Algorithmic Fairness and its Limits in Group-Formation

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Abstract

Abstract. Algorithmic group formation has become a flourishing research area
in the computer sciences, and more recently in the field of data mining and fair
machine learning. Application domains for algorithmic solutions to grouping
span wide, from team-recommendation and formation in work settings to ability-grouping in education. Recent work has also focused on fairness in group-formation. We briefly review literature on algorithmic team-formation and
consider fairness in different group-formation contexts. We articulate different
dimensions and constraints that are relevant for fair group-formation and discuss
the tension between utility and fairness. Many problems and limitations regarding
formal definitions of fairness explicated in the fair machine learning literature
apply also in the context of group-formation. We suggest some limits to the
relevance of fairness in general and algorithmic fairness, in particular. We argue
that algorithmic fairness is less relevant to some groups because of the way they
come to existence or because fairness is not a central value for them. Other central values are subjective rights; autonomy or liberty; legitimacy and authority;
solidarity; and diversity, each of which can be in tension with optimal fairness-and-utility. But within acceptable limits, we argue that fairness is indeed a
valuable goal that may be in tension with maximization of the relevant types of
utility
Original languageEnglish
Title of host publicationTethics2020: Conference on Technology Ethics
EditorsJani Koskinen, Minna Rantanen, Anne-Marie Tuikka, Sari Knaapi-Junnila
Pages38-54
Number of pages17
Publication statusPublished - 21 Oct 2020
Publication typeA4 Article in conference proceedings
EventTethics: Conference on Technology Ethics - Turku
Duration: 21 Oct 202021 Oct 2020

Publication series

NameCEUR Workshop Proceedings
PublisherCEUR
Number2737
ISSN (Electronic)1613-0073

Conference

ConferenceTethics: Conference on Technology Ethics
CityTurku
Period21/10/2021/10/20

Keywords

  • algorithmic group-formation
  • team-recommendation
  • machine learning
  • fairness
  • political philosophy
  • ethics

Publication forum classification

  • Publication forum level 1

ASJC Scopus subject areas

  • Philosophy

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