1. NCCU Academic Hub
  2. Publications
  3. Item

Publications-Articles

Article View/Open

Publication Export

Google ScholarTM

NCCU Library

Citation Infomation

Related Publications in TAIR

題名 Who is the expert? Reconciling algorithm aversion and algorithm appreciation in AI-supported decision making
作者 侯宗佑
Hou, Yoyo Tsung-Yu;Jung, Malte F.
貢獻者 傳播學院
日期 2021-10
上傳時間 6-Jul-2026 10:16:45 (UTC+8)
摘要 The increased use of algorithms to support decision making raises questions about whether people prefer algorithmic or human input when making decisions. Two streams of research on algorithm aversion and algorithm appreciation have yielded contradicting results. Our work attempts to reconcile these contradictory findings by focusing on the framings of humans and algorithms as a mechanism. In three decision making experiments, we created an algorithm appreciation result (Experiment 1) as well as an algorithm aversion result (Experiment 2) by manipulating only the description of the human agent and the algorithmic agent, and we demonstrated how different choices of framings can lead to inconsistent outcomes in previous studies (Experiment 3). We also showed that these results were mediated by the agent's perceived competence, i.e., expert power. The results provide insights into the divergence of the algorithm aversion and algorithm appreciation literature. We hope to shift the attention from these two contradicting phenomena to how we can better design the framing of algorithms. We also call the attention of the community to the theory of power sources, as it is a systemic framework that can open up new possibilities for designing algorithmic decision support systems.
關聯 Proceedings of the ACM on Human-Computer Interaction, Vol.5, No.CSCW2, article no.477, pp.1-25
資料類型 article
article
DOI https://doi.org/10.1145/3479864
dc.contributor 傳播學院
dc.creator (作者) 侯宗佑
dc.creator (作者) Hou, Yoyo Tsung-Yu;Jung, Malte F.
dc.date (日期) 2021-10
dc.date.accessioned 6-Jul-2026 10:16:45 (UTC+8)-
dc.date.available 6-Jul-2026 10:16:45 (UTC+8)-
dc.date.issued (上傳時間) 6-Jul-2026 10:16:45 (UTC+8)-
dc.identifier.uri (URI) https://ah.lib.nccu.edu.tw/item?item_id=183160-
dc.description.abstract (摘要) The increased use of algorithms to support decision making raises questions about whether people prefer algorithmic or human input when making decisions. Two streams of research on algorithm aversion and algorithm appreciation have yielded contradicting results. Our work attempts to reconcile these contradictory findings by focusing on the framings of humans and algorithms as a mechanism. In three decision making experiments, we created an algorithm appreciation result (Experiment 1) as well as an algorithm aversion result (Experiment 2) by manipulating only the description of the human agent and the algorithmic agent, and we demonstrated how different choices of framings can lead to inconsistent outcomes in previous studies (Experiment 3). We also showed that these results were mediated by the agent's perceived competence, i.e., expert power. The results provide insights into the divergence of the algorithm aversion and algorithm appreciation literature. We hope to shift the attention from these two contradicting phenomena to how we can better design the framing of algorithms. We also call the attention of the community to the theory of power sources, as it is a systemic framework that can open up new possibilities for designing algorithmic decision support systems.
dc.format.extent 95 bytes-
dc.format.mimetype text/html-
dc.relation (關聯) Proceedings of the ACM on Human-Computer Interaction, Vol.5, No.CSCW2, article no.477, pp.1-25
dc.title (題名) Who is the expert? Reconciling algorithm aversion and algorithm appreciation in AI-supported decision making
dc.type (資料類型) article
dc.type (資料類型) articleen
dc.identifier.doi (DOI) 10.1145/3479864
dc.doi.uri (DOI) https://doi.org/10.1145/3479864