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

TL;DR

This paper explores how generative AI can support legal fact verification by understanding lawyers' practices and designing trustworthy, accountable AI systems that balance efficiency with professional judgment.

Contribution

It provides novel design insights for human-AI collaboration in legal fact verification, emphasizing trustworthiness and accountability in high-stakes legal contexts.

Findings

Lawyers use GenAI for low-risk tasks like drafting.

Concerns over accuracy and confidentiality limit AI adoption.

Design principles for trustworthy, auditable AI systems are proposed.

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.