Using ChatGPT to Support Criminal Investigations: A Comparative Study of AI and Human Query

Abstract

This paper examines the role of advanced Artificial Intelligence (AI), particularly Large Language Models (LLMs) like ChatGPT, in supporting and enhancing criminal investigations. We focus on the integration of AI in query generation, intelligence analysis, and the interpretation of vast datasets to identify patterns and connections within criminal activities. Through a comparative study involving human participants and ChatGPT, we investigate the effectiveness of AI-generated queries in the 'North by Southwest' scenario, a simulated criminal case involving drug trafficking and money laundering. The ChatGPT study evaluates the AI's ability to generate a coherent investigation strategy and sequence investigative questions effectively. The human study, involving eight female Ph.D. candidates, assesses the strategies individuals employ when reasoning and developing hypotheses from ambiguous information, specifically focusing on three analytical approaches: following money, crimes, and people. Our findings highlight the complementary nature of AI and human analytical approaches. While ChatGPT provides a structured framework for sifting through evidence, human participants offer detailed, situational insights, particularly in connecting financial, criminal, and interpersonal elements. The study underlines the necessity of evaluating the accuracy and reliability of LLMs, considering the ethical implications and potential biases inherent in AI technologies. We conclude that a collaborative approach, utilizing both AI and human intelligence, can lead to more thorough and efficient investigations, ensuring that AI serves as an augmentative tool rather than a substitute for human expertise in the pursuit of justice.

Keywords: Criminal Investigations, Data, Frame Model, Large Language Models (LLMs), ChatGPT

DOI: 10.54941/ahfe1004661