Large Language Models versus Fuzzy Cognitive Maps for Solving Moral Dilemmas
Large Language Models versus Fuzzy Cognitive Maps for Solving Moral Dilemmas
Author(s): Lukas J. MeierSubject(s): Applied Linguistics, Ethics / Practical Philosophy, Special Branches of Philosophy, Computational linguistics, Philosophy of Science, ICT Information and Communications Technologies
Published by: KruZak
Keywords: Artificial intelligence; ChatGPT; decision-making; ethics consultation; generative AI; large language models; METHAD; principlism;
Summary/Abstract: Which is better at doing medical ethics: conversational artificial intelligence bots like ChatGPT or tools based on fuzzy cognitive maps? The article compares the performance of chatbots that rely on large language models to that of our own METHAD algorithm. While both tools approach dilemmas in medical ethics through the lens of Beauchamp and Childress’ mid-level principles, ChatGPT and METHAD differ considerably in the format of their inputs and outputs, in their interpretability, and in the kinds of mistakes that they make. An ideal advisory algorithm would combine their characteristics.
Journal: Croatian Journal of Philosophy
- Issue Year: XXVI/2026
- Issue No: 76
- Page Range: 41-47
- Page Count: 7
- Language: English
