Decoding algorithm appreciation: Unveiling the impact of familiarity with algorithms, tasks, and algorithm performance
Algorithm appreciation, defined as an individual's reliance or tendency to rely on algorithms in decision-making, has emerged as a subject of growing scholarly interest. Inquiries into this subject are crucial to understanding human decision-making processes as in the era of artificial intellig...
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| Vydáno v: | Decision Support Systems Ročník 179; s. 114168 |
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| Hlavní autoři: | , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Elsevier B.V
01.04.2024
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| ISSN: | 0167-9236 |
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| Abstract | Algorithm appreciation, defined as an individual's reliance or tendency to rely on algorithms in decision-making, has emerged as a subject of growing scholarly interest. Inquiries into this subject are crucial to understanding human decision-making processes as in the era of artificial intelligence, algorithms are increasingly being integrated into decision-making. To contribute to this evolving field, this study examines three factors that might play significant roles in enhancing trust in algorithms: familiarity with algorithms, familiarity with tasks, and familiarity with algorithm performance. Drawing upon prior studies, a conceptual model was developed and empirically tested using a scenario study. Data on 327 individuals showed a strong positive association between familiarity with algorithms and trust in algorithms. In contrast, task familiarity appeared to have no significant influence on trust. Trust, in turn, was identified as a key driver of algorithm appreciation. The study also revealed the moderating role of familiarity with algorithm performance in the relationship between familiarity with algorithms and trust in algorithms. Post hoc analysis highlighted that trust fully mediates the relationship between algorithm familiarity and algorithm appreciation. The study underscores the significance of algorithm familiarity and performance transparency in shaping trust in algorithms. The study contributes theoretically by offering important insights about the influences of different forms of familiarity on trust and practically by prescribing practical guidelines to enhance algorithm appreciation.
•Studied familiarity with algorithms (FA), tasks (FT), and algorithm performance (FP) in relation to algorithm appreciation.•Developed and validated a conceptual model using data from 327 participants.•FA was identified as a significant factor influencing trust, while FT showed no notable impact.•FP moderates the FA—trust relationship, and trust fully mediates between FA and algorithm appreciation.•Emphasized the critical roles of FA, FP, and trust in enhancing algorithm appreciation |
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| AbstractList | Algorithm appreciation, defined as an individual's reliance or tendency to rely on algorithms in decision-making, has emerged as a subject of growing scholarly interest. Inquiries into this subject are crucial to understanding human decision-making processes as in the era of artificial intelligence, algorithms are increasingly being integrated into decision-making. To contribute to this evolving field, this study examines three factors that might play significant roles in enhancing trust in algorithms: familiarity with algorithms, familiarity with tasks, and familiarity with algorithm performance. Drawing upon prior studies, a conceptual model was developed and empirically tested using a scenario study. Data on 327 individuals showed a strong positive association between familiarity with algorithms and trust in algorithms. In contrast, task familiarity appeared to have no significant influence on trust. Trust, in turn, was identified as a key driver of algorithm appreciation. The study also revealed the moderating role of familiarity with algorithm performance in the relationship between familiarity with algorithms and trust in algorithms. Post hoc analysis highlighted that trust fully mediates the relationship between algorithm familiarity and algorithm appreciation. The study underscores the significance of algorithm familiarity and performance transparency in shaping trust in algorithms. The study contributes theoretically by offering important insights about the influences of different forms of familiarity on trust and practically by prescribing practical guidelines to enhance algorithm appreciation.
•Studied familiarity with algorithms (FA), tasks (FT), and algorithm performance (FP) in relation to algorithm appreciation.•Developed and validated a conceptual model using data from 327 participants.•FA was identified as a significant factor influencing trust, while FT showed no notable impact.•FP moderates the FA—trust relationship, and trust fully mediates between FA and algorithm appreciation.•Emphasized the critical roles of FA, FP, and trust in enhancing algorithm appreciation |
| ArticleNumber | 114168 |
| Author | Mikalef, Patrick Islam, A.K.M. Najmul Luo, Xin (Robert) Mahmud, Hasan |
| Author_xml | – sequence: 1 givenname: Hasan surname: Mahmud fullname: Mahmud, Hasan email: hasan.mahmud@lut.fi organization: Software Engineering Department, LUT University, Lappeenranta, Finland – sequence: 2 givenname: A.K.M. Najmul surname: Islam fullname: Islam, A.K.M. Najmul email: najmul.islam@lut.fi organization: Software Engineering Department, LUT University, Lappeenranta, Finland – sequence: 3 givenname: Xin (Robert) surname: Luo fullname: Luo, Xin (Robert) email: xinluo@unm.edu organization: Anderson School of Management, The University of New Mexico, Albuquerque, USA – sequence: 4 givenname: Patrick surname: Mikalef fullname: Mikalef, Patrick email: patrick.mikalef@ntnu.no organization: Department of Computer Science, Norwegian University of Science and Technology, Sem Sælandsvei 9, 7034 Trondheim, Norway |
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| CitedBy_id | crossref_primary_10_1080_10447318_2025_2536617 crossref_primary_10_1016_j_technovation_2025_103293 crossref_primary_10_1080_01605682_2025_2466677 crossref_primary_10_1016_j_ijinfomgt_2025_102974 crossref_primary_10_1016_j_jretconser_2025_104224 crossref_primary_10_1016_j_im_2025_104216 crossref_primary_10_1007_s11301_025_00526_4 crossref_primary_10_1016_j_dss_2025_114541 crossref_primary_10_1038_s44271_024_00182_6 crossref_primary_10_1080_21515581_2024_2445505 crossref_primary_10_1016_j_ijinfomgt_2025_102937 |
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| Keywords | Algorithmic decision-making Transparency Algorithm performance Familiarity Trust Algorithm appreciation |
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