Embedded Ethics in Practice: A Toolbox for Integrating the Analysis of Ethical and Social Issues into Healthcare AI Research.
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Abstract
Integrating artificial intelligence (AI) into critical domains such as healthcare holds immense promise. Nevertheless, significant challenges must be addressed to avoid harm, promote the well-being of individuals and societies, and ensure ethically sound and socially just technology development. Innovative approaches like Embedded Ethics, which refers to integrating ethics and social science into technology development based on interdisciplinary collaboration, are emerging to address issues of bias, transparency, misrepresentation, and more. This paper aims to develop this approach further to enable future projects to effectively deploy it. Based on the practical experience of using ethics and social science methodology in interdisciplinary AI-related healthcare consortia, this paper presents several methods that have proven helpful for embedding ethical and social science analysis and inquiry. They include (1) stakeholder analyses, (2) literature reviews, (3) ethnographic approaches, (4) peer-to-peer interviews, (5) focus groups, (6) interviews with affected groups and external stakeholders, (7) bias analyses, (8) workshops, and (9) interdisciplinary results dissemination. We believe that applying Embedded Ethics offers a pathway to stimulate reflexivity, proactively anticipate social and ethical concerns, and foster interdisciplinary inquiry into such concerns at every stage of technology development. This approach can help shape responsible, inclusive, and ethically aware technology innovation in healthcare and beyond.
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Acknowledgements: This article is based on research conducted in multiple projects funded by the German Federal Ministry of Health (DR-AI), the Bavarian Research Institute for Digital Transformation (Responsible Robotics; RR-AI), the Center for Responsible AI-Technologies (CReAITech) founded by the Technical University of Munich, the University of Augsburg, and the Munich School of Philosophy, Biomarkers for Atopic Dermatitis and Psoriasis (BIOMAP—This project has received funding from the Innovative Medicine Initiative 2 Joint Undertaking (JU) under grant agreement No. 821511. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA.), INTERnational consortium for integratiVE geNomics prEdiction (INTERVENE – This project has been funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 101016775). The Innovation Network for Mental Health at TUM received funding via the Excellence Strategy of the Federal and State Governments (NEUROTECH). Stuart McLennan receives funding from Obelisk from the European Union’s Horizon Europe Research and Innovation Programme under grant agreement 101080465, and STAGE from the European Union’s Horizon Europe Research and Innovation Programme under grant agreement 101137146.
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1471-5546

