Can LLMs Create Legally Relevant Summaries and Analyses of Videos?

TL;DR

This paper explores the ability of large language models to understand and generate legally relevant summaries and analyses of videos, demonstrating promising results that could enhance access to justice.

Contribution

It investigates LLMs' capacity to interpret and summarize videos for legal purposes, a novel application beyond traditional text-based tasks.

Findings

71.7% of summaries rated as high or medium quality

Demonstrates potential for LLMs in legal video analysis

Opens avenues for improving access to justice

Abstract

Understanding the legally relevant factual basis of an event and conveying it through text is a key skill of legal professionals. This skill is important for preparing forms (e.g., insurance claims) or other legal documents (e.g., court claims), but often presents a challenge for laypeople. Current AI approaches aim to bridge this gap, but mostly rely on the user to articulate what has happened in text, which may be challenging for many. Here, we investigate the capability of large language models (LLMs) to understand and summarize events occurring in videos. We ask an LLM to summarize and draft legal letters, based on 120 YouTube videos showing legal issues in various domains. Overall, 71.7\% of the summaries were rated as of high or medium quality, which is a promising result, opening the door to a number of applications in e.g. access to justice.