ValueCompass: A Framework of Fundamental Values for Human-AI Alignment
Shen, Hua, Knearem, Tiffany, Ghosh, Reshmi, Yang, Yu-Ju, Mitra, Tanushree, Huang, Yun
–arXiv.org Artificial Intelligence
As AI systems become more advanced, ensuring their alignment with a diverse range of individuals and societal values becomes increasingly critical. But how can we capture fundamental human values and assess the degree to which AI systems align with them? We introduce ValueCompass, a framework of fundamental values, grounded in psychological theory and a systematic review, to identify and evaluate human-AI alignment. We apply ValueCompass to measure the value alignment of humans and language models (LMs) across four real-world vignettes: collaborative writing, education, public sectors, and healthcare. Our findings uncover risky misalignment between humans and LMs, such as LMs agreeing with values like "Choose Own Goals", which are largely disagreed by humans. We also observe values vary across vignettes, underscoring the necessity for context-aware AI alignment strategies. This work provides insights into the design space of human-AI alignment, offering foundations for developing AI that responsibly reflects societal values and ethics.
arXiv.org Artificial Intelligence
Sep-14-2024
- Country:
- Africa (0.04)
- Asia > Middle East
- Jordan (0.04)
- Europe (0.04)
- North America
- Central America (0.04)
- United States
- Illinois > Champaign County
- Louisiana > Orleans Parish
- New Orleans (0.04)
- Massachusetts > Middlesex County
- Cambridge (0.04)
- New York > New York County
- New York City (0.04)
- Virginia (0.04)
- Washington > King County
- Seattle (0.14)
- South America (0.04)
- Genre:
- Questionnaire & Opinion Survey (1.00)
- Research Report
- Experimental Study (1.00)
- New Finding (1.00)
- Industry:
- Education (1.00)
- Government
- Health & Medicine (1.00)
- Information Technology > Security & Privacy (0.67)
- Law (1.00)
- Media > News (0.46)
- Technology:
- Information Technology > Artificial Intelligence
- Applied AI (0.92)
- Issues > Social & Ethical Issues (1.00)
- Machine Learning > Neural Networks
- Deep Learning (1.00)
- Natural Language
- Chatbot (1.00)
- Large Language Model (1.00)
- Representation & Reasoning (1.00)
- Information Technology > Artificial Intelligence