TY - JOUR
T1 - Responsible AI for digital health
T2 - a synthesis and a research agenda
AU - Trocin, Cristina
AU - Mikalef, Patrick
AU - Papamitsiou, Zacharoula
AU - Conboy, Kieran
N1 - Publisher Copyright:
© 2021, The Author(s).
PY - 2023/12
Y1 - 2023/12
N2 - Responsible AI is concerned with the design, implementation and use of ethical, transparent, and accountable AI technology in order to reduce biases, promote fairness, equality, and to help facilitate interpretability and explainability of outcomes, which are particularly pertinent in a healthcare context. However, the extant literature on health AI reveals significant issues regarding each of the areas of responsible AI, posing moral and ethical consequences. This is particularly concerning in a health context where lives are at stake and where there are significant sensitivities that are not as pertinent in other domains outside of health. This calls for a comprehensive analysis of health AI using responsible AI concepts as a structural lens. A systematic literature review supported our data collection and sampling procedure, the corresponding analysis, and extraction of research themes helped us provide an evidence-based foundation. We contribute with a systematic description and explanation of the intellectual structure of Responsible AI in digital health and develop an agenda for future research.
AB - Responsible AI is concerned with the design, implementation and use of ethical, transparent, and accountable AI technology in order to reduce biases, promote fairness, equality, and to help facilitate interpretability and explainability of outcomes, which are particularly pertinent in a healthcare context. However, the extant literature on health AI reveals significant issues regarding each of the areas of responsible AI, posing moral and ethical consequences. This is particularly concerning in a health context where lives are at stake and where there are significant sensitivities that are not as pertinent in other domains outside of health. This calls for a comprehensive analysis of health AI using responsible AI concepts as a structural lens. A systematic literature review supported our data collection and sampling procedure, the corresponding analysis, and extraction of research themes helped us provide an evidence-based foundation. We contribute with a systematic description and explanation of the intellectual structure of Responsible AI in digital health and develop an agenda for future research.
KW - Responsible AI
KW - Artificial intelligence
KW - Ethical concerns
KW - Healthcare
KW - Systematic literature review
KW - Meta-data analysis
UR - http://www.scopus.com/inward/record.url?scp=85108810679&partnerID=8YFLogxK
U2 - 10.1007/s10796-021-10146-4
DO - 10.1007/s10796-021-10146-4
M3 - Article
SN - 1387-3326
VL - 25
SP - 2139
EP - 2157
JO - Information Systems Frontiers
JF - Information Systems Frontiers
IS - 6
ER -