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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.

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Jan 17th, 12:00 AM

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

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.