In Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems (CHI EA '19). ACM, New York, NY, USA, Paper alt13, 11 pages.

Digital Library

[36]

World Institute on Disability. 2019. AI and Accessibility (July 2019). Retrieved 23 June, 2019 from https://wid.org/2019/06/12/ai-and-accessibility/

[37]

Yuhang Zhao, Cynthia L. Bennett, Hrvoje Benko, Edward Cutrell, Christian Holz, Meredith Ringel Morris, and Mike Sinclair. 2018. Enabling People with Visual Impairments to Navigate Virtual Reality with a Haptic and Auditory Cane Simulation. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI '18). ACM, New York, NY, USA, Paper 116, 14 pages.

Digital Library

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Froehlich JLi CHosseini MMiranda FSevtsuk AEisenberg Y(2024)The Future of Urban Accessibility: The Role of AIProceedings of the 26th International ACM SIGACCESS Conference on Computers and Accessibility10.1145/3663548.3688550(1-6)Online publication date: 27-Oct-2024
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Information & Contributors

Information

Published In

cover image ACM SIGACCESS Accessibility and Computing

ACM SIGACCESS Accessibility and Computing Just Accepted

ASSETS 2019 Workshop: AI Fairness for People with Disabilities

October 2019

48 pages

ISSN:1558-2337

EISSN:1558-1187

DOI:10.1145/3386296

Editor:
André Rodrigues
University of Lisbon

Issue’s Table of Contents

Copyright © 2020 Copyright is held by the owner/author(s).

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Association for Computing Machinery

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Published: 02 March 2020

Published in SIGACCESS , Issue 125

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Cited By

Froehlich JLi CHosseini MMiranda FSevtsuk AEisenberg Y(2024)The Future of Urban Accessibility: The Role of AIProceedings of the 26th International ACM SIGACCESS Conference on Computers and Accessibility10.1145/3663548.3688550(1-6)Online publication date: 27-Oct-2024
https://dl.acm.org/doi/10.1145/3663548.3688550
Bennett CShelby RRostamzadeh NKane S(2024)Painting with Cameras and Drawing with Text: AI Use in Accessible CreativityProceedings of the 26th International ACM SIGACCESS Conference on Computers and Accessibility10.1145/3663548.3675644(1-19)Online publication date: 27-Oct-2024
https://dl.acm.org/doi/10.1145/3663548.3675644
Darling-Wolf HPatitsas E(2024)"Not my Priority:" Ethics and the Boundaries of Computer Science Identities in Undergraduate CS EducationProceedings of the ACM on Human-Computer Interaction10.1145/36410138:CSCW1(1-28)Online publication date: 26-Apr-2024
https://dl.acm.org/doi/10.1145/3641013
Shelby RSrinivasan RBurgdorf KLena JRostamzadeh N(2024)Creative ML Assemblages: The Interactive Politics of People, Processes, and ProductsProceedings of the ACM on Human-Computer Interaction10.1145/36373158:CSCW1(1-30)Online publication date: 26-Apr-2024
https://dl.acm.org/doi/10.1145/3637315
Simson JFabris AKern C(2024)Lazy Data Practices Harm Fairness ResearchProceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency10.1145/3630106.3658931(642-659)Online publication date: 3-Jun-2024
https://dl.acm.org/doi/10.1145/3630106.3658931
Rizvi NWu WBolds MMondal RBegel AMunyaka I(2024)Are Robots Ready to Deliver Autism Inclusion?: A Critical ReviewProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642798(1-18)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642798
Chordia IBaltaxe-Admony LBoone ASheehan ADombrowski LLe Dantec CRingland KSmith A(2024)Social Justice in HCI: A Systematic Literature ReviewProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642704(1-33)Online publication date: 11-May-2024
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Shelby RRismani SHenne KMoon ARostamzadeh NNicholas PYilla-Akbari NGallegos JSmart AGarcia EVirk G(2023)Sociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm ReductionProceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society10.1145/3600211.3604673(723-741)Online publication date: 8-Aug-2023
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Aler Tubella ACoelho Mollo DDahlgren Lindström ADevinney HDignum VEricson PJonsson AKampik TLenaerts TMendez JNieves J(2023)ACROCPoLis: A Descriptive Framework for Making Sense of FairnessProceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency10.1145/3593013.3594059(1014-1025)Online publication date: 12-Jun-2023
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Greiffenhagen CXu XReeves S(2023)The Work to Make Facial Recognition WorkProceedings of the ACM on Human-Computer Interaction10.1145/35795317:CSCW1(1-30)Online publication date: 16-Apr-2023
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