Personalized Medicine and Data. Technologies, Welfare System, and Ethical Issues
During the last decades, tremendous progress has been achieved in the application of new technologies to health. In this context, there are rising expectations that major health issues can be technologically managed and that we will observe further increase of human longevity. In particular, it allows us ambitioning the development of personalized medicine, i.e. diagnosis and treatment that are tailor-made for each patient. A key is the accumulation of data in order to increase our knowledge of each patient through the statistical management of individual heterogeneity.
The potentialities of data management by extended intelligence or by artificial intelligence (AI) have attracted a lot of attention. It is considered as the most promising avenue in terms of innovation and transformation of our socio-economic systems but also of our intimate life. To put it simply, AI in healthcare is an overarching term used to describe the use of AI to mimic human cognition in the analysis, presentation, and comprehension of complex medical, and health care data. Although the concrete applications of AI to healthcare are diverse, it is possible to consider that the primary aim of health-related AI applications is to analyze relationships between prevention or treatment techniques and patient outcomes. At the same time, despite or because of all these promises, AI in healthcare raises several unprecedented ethical concerns related to its practice such as data privacy, automation of jobs, and representation biases.
In our project, three fundamental questions will be at the center of our investigation:
1) What are the respective benefits of home care and hospitalization?
2) How personalized medicine can contribute to a public policy of prevention?
3) How to conciliate the development of personal medicine and the protection of personal data?
- Eri KASAGI (The University of Tokyo, Faculty of Law)
- Sébastien LECHEVALIER (EHESS, Fondation France-Japon)
- Thomas LEFEVRE (Université Sorbonne Paris Nord, IRIS)
- Kazuhiro SAKURADA (Keio University School of Medicine, RIKEN Advanced Data Science Project)
- Catherine BOURGAIN (Inserm, CERMES3)
- Théau BRIGAND (EHESS, CERMES3)
- Amelia FISKE (Technical University of Munich, Institute for History and Ethics of Medicine)
- Mathieu GUEGUIN (EHESS, IRIS)
- Haluna KAWASHIMA (Keio University, Global Research Institute)
- Nao KINOSHITA (Ministry of Health, Labour and Welfare and Fondation France-Japon de l'EHESS)
- Kota KODAMA (Ritsumeikan University)
- Karin KURATA (Ritsumeikan University)
- Paul LARCHET (EHESS)
- Yeongjoo LIM (Ritsumeikan University)
- Philippe MARTIN (Université de Bordeaux, COMPTRASEC)
- Vanessa NUROCK (Université Côte d'Azur, CRHI)
- Paul VANPEENE (Université de Bordeaux, COMPTRASEC)
- Tatsuhiko YAMAMOTO (Keio University, Faculty of Law)
- Yu YASUI (Yamato Clinic)
- Shigeto YONEMURA (The University of Tokyo, Faculty of Law)