Acceptance study on data sharing in AI-supported healthcare services published

With the help of an experiment, a research team from Ludwig-Maximilians-Universität München (LMU), a consortium partner in SmartLivingNEXT flagship project, showed that increased transparency about data usage reduces uncertainty and increases the willingness to share data, while data protection uncertainty significantly reduces this willingness. The researchers use the term “AI reciprocity” to describe this. It describes the benefits that can be achieved by sharing data not only for oneself, but also for others, as the quality of services is improved for all users. For example, AI reciprocity can have a positive impact on data sharing. However, social distance, i.e. how close or similar users feel to others, had no significant influence on the perceived relevance of AI reciprocity. The study provides important indications of how trust and willingness to cooperate can be promoted in data-based applications and illustrates that people share data not only for selfish reasons, but also out of a desire to help others.

Acceptance study with 240 participants

The results are based on an online experiment that was conducted in a 2×2 factorial design. The 240 participants were randomly assigned to one of four groups that differed in the dimensions of “data transparency” (high versus low) and “social distance” (close versus distant). They were asked to decide whether they would share different types of sensitive data, such as health and movement data, with a hypothetical AI-powered healthcare service. In addition, questionnaires were used to measure perceptions of transparency, privacy uncertainty and the benefits of AI reciprocity. The results were analyzed using structural equation modeling (SEM), which identified causal relationships between the variables studied and tested the central hypotheses.

Professor Johann Kranz, Professor of Digital Services and Sustainability at LMU: “The results suggest that companies in the healthcare sector can increase users’ willingness to share data by communicating transparently and emphasizing collective benefits. However, data privacy uncertainty remains a significant barrier that should be addressed through clear and understandable information about data use and protection. Overall, the study provides valuable insights into the balance between data privacy and the potential benefits of data sharing in a commercial context.”

Research team receives “Best Paper First Runner-Up” award

The LMU research team, consisting of Professor Johann Kranz and co-authors Alexander Zieglmeier and Tawfiq Alashoor, also received the “Best Paper First Runner-Up Award” at the International Conference on Information Systems (ICIS). The ICIS took place from December 15 to 18, 2024 at the Marriott Marquis Queen’s Park in Bangkok, Thailand.