Reimagining Legal Fact Verification with GenAI: Toward Effective Human-AI Collaboration

Read full text
Authors: Sirui Han, Yuyao Zhang, Yidan Huang, Xueyan Li, Chengzhong Liu, Yike Guo
Cited by: 3
References: 102

Abstract

Fact verification is a critical yet underexplored component of non-litigation legal practice. While existing research has examined automation in legal workflow and human-AI collaboration in high-stakes domains, little is known about how GenAI can support fact verification, a task that demands prudent judgment and strict accountability. To address this, we conducted semi-structured interviews with 18 lawyers to understand their current verification practices, attitudes toward GenAI adoption, and expectations for future systems. We found that while lawyers use GenAI for low-risk tasks like drafting and language optimization, concerns over accuracy, confidentiality, and liability are currently limiting its adoption for fact verification. These concerns translate into core design requirements for AI systems that are trustworthy and accountable. Based on these, we contribute design insights for human-AI collaboration in legal fact verification, emphasizing the development of auditable systems that balance efficiency with professional judgment and uphold ethical and legal accountability in high-stakes practice.

Fields of Study & Subjects

Ethics and Social Impacts of AI Artificial Intelligence in Law Artificial Intelligence in Healthcare and Education

Publication details

Journal / source
Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems
Publisher
ACM
Pages
1–15
Publication date
13 April 2026
Language
EN