20206-09-25 北陸先端科学技術大学院大学,早稲田大学
＜関連情報＞
- https://www.jaist.ac.jp/whatsnew/press/2026/09/25-1.html
- https://www.sciencedirect.com/science/article/pii/S2666165926001651
健康を支える都市環境のデザインに関する大規模言語モデル生成助言文の倫理的評価 Ethical assessment of large language model-generated advisory text on designing the built environment for health
Mohammad Javad Koohsari, Becky P.Y. Loo, Jing Zhao, Jiuling Li, Ying Long, Yi Lu, Koichiro Oka, Andrew T. Kaczynski
Developments in the Built Environment Available online: 10 August 2026
DOI:https://doi.org/10.1016/j.dibe.2026.101007
Highlights
- This paper examines ethical properties of LLMs in urban design advice for health.
- LLMs produced non-maleficent health solutions across diverse income contexts.
- Human judgment is essential in urban health strategies informed by LLMs.
Abstract
Large language models (LLMs) can generate advisory text on modifying built environments to support health. This study examined the ethical properties of a recent LLM generating text on built environments to support health. The prompts covered six health-related pathways in higher-income, lower-income, and mixed-income neighbourhoods. Overall, 180 answers were coded against four ethical criteria. Non-maleficence was satisfied in all answers. Lower-income contexts were rarely offered weaker proposals than higher-income contexts. Reference to collective participation and transparent oversight appeared in 70-90% of answers without a budget constraint, but only 30-50% under one. The LLM more consistently met minimum expectations for harm avoidance and distributive justice than for collective participation and transparent oversight. These findings suggest that current LLM outputs may reproduce some baseline ethical conventions in urban design discourse but are less reliable on procedural concerns. LLM-generated outputs should therefore be interpreted cautiously within existing built environment decision-making processes.
