arXiv:2605.30036v1 Announce Type: new Abstract: Large Language Models (LLMs) demonstrate a remarkable capacity to adopt different personas and roles; however, it remains unclear whether they can manifest behavior that adheres to a coherent, human-like value structure. In this work, we draw on established psychological value theory to induce human-like values in LLMs and assess their alignment with patterns observed in human studies. Using validated psychological questionnaires, we conduct large-scale experiments -- over 5 million questions -- to evaluate value structures and value-behavior rel
The rapid advancement of LLMs necessitates understanding and controlling their ethical and behavioral frameworks, making the development of human-like value systems a critical immediate challenge.
A strategic reader should care as LLM alignment with human values impacts trust, regulatory frameworks, and the safe deployment of AI across all sectors.
This research suggests a pathway to more reliably instill human-like value structures in LLMs, potentially leading to more predictable and ethically aligned AI behavior.
- · AI developers
- · Ethical AI advocates
- · Organizations deploying LLMs
- · Malicious actors
- · Developers of unaligned AI systems
Further research and development will focus on robust methods for value induction and alignment in AI.
Public and regulatory bodies will gain confidence in deploying increasingly autonomous AI systems in sensitive domains.
The definition of 'human-like' values in AI may become a new philosophical and societal debate as AI capabilities advance.
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Read at arXiv cs.AI