The Socratic Dialogue as a Method for Virtue Ethics in AI: A Case Study
DOI:
https://doi.org/10.1609/aies.v8i3.36748Abstract
This paper investigates how the Socratic Dialogue can cultivate moral virtues among AI practitioners, focusing on core virtues identified by Hagendorff as essential to ethical AI practice: justice, care, honesty, responsibility, practical wisdom (phronesis), and fortitude. Using a case study conducted at a financial bank’s transaction monitoring department, we examine how structured ethical deliberation cultivates the dispositions needed to navigate moral complexity in AI ethics. Seven participants, including data scientists, legal specialists, and ethics experts, engaged in a facilitated Socratic Dialogue centered on an ethical dilemma involving AI-driven detection of financial fraud and terrorist activity. Through abductive analysis, we found that tensions emerged within key virtues, illustrating the complexities of ethical decision-making in AI systems. Through the collective nature of the dialogue, participants developed a more refined and context-sensitive understanding of key virtues, exploring what it means to be just, caring, honest, or responsible in practice by navigating within them. This process cultivated practical wisdom not as a solitary trait, but as a relational capacity fostered through shared reflection and moral reasoning. Additionally, the method strengthens fortitude, encouraging AI practitioners to voice ethical concerns despite situational pressures. While challenges remain, such as time investment, facilitation demands, and existing power imbalances, the Socratic Dialogue offers a promising foundation for virtue-oriented AI ethics that moves beyond compliance frameworks toward deeper moral engagement.Downloads
Published
2025-10-15
How to Cite
Wilders, M., Martínez de Rituerto de Troya, Íñigo, & Dobbe, R. (2025). The Socratic Dialogue as a Method for Virtue Ethics in AI: A Case Study. Proceedings of the AAAI ACM Conference on AI, Ethics, and Society, 8(3), 2680–2691. https://doi.org/10.1609/aies.v8i3.36748