An Anthropologist LLM to Elicit Users' Moral Preferences through Role-Play
This addresses the need to capture individual moral preferences for software developers, though it is incremental as it builds on existing distinctions in ethics and LLM methods.
This study tackled the problem of eliciting users' moral preferences by using immersive role-playing games combined with LLM analysis, focusing on digital privacy scenarios, and found that this approach significantly enhanced the model's ability to predict user behavior, effectively automating the understanding of moral decision-making in software development.
This study investigates a novel approach to eliciting users' moral decision-making by combining immersive roleplaying games with LLM analysis capabilities. Building on the distinction introduced by Floridi between hard ethics inspiring and shaping laws-and soft ethics-moral preferences guiding individual behavior within the free space of decisions compliant to laws-we focus on capturing the latter through contextrich, narrative-driven interactions. Grounded in anthropological methods, the role-playing game exposes participants to ethically charged scenarios in the domain of digital privacy. Data collected during the sessions were interpreted by a customized LLM ("GPT Anthropologist"). Evaluation through a cross-validation process shows that both the richness of the data and the interpretive framing significantly enhance the model's ability to predict user behavior. Results show that LLMs can be effectively employed to automate and enhance the understanding of user moral preferences and decision-making process in the early stages of software development.