Towards AI ethics’ institutionalization: knowledge bridges from business ethics to advance organizational AI ethics

This paper proposes to generate awareness for developing Artificial intelligence (AI) ethics by transferring knowledge from other fields of applied ethics, particularly from business ethics, stressing the role of organizations and processes of institutionalization. With the rapid development of AI systems in recent years, a new and thriving discourse on AI ethics has (re-)emerged, dealing primarily with ethical concepts, theories, and application contexts. We argue that business ethics insights may generate positive knowledge spillovers for AI ethics, given that debates on ethical and social responsibilities have been adopted as voluntary or mandatory regulations for organizations in both national and transnational contexts. Thus, business ethics may transfer knowledge from five core topics and concepts researched and institutionalized to AI ethics: (1) stakeholder management, (2) standardized reporting, (3) corporate governance and regulation, (4) curriculum accreditation, and as a unified topic (5) AI ethics washing derived from greenwashing. In outlining each of these five knowledge bridges, we illustrate current challenges in AI ethics and potential insights from business ethics that may advance the current debate. At the same time, we hold that business ethics can learn from AI ethics in catching up with the digital transformation, allowing for cross-fertilization between the two fields. Future debates in both disciplines of applied ethics may benefit from dialog and cross-fertilization, meant to strengthen the ethical depth and prevent ethics washing or, even worse, ethics bashing.