2026-06-07T23:41:55Zhttps://docta.ucm.es/rest/oai/request

oai:docta.ucm.es:20.500.14352/1348802026-04-21T00:02:43Zcom_20.500.14352_14col_20.500.14352_15

Can Generative AI Co-Evolve with Human Guidance and Display Non-Utilitarian Moral Behavior? Lahoz Beltra, Rafael The growing presence of autonomous AI systems, such as self-driving cars and humanoid robots, raises critical ethical questions about how these technologies should make moral decisions. Most existing moral machine (MM) models rely on secular, utilitarian principles, which prioritize the greatest good for the greatest number but often overlook the religious and cultural values that shape moral reasoning across different traditions. This paper explores how theological perspectives, particularly those from Christian, Islamic, and East Asian ethical frameworks, can inform and enrich algorithmic ethics in autonomous systems. By integrating these religious values, the study proposes a more inclusive approach to AI decision making that respects diverse beliefs. A key innovation of this research is the use of large language models (LLMs), such as ChatGPT (GPT-5.2), to design with human guidance MM architectures that incorporate these ethical systems. Through Python 3 scripts, the paper demonstrates how autonomous machines, e.g., vehicles and humanoid robots, can make ethically informed decisions based on different religious principles. The aim is to contribute to the development of AI systems that are not only technologically advanced but also culturally sensitive and ethically responsible, ensuring that they align with a wide range of theological values in morally complex situations. 2026-04-20T09:19:04Z 2026-04-20T09:19:04Z 2026-04-20T09:19:04Z 2026-02-02 journal article https://hdl.handle.net/20.500.14352/134880 2079-3197 10.3390/computation14020040 eng Lahoz-Beltra, R. (2026). Can Generative AI Co-Evolve with Human Guidance and Display Non-Utilitarian Moral Behavior? Computation, 14(2). https://doi.org/10.3390/COMPUTATION14020040 http://creativecommons.org/licenses/by/4.0/ open access Attribution 4.0 International MDPI