Principal Trait Analysis: Towards Deriving "Skills" in Human-AI Collaboration
Large Language Model-powered agents are increasingly used in the workplace via human-artificial intelligence (AI) collaboration. In this new era of work, it is important to understand the kinds of prompting traits that contribute to task success. Moreover, we need to uncover key skills required for modern professionals and inform educators on how to foster these skills among students. Existing guidelines for human-AI collaboration are built from either top-down theory or context-specific observations of human-AI interactions. However, since LLM capabilities are rapidly improving, theory may not be able to explain emerging interaction patterns, and empirical guidelines may become obsolete ...
| Authors | Hunter McNichols, Kai Du, Andrew Lan |
|---|---|
| Primary category | cs.CL |
| Published | 11 August 2026 |
| Last updated at source | 11 August 2026 |
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