Can Our Health Data Stay Private?: A Review and Future Directions for IS Research on Privacy-preserving AI in Healthcare

Aycan Aslan; Maike Greve; Till Ole Diesterhöft; Lutz M. Kolbe

Can Our Health Data Stay Private? A Review and Future Directions for IS Research on Privacy-preserving AI in Healthcare

Aycan Aslan
, Maike Greve
, Till Ole Diesterhöft
, Lutz M. Kolbe

University of Göttingen

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Abstract

The generation of data has become one of the main drivers of modern healthcare. Like other industries, we see that the total amount of healthcare data is growing and in diversity. Thus, Artificial Intelligence (AI) is being used increasingly as a tool to turn this body of healthcare data into real value. But with AI and big data comes big risk, especially in terms of data privacy. Privacy-preserving AI techniques are gaining in popularity to prevent patient privacy compromises while utilizing the potentials offered by AI. However, there is no clear understanding of the current research space of applying such privacy-preserving techniques in healthcare. This paper aims to provide an understanding of these techniques and investigates the emerging research field of privacy-preserving AI and its use in healthcare by reviewing the current multidisciplinary research to synthesize knowledge and derive future research directions in this regard.

Original language	English
Title of host publication	Proceedings of the 17th International Conference on Wirtschaftsinformatik (WI)
Editors	Sven Laumer, Martin Matzner
Number of pages	17
Place of Publication	Atlanta, GA
Publisher	Association for Information Systems. AIS Electronic Library (AISeL)
Publication date	2022
Publication status	Published - 2022
Externally published	Yes
Event	17th International Conference on Wirtschaftsinformatik. WI 2022 - Online, Nuremberg, Germany Duration: 21 Feb 2022 → 23 Feb 2022 Conference number: 17 https://wi22.de/en/home-en/

Conference

Conference	17th International Conference on Wirtschaftsinformatik. WI 2022
Number	17
Location	Online
Country/Territory	Germany
City	Nuremberg
Period	21/02/2022 → 23/02/2022
Internet address	https://wi22.de/en/home-en/

Bibliographical note

Publisher Copyright:
© 2022 17th International Conference on Wirtschaftsinformatik, WI 2022. All rights reserved.

Keywords

Data Privacy
Healthcare
Privacy-Preserving AI
Private AI

Access to Document

https://aisel.aisnet.org/wi2022/digital_health/digital_health/8 Licence: Unspecified

Handle.net

Persistent link

Cite this

Aslan, A., Greve, M., Diesterhöft, T. O., & Kolbe, L. M. (2022). Can Our Health Data Stay Private? A Review and Future Directions for IS Research on Privacy-preserving AI in Healthcare. In S. Laumer, & M. Matzner (Eds.), Proceedings of the 17th International Conference on Wirtschaftsinformatik (WI) Association for Information Systems. AIS Electronic Library (AISeL). https://aisel.aisnet.org/wi2022/digital_health/digital_health/8

Aslan, Aycan ; Greve, Maike ; Diesterhöft, Till Ole et al. / Can Our Health Data Stay Private? A Review and Future Directions for IS Research on Privacy-preserving AI in Healthcare. Proceedings of the 17th International Conference on Wirtschaftsinformatik (WI). editor / Sven Laumer ; Martin Matzner. Atlanta, GA : Association for Information Systems. AIS Electronic Library (AISeL), 2022.

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title = "Can Our Health Data Stay Private?: A Review and Future Directions for IS Research on Privacy-preserving AI in Healthcare",

abstract = "The generation of data has become one of the main drivers of modern healthcare. Like other industries, we see that the total amount of healthcare data is growing and in diversity. Thus, Artificial Intelligence (AI) is being used increasingly as a tool to turn this body of healthcare data into real value. But with AI and big data comes big risk, especially in terms of data privacy. Privacy-preserving AI techniques are gaining in popularity to prevent patient privacy compromises while utilizing the potentials offered by AI. However, there is no clear understanding of the current research space of applying such privacy-preserving techniques in healthcare. This paper aims to provide an understanding of these techniques and investigates the emerging research field of privacy-preserving AI and its use in healthcare by reviewing the current multidisciplinary research to synthesize knowledge and derive future research directions in this regard.",

keywords = "Data Privacy, Healthcare, Privacy-Preserving AI, Private AI, Data Privacy, Healthcare, Privacy-Preserving AI, Private AI",

author = "Aycan Aslan and Maike Greve and Diesterh{\"o}ft, \{Till Ole\} and Kolbe, \{Lutz M.\}",

note = "Publisher Copyright: {\textcopyright} 2022 17th International Conference on Wirtschaftsinformatik, WI 2022. All rights reserved.; 17th International Conference on Wirtschaftsinformatik. WI 2022, WI2022 ; Conference date: 21-02-2022 Through 23-02-2022",

year = "2022",

language = "English",

editor = "Sven Laumer and Martin Matzner",

booktitle = "Proceedings of the 17th International Conference on Wirtschaftsinformatik (WI)",

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Aslan, A, Greve, M, Diesterhöft, TO & Kolbe, LM 2022, Can Our Health Data Stay Private? A Review and Future Directions for IS Research on Privacy-preserving AI in Healthcare. in S Laumer & M Matzner (eds), Proceedings of the 17th International Conference on Wirtschaftsinformatik (WI). Association for Information Systems. AIS Electronic Library (AISeL), Atlanta, GA, 17th International Conference on Wirtschaftsinformatik. WI 2022, Nuremberg, Bavaria, Germany, 21/02/2022. <https://aisel.aisnet.org/wi2022/digital_health/digital_health/8 >

Can Our Health Data Stay Private? A Review and Future Directions for IS Research on Privacy-preserving AI in Healthcare. / Aslan, Aycan; Greve, Maike; Diesterhöft, Till Ole et al.
Proceedings of the 17th International Conference on Wirtschaftsinformatik (WI). ed. / Sven Laumer; Martin Matzner. Atlanta, GA: Association for Information Systems. AIS Electronic Library (AISeL), 2022.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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