The ethics of AI value chains
Researchers, practitioners, and policymakers with an interest in the ethics of artificial intelligence (AI) need more integrative approaches for studying and intervening in AI systems across many contexts and scales of activity. This paper presents AI value chains as an integrative concept that satisfies that need. To more clearly theorize AI value chains and conceptually distinguish them from supply chains, we review theories of value chains and AI value chains from strategic management, service science, economic geography, industry, government, and applied research literature. We then conduct an integrative review of a sample of 67 sources that cover the ethical concerns implicated in AI value chains. Building upon the findings of our integrative review, we recommend three future directions that researchers, practitioners, and policymakers can take to advance more ethical practices across AI value chains. We urge AI ethics researchers and practitioners to move toward value chain perspectives that situate actors in context, account for the many types of resources involved in cocreating AI systems, and integrate a wider range of ethical concerns across contexts and scales.
Authors
- Blair Attard-Frost (ORCID: https://orcid.org/0000-0001-8433-2317)
- David Gray Widder (ORCID: https://orcid.org/0000-0002-6912-8067)
Institutions
- University of Toronto (CA)
- Cornell University (US)
Publication Details
- Journal
- Big Data & Society
- Published
- 2025-05-06
- DOI
- https://doi.org/10.1177/20539517251340603
- Citations
- 8
- Primary Topic
- Ethics and Social Impacts of AI
- Type
- article
- Field-Weighted Citation Impact
- 18.93
Funders
- Social Sciences and Humanities Research Council of Canada