AI for Depression Treatment : Addressing the Paradox of Privacy and Trust with Empathy, Accountability, and Explainability

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review

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Detail(s)

Original languageEnglish
Title of host publicationICIS 2021 Proceedings
PublisherAssociation for Information Systems
ISBN (Print)978-1-7336325-9-1
Publication statusPublished - Dec 2021

Conference

Title42nd International Conference on Information Systems (ICIS 2021)
PlaceUnited States
CityAustin
Period12 - 15 December 2021

Abstract

Personal healthcare information (PHI) disclosure is vital in leveraging artificial intelligence (AI) technology for depression treatment. Two challenges for PHI disclosure are high privacy concern and low trust. In this study, we integrate three theoretical lenses, i.e., information boundary theory, trust, and AI principles to investigate whether AI principles of empathy, accountability, and explainability can address these two challenges. We propose that AI empathy can increase depression patients’ privacy concern and trust simultaneously. This paradox of high privacy concern and high trust has to be addressed for successful AI deployment in depression treatment. The proxies of AI accountability such as AI company reputation and government regulation can help reduce this paradox. Further, we argue that explainability can moderate the relationships between this paradox (i.e., privacy concern and trust) and patient’s intention to disclose PHI. Overall, our expected results can provide significant implications to IS literature and practitioners.

Bibliographic Note

“Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s).

Citation Format(s)

AI for Depression Treatment : Addressing the Paradox of Privacy and Trust with Empathy, Accountability, and Explainability. / Yan, Aihua; Xu, David.

ICIS 2021 Proceedings. Association for Information Systems, 2021. 1937.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review