Being human in the time of neuroscience and artificial intelligence involve carefully exploring the nexuses of complexity where valid ideas are nevertheless in tension, manifesting subtleties and challenges that must not be overlooked. Each page expresses the existing tension(s) between ideas and within each theme, which emerged in the collective discussions, and are then complemented by insights from NHNAI network researchers.
Complexity on Health #6: Regulating technologies and preserving persons’ privacy and integrity without stifling medical innovation
Participants largely acknowledge the benefits one can get from developing AI and health technologies in healthcare and medicine as well as in the domain of human enhancement (improved medical decision making, automation of certain tasks, enhanced access to healthcare and health related information, enhancement of physical and mental capacities, …).
At the same time, participants also worry about the risk that sensitive health information are collected for non-medical uses. Health data collected by AI or digital tools should only serve medical and healthcare purposes. Digital solutions should not imply intrusion of outside organizations (like insurance companies).
Moreover, with the convergence of NS and AI, data could be used to enhance prediction power over persons behaviors and thought, as well as the possibilities for cognitive manipulation. Therefore, mind privacy should be protected.
This raises the hard question of regulation. As evoked in the discussions, innovation could be hampered by overly rigid regulation, and patient safety compromised by overly lax regulation. So how do we strike the right balance between encouraging innovation and protecting patients?
Insights from NHNAI academic network:
The possibility of using healthcare data to contribute to the costly financing of healthcare innovation is a point of recurrent debate. This could prove to be an interesting avenue, provided that the protection of such data is convincing, and that it is used anonymized and with informed consent. However, a number of studies have documented cases where anonymization has failed, leading to a risk of re-identification.[1] It has also been highlighted that, under the effect of economic incentives, particularly vulnerable populations could be subject to various types of abuse.[2]
It is generally recognized as very important that external actors such as insurance companies should not be able to access health data. Public trust could be seriously undermined by the use of health data by private organizations for commercial or discriminatory purposes. The use of health data for explicit medical purposes only is intended to be guaranteed by the EU GDPR regulation, which imposes clear restrictions on the access and use of personal data to this end.[3]
The convergence of AI and neurotechnology opens the door to the prediction or manipulation of cognitive behavior, and thus poses new threats to cognitive privacy and mental freedom. Several authors thus insist on the importance of protecting the “privacy of the mind,” notably through regulations.[4]
Faced with all these challenges, tools such as blockchain are sometimes mentioned as likely to enable individuals to control access to their health data as well as its eventual availability for innovation purposes, on condition of the parallel development of voluntary and rigorous regulation.
Because of the stakes involved in terms of safety, efficacy and ethical use, it is imperative that innovation in AI and healthcare technologies is accompanied by sound regulatory frameworks. The healthcare sector is therefore expected to be able to bridge the gap between innovation and regulation. Excessive regulation, however, could have the effect of stifling innovation, discouraging investment in new technologies, and slowing the development of life-saving advances. Faced with a rapidly changing healthcare technology landscape, it is thus crucial to develop a balanced regulatory approach that is both flexible and adaptable. Some adaptive regulatory models have been proposed by researchers, in which technological development and oversight evolve simultaneously, allowing room for innovation without affecting accountability. In this way, we can hope to avoid the twin pitfalls of impeding progress, or under-protecting patients in the face of certain potential harms (Bouderhem, 2024; Zhou & Gattinger, 2024).[5]
[1] Ohm, P. (2010). Broken promises of privacy: Responding to the surprising failure of anonymization. UCLA Law Review, 57(6), 1701-1777.
[2] Vayena, E., & Tasioulas, J. (2016). The ethics of personalized medicine: New challenges and opportunities. Journal of Medical Ethics, 42(8), 451-454.
[3] Floridi, L., & Taddeo, M. (2016). What is data ethics? Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 374(2083), 20160360.
[4] Ienca, M., & Andorno, R. (2017). Towards new human rights in the age of neuroscience and neurotechnology. Life Sciences, Society and Policy, 13(1), 5.
[5] Bouderhem, R. (2024). Shaping the future of AI in healthcare through ethics and governance. Humanities and Social Sciences Communications, 11(416). Zhou, K., & Gattinger, G. (2024). The Evolving Regulatory Paradigm of AI in MedTech: A Review of Perspectives and Where We Are Today. Therapeutic Innovation & Regulatory Science, 58(456–464).
