The ethics of data-driven personas

Joni Salminen, Willemien Froneman, Soon Gyo Jung, Shammur Chowdhury, Bernard J. Jansen

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

9 Citations (Scopus)

Abstract

Quantitative methods are becoming more common for persona creation, but it is not clear to which extent online data and opaque machine learning algorithms introduce bias at various steps of data-driven persona creation (DDPC) and if these methods violate user rights. In this conceptual analysis, we use Gillespie's framework of algorithmic ethics to analyze DDPC for ethical considerations. We propose five design questions for evaluating the ethics of DDPC. DDPC should demonstrate the diversity of the user base but represent the actual data, be accompanied by explanations of their creation, and mitigate the possibility of unfair decisions.

Original languageEnglish
Title of host publicationCHI EA 2020 - Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450368193
DOIs
Publication statusPublished - 25 Apr 2020
Event2020 ACM CHI Conference on Human Factors in Computing Systems, CHI EA 2020 - Honolulu, United States
Duration: 25 Apr 202030 Apr 2020

Publication series

NameConference on Human Factors in Computing Systems - Proceedings

Conference

Conference2020 ACM CHI Conference on Human Factors in Computing Systems, CHI EA 2020
Country/TerritoryUnited States
CityHonolulu
Period25/04/2030/04/20

Keywords

  • Data-driven personas
  • Ethics
  • Fairness
  • Personas

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