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Explaining how algorithms work reduces consumers' concerns regarding the collection of personal data and promotes AI technology adoption
Author(s) -
Querci Ilaria,
Barbarossa Camilla,
Romani Simona,
Ricotta Francesco
Publication year - 2022
Publication title -
psychology and marketing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.035
H-Index - 116
eISSN - 1520-6793
pISSN - 0742-6046
DOI - 10.1002/mar.21705
Subject(s) - data collection , work (physics) , computer science , emerging technologies , data science , artificial intelligence , knowledge management , psychology , marketing , business , sociology , engineering , mechanical engineering , social science
Consumers' concerns about how companies gather and use their personal data can impede the widespread adoption of artificial intelligence (AI) technologies. This study demonstrates that mechanistic explanations of AI algorithms can inhibit such data collection concerns. Four independent online experiments show a negative effect of detailed mechanistic explanations on data collection concerns (Studies 1a and 1b), as well as mediating influences of a subjective understanding of how AI algorithms work (Study 2) and increased the likelihood to adopt AI technologies after data collection concerns have been mitigated (Study 3). These findings contribute to research on consumer privacy concerns and the adoption of AI technologies, by identifying (1) a new inhibitor of data collection concerns, namely, mechanistic explanations of AI algorithms; (2) the psychological mechanisms underlying mechanist explanation effects; and (3) how diminished data collection concerns promote AI technology adoption. These insights can help companies design more effective communication strategies that reduce the perceived opacity of AI algorithms, reassure consumers, and encourage their adoption of AI technologies.