What if an AI told you that 2 + 2 is 5? Conformity to algorithmic recommendations

Yotam Liel, Lior Zalmanson

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

Abstract

Organizations are increasingly integrating human-AI decision-making processes. Therefore, it is crucial to make sure humans possess the ability to call out algorithms' biases and errors. Biased algorithms were shown to negatively affect access to loans, hiring processes, judicial decisions, and more. Thus, studying workers' ability to balance reliance on algorithmic recommendations and critical judgment towards them, holds immense importance and potential social gain. In this study, we focused on gig-economy platform workers (MTurk) and simple perceptual judgment tasks, in which algorithmic mistakes are relatively visible. In a series of experiments, we present workers with misleading advice perceived to be the results of AI calculations and measure their conformity to the erroneous recommendations. Our initial results indicate that such algorithmic recommendations hold strong persuasive power, even compared to recommendations that are presented as crowd-based. Our study also explores the effectiveness of mechanisms for reducing workers' conformity in these situations.

Original languageEnglish
Title of host publicationInternational Conference on Information Systems, ICIS 2020 - Making Digital Inclusive
Subtitle of host publicationBlending the Local and the Global
PublisherAssociation for Information Systems
ISBN (Electronic)9781733632553
StatePublished - 2021
Event2020 International Conference on Information Systems - Making Digital Inclusive: Blending the Local and the Global, ICIS 2020 - Virtual, Online, India
Duration: 13 Dec 202016 Dec 2020

Publication series

NameInternational Conference on Information Systems, ICIS 2020 - Making Digital Inclusive: Blending the Local and the Global

Conference

Conference2020 International Conference on Information Systems - Making Digital Inclusive: Blending the Local and the Global, ICIS 2020
Country/TerritoryIndia
CityVirtual, Online
Period13/12/2016/12/20

Keywords

  • AI-human decision making
  • Conformity
  • Experiments
  • Gig-workers

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