How Uncertainty and AI Reciprocity Shape Data Disclosure Decisions in AI Health Services

AI health services have become pervasive through advancements such as machine learning and increasing demands stemming from the needs of an aging society. This study explores the concept of "AI reciprocity" within commercial AI health services to examine prosocial data disclosure, wherein users contribute data to enhance service quality for all other users within a system. This study expands the literature on privacy calculus in the context of AI health services as it scrutinizes the impact of privacy uncertainty and AI reciprocity benefits on data disclosure. Conducting an online experiment, we found that privacy uncertainty is driven by transparency features and is associated negatively with data disclosure. Conversely, we find that AI reciprocity is positively associated with data disclosure. However, we could not find evidence that AI reciprocity can be influenced by manipulating the perceived social distance of the beneficiaries. Our findings suggest several avenues for future research.