Paper Number
ICIS2025-1255
Paper Type
Complete
Abstract
AI-based health services offer major potential to address rising care demands through improved personalization enabled by continuous data collection. However, concerns about privacy risks, particularly regarding sensitive health data, can impede usage intentions. To address this tension, we investigate the role of AI reciprocity within AI-based health services, focusing on how mutual benefits from data disclosure influence personal benefits and privacy risks. Based on an online vignette study with 302 elderly participants, we analyze AI reciprocity’s dual role in the privacy calculus. Our findings reveal that AI reciprocity enhances the perception of personal benefits and reduces perceived privacy risks, suggesting a recalibration of the traditional privacy calculus. Trust in technology and in the provider emerge as key antecedents, each significantly influencing the perception of AI reciprocity. These insights highlight the importance of communicating the collective benefits inherent to AI reciprocity to foster positive usage intentions toward AI-based health services.
Recommended Citation
Zieglmeier, Alexander and Kranz, Johann, "Rewiring the Privacy Calculus: How AI Reciprocity Drives Usage Intentions by Boosting Benefits and Reducing Risks" (2025). ICIS 2025 Proceedings. 2.
https://aisel.aisnet.org/icis2025/cyb_security/cyb_security/2
Rewiring the Privacy Calculus: How AI Reciprocity Drives Usage Intentions by Boosting Benefits and Reducing Risks
AI-based health services offer major potential to address rising care demands through improved personalization enabled by continuous data collection. However, concerns about privacy risks, particularly regarding sensitive health data, can impede usage intentions. To address this tension, we investigate the role of AI reciprocity within AI-based health services, focusing on how mutual benefits from data disclosure influence personal benefits and privacy risks. Based on an online vignette study with 302 elderly participants, we analyze AI reciprocity’s dual role in the privacy calculus. Our findings reveal that AI reciprocity enhances the perception of personal benefits and reduces perceived privacy risks, suggesting a recalibration of the traditional privacy calculus. Trust in technology and in the provider emerge as key antecedents, each significantly influencing the perception of AI reciprocity. These insights highlight the importance of communicating the collective benefits inherent to AI reciprocity to foster positive usage intentions toward AI-based health services.
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09-Cybersecurity