Explainable AI in Legal Decision-Making

Note: This article is just one of 60+ sections from our full report titled: The 2024 Legal AI Retrospective - Key Lessons from the Past Year. Please download the full report to check any citations.

Trend 2: Explainable AI (XAI) in legal decision-making

Explainable AI (XAI) has emerged as a crucial tool in the legal domain, addressing the need for transparency, accountability, and trust in AI-driven decision-making processes. We need AI to be explainable so we can understand how it did what it did. XAI is the research field of 'peeking behind the curtain', to figure out the inner workings of the machine. By providing clear explanations for AI-generated outcomes to the user (legal professionals, let's say) then those users know how to interpret and adapt to those legal AI responses. Explainability means you know what you can and can't trust.

This section explores, as of today, the current challenges and research directions of XAI in 7 different aspects, many of them highly relevant to legal practice.

When procuring new Legal AI tools, legal teams should be asking how vendors are tackling these issues.

"Legal AI adoption faces barriers due to a lack of explainability. Lawyers, often underwhelmed by legal AI's unfulfilled promises, require absolute confidence in its accuracy. In high-stakes matters, explainable AI is essential to ensure transparency, reliability, and trust in its results."

Sean A. Harrington, Director of Technology Innovation, University of Oklahoma College of Law, USA