Applications of Artificial Intelligence in Public Health and Medicine: From Targeted, Improved Technical Tools to a Wide, Deep Social Revolution

Dear Colleagues,

Since the end of the 2010s, there has been a strong resurgence of interest in artificial intelligence (AI) in all areas of activity, including health. While the concept and the first techniques of artificial intelligence are now more than 60 years old, this renewal of AI is often made to coincide with the successes encountered by the progress of machine learning, more specifically, deep learning. This vision is reductive because what we are witnessing is above all an acceleration of both a general and continuous movement and of more or less mature technological developments, in a sociocultural context favorable to their establishment.

Health is a very specific sector, subject on the one hand to strong regulation, and on the other hand the subject of concerns shared by the greatest number and not stopping at the borders of healthcare systems or medicine. Public health is also unique in that it refers as much to the health of populations as to the means, particularly political ones, put in place to maintain and improve it. AI, and the more general development of digital technology, arise in this ambivalent context, between very strong regulation and the common good, collective and individual.

For this Special Issue, we call for contributions that can account for the entire spectrum between these two extremes, in order to determine whether they are fully reconcilable:

• The application of AI to targeted issues in medicine and public health: use of natural language processing to extract knowledge from medical records and the scientific literature; diagnostic aid; predictive modeling of diseases, epidemics, the evolution of a health system under various constraints; ethical, legal, ecological and economic aspects of AI in health; etc.;
• The application of AI in public or population health, as a socio-technical means redistributing roles between traditional health actors and new actors, promoting the emergence of new uses and new practices, authorized or not at present: the health in the hands of private companies outside of health; the reaction of public institutions to digital and AI in health; the place of the individual and the patient in relation to AI and their health; new jobs; etc.

We, therefore, invite both articles presenting applications, specific use cases, in particular, their scientific evaluation, and articles on perspectives or the state of the art on these questions. AI is evolving rapidly in an ecosystem that is generally favorable to it and is capable of dramatically changing many aspects of medicine and public health. We are counting on your contributions to help give us new landmarks.

Dr. Thomas Lefèvre
Dr. Claire Morgand
Dr. Cyrille Delpierre
Guest Editors

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• artificial intelligence
• machine learning
• public health
• medicine
• digital revolution
• digital transformation
• personalized medicine
• predictive modeling
• health policy

Title: Artificial Intelligence, Precision Medicine and Precision Public Health as Frontier Concepts Regarding Their Relationships to Behavioral Sciences
Authors: Thomas Lefèvre
Affiliation: IRIS – Institut de recherche interdisciplinaire sur les enjeux sociaux UMR CNRS 8156 Inserm 997 EHESS USPN, Université Sorbonne Paris Nord, 93017 Paris, France; HCSP – Haut conseil de la santé publique, 10 place des 5 martyrs du lycée Buffon, 75014 Paris, France
Abstract: The last decade has seen the diffusion of the concept of precision medicine and the emergence of that of precision public health. The evolution of these two concepts has been accompanied by the ubiquitous development of digital technology in all dimensions of our lives, including in the field of health. More specifically, the multiplication of data sources and of their nature has led to a renewed interest in the development of artificial intelligence (AI) algorithms. If precision medicine and public health largely draw on the opportunities offered by digital technology and AI on the one hand, and by genomics and omics in general on the other, it remains that both the individual health that the health of populations is only partially based on genetics and the health system. On the other hand, environmental factors, social determinants and health behaviors contribute significantly to individual and population health. Furthermore, one of the advantages of focusing on health behaviors is that they are theoretically modifiable. Nevertheless, the question of behavior refers to the question of individual and collective responsibility, as well as the nature of possible interventions to act on these behaviors: they can for example be coercive or incentive, and above all, they can be implicit or explicit. It is remarkable that a privileged meeting point of digital technology and health, especially precision health, is these behaviors, in general or health in particular. Indeed, the development of digital technology and the success of its adoption are largely due to the mobilization of techniques from behavioral sciences and the attention economy, taking advantage of cognitive biases to better capture the public, where healthcare professionals were primarily interested in motivational techniques and therapeutic education. At the individual and population level, public and private stakeholders come together on the question of the use of behavioral science techniques, but with perspectives and motivations that may be incompatible. Conscientious action and the consent of citizens regarding the use of these techniques are probably not the center of attention which is questionable. In this paper, we present the issues surrounding the use of behavioral sciences in precision medicine and public health, in connection with the development of AI.