Third Party Funds Group - Overall project
Acronym: vALID
Start date : 01.11.2019
End date : 31.10.2022
AI is on everyone’s lips. Applications of AI are becoming increasingly relevant in the field of clinical decision-making. While many of the conceivable use cases of clinical AI still lay in the future, others have already begun to shape practice. The project vALID provides a normative, legal, and technical analysis of how AI-driven clinical Decisions Support Systems could be aligned with the ideal of clinician and patient sovereignty. It examines how concepts of trustworthiness, transparency, agency, and responsibility are affected and shifted by clinical AI—both on a theoretical level, and with regards to concrete moral and legal consequences. This analysis is grounded in an empirical case study which deploys mock-up simulations of AI-driven clinical Decision Support Systems and systematically gathers clinician and patient attitudes on a variety of designs and implementations. One key output of vALID will be a governance perspective on human-centric AI-driven Decision Support Systems in the context of shared clinical decision-making.
AI is on
everyone’s lips. Applications of AI are becoming increasingly relevant in the
field of clinical decision-making. While many of the conceivable use cases
still lay in the future, others have already begun to shape practice. The
project vALID provides a normative, legal, and technical
analysis of how AI-driven clinical Decisions Support Systems could be aligned
with the ideal of clinician and patient sovereignty.
vALID consists
of four subprojects. On the basis of an in-depth analysis of existing normative
work on clinical AI, the ethical subproject examines which aspects the ideal of
clinician and patient sovereignty encompasses. On the basis of a de lege lata
analysis, the legal subproject analyzes and evaluates various regulatory
options in the national and international context. Both subprojects reflect on
how concepts of trustworthiness, transparency, agency and responsibility are
influenced and shifted by clinical AI, both on a theoretical level and with
regard to concrete moral and legal consequences.
In the
technical subproject, and against the background of a thorough analysis of what
is technically possible and already being practiced in the clinic, mock-up
simulations of conventional, automated and integrative decision support systems
will be developed. In the empirical subproject, clinicians and patients will be
exposed to these mock-up simulations. Quantitative and qualitative methods will
then be used to systematically gather perspectives and argumentative patterns
on the range of designs and implementations of AI-driven, clinical decision
support systems.
Throughout
this process, the subprojects are continuously methodologically intertwined:
The normative subprojects on the one hand develop the conceptual framework for
the empirical investigations, and on the other hand incorporate results of the
latter into their positions.
On the basis of this work, the four vALID subprojects
will finally jointly develop an ethically, legally, technically, and
empirically informed governance perspective for AI-driven decision support
systems in the context of shared clinical decision-making.