Knowing But Not Doing: Convergent Morality and Divergent Action in LLMs
NeutralArtificial Intelligence
- A recent study introduced ValAct-15k, a dataset comprising 3,000 advice-seeking scenarios from Reddit, aimed at evaluating how Large Language Models (LLMs) represent and enact human values based on Schwartz Theory of Basic Human Values. The study assessed ten frontier LLMs from both U.S. and Chinese companies, revealing a significant knowledge-action gap where both LLMs and human participants exhibited weak correspondence between self-reported and enacted values.
- This development highlights the critical issue of value alignment in artificial intelligence, emphasizing the need for LLMs to not only understand human values but also to act in accordance with them. The findings suggest that while LLMs demonstrate consistency in decision-making, their ability to translate knowledge into action remains limited, raising concerns about their reliability in real-world applications.
- The research underscores ongoing debates regarding the ethical implications of AI and the challenges of aligning machine behavior with human values. As LLMs are increasingly utilized in various sectors, including legal interpretation and user interaction, the discrepancies between their programmed values and actual outputs could lead to broader societal implications, including biases and misrepresentation of diverse perspectives.
— via World Pulse Now AI Editorial System
