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Research agenda for algorithmic fairness studies: Access to justice lessons for interdisciplinary research

Access to justice is one of the fundamental legitimating principles underlying all modern Western legal systems, yet its role in critical algorithm studies remains underdeveloped. In historical and methodological terms, the access to justice movement showcased multi- and interdisciplinary research o...

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Autores principales: Kontiainen, Laura, Koulu, Riikka, Sankari, Suvi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9811409/
https://www.ncbi.nlm.nih.gov/pubmed/36620752
http://dx.doi.org/10.3389/frai.2022.882134
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author Kontiainen, Laura
Koulu, Riikka
Sankari, Suvi
author_facet Kontiainen, Laura
Koulu, Riikka
Sankari, Suvi
author_sort Kontiainen, Laura
collection PubMed
description Access to justice is one of the fundamental legitimating principles underlying all modern Western legal systems, yet its role in critical algorithm studies remains underdeveloped. In historical and methodological terms, the access to justice movement showcased multi- and interdisciplinary research on legal phenomena. We argue that interdisciplinary research on AI ethics and regulation, datafication of society, and algorithmic governance could benefit from adopting access to justice as a vantage point for bridging the different approaches in the context of administering justice. To this end, we explore technological, legal, and societal intersections to demonstrate how law, social sciences, and algorithm studies could benefit from a historically more informed and holistic approach facilitating more “cost-effective” interdisciplinary research collaboration. Such approach could assist the substantive study of algorithmic fairness to contribute actionable systemic solutions on what we perceive as systemic challenges. We propose utilizing access to justice as a boundary object for interdisciplinary dialogue over algorithmic fairness while respecting the epistemic diversity of disciplines.
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spelling pubmed-98114092023-01-05 Research agenda for algorithmic fairness studies: Access to justice lessons for interdisciplinary research Kontiainen, Laura Koulu, Riikka Sankari, Suvi Front Artif Intell Artificial Intelligence Access to justice is one of the fundamental legitimating principles underlying all modern Western legal systems, yet its role in critical algorithm studies remains underdeveloped. In historical and methodological terms, the access to justice movement showcased multi- and interdisciplinary research on legal phenomena. We argue that interdisciplinary research on AI ethics and regulation, datafication of society, and algorithmic governance could benefit from adopting access to justice as a vantage point for bridging the different approaches in the context of administering justice. To this end, we explore technological, legal, and societal intersections to demonstrate how law, social sciences, and algorithm studies could benefit from a historically more informed and holistic approach facilitating more “cost-effective” interdisciplinary research collaboration. Such approach could assist the substantive study of algorithmic fairness to contribute actionable systemic solutions on what we perceive as systemic challenges. We propose utilizing access to justice as a boundary object for interdisciplinary dialogue over algorithmic fairness while respecting the epistemic diversity of disciplines. Frontiers Media S.A. 2022-12-21 /pmc/articles/PMC9811409/ /pubmed/36620752 http://dx.doi.org/10.3389/frai.2022.882134 Text en Copyright © 2022 Kontiainen, Koulu and Sankari. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Artificial Intelligence
Kontiainen, Laura
Koulu, Riikka
Sankari, Suvi
Research agenda for algorithmic fairness studies: Access to justice lessons for interdisciplinary research
title Research agenda for algorithmic fairness studies: Access to justice lessons for interdisciplinary research
title_full Research agenda for algorithmic fairness studies: Access to justice lessons for interdisciplinary research
title_fullStr Research agenda for algorithmic fairness studies: Access to justice lessons for interdisciplinary research
title_full_unstemmed Research agenda for algorithmic fairness studies: Access to justice lessons for interdisciplinary research
title_short Research agenda for algorithmic fairness studies: Access to justice lessons for interdisciplinary research
title_sort research agenda for algorithmic fairness studies: access to justice lessons for interdisciplinary research
topic Artificial Intelligence
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9811409/
https://www.ncbi.nlm.nih.gov/pubmed/36620752
http://dx.doi.org/10.3389/frai.2022.882134
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