Toward the Utilization of Artificial Intelligence in Life Sciences: A Voluntary Medical Data Provisioning Model

Masanori Fujita, Ayato Kitadai, Koichi Sumikura, Nariaki Nishino

Abstract: To extend people’s life expectancy while improving their health and quality of life, the promotion of artificial intelligence (AI) and big data technologies to life science fields is crucial. In the medical field, AI model training is quite difficult owing to its heterogeneity and the fact that the stakeholders and data owners have a variety of valid privacy and protection needs and concerns, which has resulted in heavily suppressed cooperation. To help remedy this problem, we examine the behaviors of life science researchers who use medical data for AI purposes from social and institutional perspectives. From this, we provide a mathematical model for medical data provisioning based on the public goods game theory. Numerical simulation of the proposed model shows that the "pump-priming effect" caused by the existence of voluntary data providers may result in cooperative behaviors instead of the non-cooperative equilibrium obtained in the conventional public goods game. We conclude that our approach provides an effective mathematical and quantitative mechanism design in response to extant qualitative medical data provisioning problems.