Drawing on over four years of experience developing the Embedded Ethics and Social Sciences methodology in the field of health AI, I reflect on how we have integrated the analysis of ethical and social issues in a dynamic, practice-oriented way.
Long abstract:
Ethical concerns around artificial intelligence technology have prompted a rush towards ‘AI ethics’ to consider how AI technology can be developed and implemented in an ethical manner. Since 2019, I have been working with my colleagues in the Munich Embedded Ethics Lab (MEEL) at the Technical University of Munich to develop the Embedded Ethics and Social Science Approach (EESS) to address established and emerging concerns with AI. EESS denotes the practice of integrating the consideration of social, ethical and legal issues into the entire AI development process in a deeply integrated, collaborative and interdisciplinary way. Our approach combines methodological and conceptual frameworks from bioethics and the social sciences (in particular STS) to help interdisciplinary development teams anticipate harmful effects and suggest new ways of thinking about ethical and social challenges during development processes.
We have accumulated over four years of experience through seven Embedded Ethics and Social Science projects within various interdisciplinary consortia in the field of health AI. By applying a wide range of methods (ranging from stakeholder interviews to bias analysis to participant observation), we have learned how to incorporate the analysis of ethical and social issues into AI projects in a dynamic, practice-oriented way.