Embedded Ethics in Practice: A Toolbox for Integrating the Analysis of Ethical and Social Issues into Healthcare AI Research
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.
Authors
- Maximilian Braun (ORCID: https://orcid.org/0000-0003-4017-1851)
- Amelia Fiske (ORCID: https://orcid.org/0000-0001-7207-6897)
- Daniel W. Tigard (ORCID: https://orcid.org/0000-0003-3633-3563)
- Anja K. Ruess (ORCID: https://orcid.org/0000-0003-2089-6302)
- Stuart McLennan (ORCID: https://orcid.org/0000-0002-2019-6253)
- Bettina Zimmermann (ORCID: https://orcid.org/0000-0001-7047-4496)
- Franziska Schönweitz (ORCID: https://orcid.org/0000-0002-6195-4903)
- Marieke Bak (ORCID: https://orcid.org/0000-0003-0655-0743)
- Lukas J. Meier (ORCID: https://orcid.org/0000-0002-3316-3928)
- Anna Sierawska (ORCID: https://orcid.org/0000-0002-0502-4146)
- Alena Buyx (ORCID: https://orcid.org/0000-0002-5726-7633)
- Theresa Willem (ORCID: https://orcid.org/0000-0001-7643-8816)
- Svenja Breuer (ORCID: https://orcid.org/0000-0002-9686-4852)
- Marie-Christine Fritzsche (ORCID: https://orcid.org/0000-0002-8056-2462)
- Ruth Müller (ORCID: https://orcid.org/0000-0002-2685-0009)
Institutions
- University of Bern (CH)
- Northeastern University (US)
- Harvard University (US)
- University of San Diego (US)
- University of Augsburg (DE)
- University of Basel (CH)
- University of Cambridge (GB)
- Munich School of Philosophy (DE)
- Amsterdam Neuroscience (NL)
- Amsterdam University of Applied Sciences (NL)
- Technical University of Munich (DE)
- Technische Universität Dresden (DE)
Publication Details
- Journal
- Science and Engineering Ethics
- Published
- 2024-12-24
- DOI
- https://doi.org/10.1007/s11948-024-00523-y
- Citations
- 13
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 1.56