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AI data driven personalisation and disability inclusion

AI data driven personalisation and disability inclusion
AI data driven personalisation and disability inclusion
This paper examines the relationship between the terms ‘Personalisation’ and ‘Classification’ with regard to disability inclusion. Classification using big data struggles to cope with the individual uniqueness of disabled people and whereas developers tend to design for the majority so ignoring outliers, designing for edge cases would be a more inclusive approach. Other issues that are discussed in the paper include: personalising mobile technology accessibility settings with interoperable profiles to allow ubiquitous accessibility; the ethics of using genetic data driven personalisation to ensure babies are not born with disabilities; the importance of including disabled people in decisions to help understand AI implications; the relationship between localisation and personalisation as assistive technologies need localising in terms of language as well as culture; the ways in which AI could be used to create personalised symbols for people who find it difficult to communicate in speech or writing; and whether blind or visually impaired person will be permitted to ‘drive’ an autonomous car. This paper concludes by suggesting that the relationship between the terms ‘Personalisation’ and ‘Classification’ with regards to AI and disability inclusion is a very unique one because of the heterogeneity in contrast to the other protected characteristics and so needs unique solutions.
personalisation, classification‐, localisation, artificial intelligence, Disability
Wald, Mike
90577cfd-35ae-4e4a-9422-5acffecd89d5
Wald, Mike
90577cfd-35ae-4e4a-9422-5acffecd89d5

Wald, Mike (2021) AI data driven personalisation and disability inclusion. Frontiers in Artificial Intelligence-Machine Learning and Artificial Intelligence. (doi:10.3389/frai.2020.571955).

Record type: Article

Abstract

This paper examines the relationship between the terms ‘Personalisation’ and ‘Classification’ with regard to disability inclusion. Classification using big data struggles to cope with the individual uniqueness of disabled people and whereas developers tend to design for the majority so ignoring outliers, designing for edge cases would be a more inclusive approach. Other issues that are discussed in the paper include: personalising mobile technology accessibility settings with interoperable profiles to allow ubiquitous accessibility; the ethics of using genetic data driven personalisation to ensure babies are not born with disabilities; the importance of including disabled people in decisions to help understand AI implications; the relationship between localisation and personalisation as assistive technologies need localising in terms of language as well as culture; the ways in which AI could be used to create personalised symbols for people who find it difficult to communicate in speech or writing; and whether blind or visually impaired person will be permitted to ‘drive’ an autonomous car. This paper concludes by suggesting that the relationship between the terms ‘Personalisation’ and ‘Classification’ with regards to AI and disability inclusion is a very unique one because of the heterogeneity in contrast to the other protected characteristics and so needs unique solutions.

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More information

Accepted/In Press date: 15 December 2020
e-pub ahead of print date: 18 January 2021
Keywords: personalisation, classification‐, localisation, artificial intelligence, Disability

Identifiers

Local EPrints ID: 447207
URI: http://eprints.soton.ac.uk/id/eprint/447207
PURE UUID: 71df14f2-3749-4164-ac5e-6b13713b4203

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Date deposited: 04 Mar 2021 17:46
Last modified: 04 Mar 2021 17:46

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Contributors

Author: Mike Wald

University divisions

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