Stakeholder-dependent views on biases of human- and machine-based judging systems

Elena Mazurova*, Esko Penttinen, Antti Salovaara

*Corresponding author for this work

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

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Motivated by recent controversy over biases associated with algorithmic decision-making, we embarked on studying various stakeholders’ perceptions related to potential biases in verdicts from human-based and algorithm-based judging. In an empirical study conducted in the domain of gymnastics judging, we found that, while our informants viewed both human- and AI-based judging systems as being subject to biases (of different types), they were quite welcoming of a shift from human-based judging to machine-based judging. Our findings show that the athletes trusted strongly in unknown, “magic” capabilities of AI, thought to be more objective and impartial. This, in turn, encouraged potential acceptance of new technology. While the gymnasts saw AI-based systems in a positive light, judges demonstrated less favorable perceptions overall and less acceptance of AI technology, expressing concern about possible challenges of AI.
Original languageEnglish
Title of host publicationProceedings of the 54th Hawaii International Conference on System Sciences
PublisherHawaii International Conference on System Sciences
Number of pages10
ISBN (Electronic)978-0-9981331-4-0
Publication statusPublished - 2021
MoE publication typeA4 Conference publication
EventAnnual Hawaii International Conference on System Sciences - Maui, United States
Duration: 7 Jan 202010 Jan 2020
Conference number: 53


ConferenceAnnual Hawaii International Conference on System Sciences
Abbreviated titleHICSS
Country/TerritoryUnited States


  • bias
  • case study
  • gymnastics
  • human-based judging
  • machine learning


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