Large language models (LLMs) are transforming global decision-making and societal systems by processing diverse data at unprecedented scales. However, their potential to homogenize human values poses critical risks, similar to biodiversity loss undermining ecological resilience. Rooted in the ancient Greek concept of ethos, meaning both individual character and the shared moral fabric of communities, EthosGPT draws on a tradition that spans from Aristotle's virtue ethics to Adam Smith's moral sentiments as the ethical foundation of economic cooperation. These traditions underscore the vital role of value diversity in fostering social trust, institutional legitimacy, and long-term prosperity. EthosGPT addresses the challenge of value homogenization by introducing an open-source framework for mapping and evaluating LLMs within a global scale of human values. Using international survey data on cultural indices, prompt-based assessments, and comparative statistical analyses, EthosGPT reveals both the adaptability and biases of LLMs across regions and cultures. It offers actionable insights for developing inclusive LLMs, such as diversifying training data and preserving endangered cultural heritage to ensure representation in AI systems. These contributions align with the United Nations Sustainable Development Goals (SDGs), especially SDG 10 (Reduced Inequalities), SDG 11.4 (Cultural Heritage Preservation), and SDG 16 (Peace, Justice and Strong Institutions). Through interdisciplinary collaboration, EthosGPT promotes AI systems that are both technically robust and ethically inclusive, advancing value plurality as a cornerstone for sustainable and equitable futures.

本研究集中解决大语言模型可能导致的人类价值同质化问题，影响社会信任和长期繁荣。通过推出一个开放源码的框架，EthosGPT能够在全球范围内映射和评估人类价值，并揭示不同地区和文化中模型的适应性和偏见。这项工作的显著发现为开发更具包容性的语言模型提供了切实可行的见解，尤其在文化遗产保护和减少不平等方面具有重要影响。

EthosGPT：映射人类价值多样性以推动可持续发展目标