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

2026-02-06

AI Summary

This study addresses the lack of effective AI support for fact-checking in non-litigious legal practice, where attorneys remain cautious about adopting generative AI in high-stakes contexts due to concerns over accuracy, confidentiality, and liability. Through semi-structured interviews with 18 practicing lawyers, the research systematically uncovers current fact-checking practices and key barriers to GenAI adoption. Grounded in the core requirements of trustworthiness and accountability, the work proposes design principles for human-AI collaborative systems tailored to legal fact-checking. It introduces the first auditable collaboration framework that jointly optimizes efficiency, professional judgment, and legal ethics, offering both theoretical foundations and practical guidance for developing reliable, ethically compliant legal AI tools.

Technology Category

• Philosophy and Ethics of AI: Safety, Robustness & Trustworthiness
• Natural Language Processing: Fact-Checking / Misinformation Detection (NLP Focus)
• Humans and AI: Learning Human Values and Preferences

Application Category

• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• Search and Retrieval-Augmented AI: Agentic search
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems

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.

Problem

• legal fact verification
• GenAI
• human-AI collaboration
• accountability
• trustworthy AI

Innovation

• Generative AI
• Legal Fact Verification
• Human-AI Collaboration
• Auditable AI
• Professional Accountability