Embedded Ethics in Practice: A Toolbox for Integrating the Analysis of Ethical and Social Issues into Healthcare AI Research.
Theresa Willem, Marie-Christine Fritzsche, Bettina M Zimmermann, Anna Sierawska, Svenja Breuer, Maximilian Braun, Anja K Ruess, Marieke Bak, Franziska B Sch��nweitz, Lukas J Meier, Amelia Fiske, Daniel Tigard, Ruth M��ller, Stuart McLennan, Alena Buyx
Author Information
Theresa Willem: Institute of History and Ethics in Medicine, Department of Preclinical Medicine, TUM School of Medicine and Health, Technical University of Munich, Ismaninger Stra��e 22, 81675, Munich, Germany. theresa.willem@tum.de. ORCID
Marie-Christine Fritzsche: Institute of History and Ethics in Medicine, Department of Preclinical Medicine, TUM School of Medicine and Health, Technical University of Munich, Ismaninger Stra��e 22, 81675, Munich, Germany.
Bettina M Zimmermann: Institute of History and Ethics in Medicine, Department of Preclinical Medicine, TUM School of Medicine and Health, Technical University of Munich, Ismaninger Stra��e 22, 81675, Munich, Germany.
Anna Sierawska: Institute of History and Ethics in Medicine, Department of Preclinical Medicine, TUM School of Medicine and Health, Technical University of Munich, Ismaninger Stra��e 22, 81675, Munich, Germany.
Svenja Breuer: Department of Science, Technology and Society (STS), School of Social Science and Technology, Technical University of Munich, Munich, Germany.
Maximilian Braun: Department of Science, Technology and Society (STS), School of Social Science and Technology, Technical University of Munich, Munich, Germany.
Anja K Ruess: Department of Science, Technology and Society (STS), School of Social Science and Technology, Technical University of Munich, Munich, Germany.
Marieke Bak: Institute of History and Ethics in Medicine, Department of Preclinical Medicine, TUM School of Medicine and Health, Technical University of Munich, Ismaninger Stra��e 22, 81675, Munich, Germany.
Franziska B Sch��nweitz: Institute of History and Ethics in Medicine, Department of Preclinical Medicine, TUM School of Medicine and Health, Technical University of Munich, Ismaninger Stra��e 22, 81675, Munich, Germany.
Lukas J Meier: Institute of History and Ethics in Medicine, Department of Preclinical Medicine, TUM School of Medicine and Health, Technical University of Munich, Ismaninger Stra��e 22, 81675, Munich, Germany.
Amelia Fiske: Institute of History and Ethics in Medicine, Department of Preclinical Medicine, TUM School of Medicine and Health, Technical University of Munich, Ismaninger Stra��e 22, 81675, Munich, Germany.
Daniel Tigard: Department of Philosophy, University of San Diego, San Diego, USA.
Ruth M��ller: Department of Science, Technology and Society (STS), School of Social Science and Technology, Technical University of Munich, Munich, Germany.
Stuart McLennan: Institute of History and Ethics in Medicine, Department of Preclinical Medicine, TUM School of Medicine and Health, Technical University of Munich, Ismaninger Stra��e 22, 81675, Munich, Germany.
Alena Buyx: Institute of History and Ethics in Medicine, Department of Preclinical Medicine, TUM School of Medicine and Health, Technical University of Munich, Ismaninger Stra��e 22, 81675, Munich, Germany.
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.
