Giving the Emperor clothes: operationalizing AI ethics principles in corporations
Abstract Artificial intelligence (AI) technologies raise enormous questions for society and how we should live. For corporations, AI raises questions about how organizations ought to incorporate principles and other forms of ethical guidance into their work. The movement from theory to practice, or “the operationalization question” demands that organizations not only have good intentions, but actual institutionalized approaches towards ethical problem solving. In this paper, we look at the movement from theory to practice, and particularly at the use of principles as a way to guide ethical behavior, considering, first, why implementation of principles is difficult, second, how to move from abstract principles to actionable principles, and third, illustrating this progression through seven real-life AI cases. These seven cases each relate to an ethical principle: (1) protecting human dignity and rights, and the International Baccalaureate exam replacement by algorithm, (2) promoting human well-being, and Amazon warehouse worker injuries, (3) investing in humanity, and the Partnership on AI’s work to bring together AI corporations and civil society, (4) promoting inclusion, and IBM’s response to the Gender Shades study, (5) protecting the environment, and Hugging Face’s tracking AI energy use, (6) maintaining accountability, and the Christchurch, New Zealand mass shooting response by Facebook and Western Digital, (7) and, lastly, promoting transparency, and AI model cards. The cases model the movement from abstract principle to concrete action, and collectively illustrate a pattern that can be repeated in many contexts, thus demonstrating a new possible solution for organizations implementing ethics.
Authors
- Ann Gregg Skeet
- Brian Patrick Green (ORCID: https://orcid.org/0000-0002-7125-3086)
Publication Details
- Journal
- AI and Ethics
- Published
- 2026-10-08
- DOI
- https://doi.org/10.1007/s43681-026-01348-0
- Primary Topic
- Ethics and Social Impacts of AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00