Abductive Reasoning with the GPT-4 Language Model: Case studies from criminal investigation, medical practice, scientific research

TL;DR

This paper assesses GPT-4's ability to perform abductive reasoning across diverse complex domains, demonstrating its potential in hypothesis generation and explanation in fields like medicine, criminology, and cosmology.

Contribution

It provides a systematic evaluation of GPT-4's abductive reasoning capabilities in real-world scenarios, highlighting its reliability and potential applications.

Findings

GPT-4 effectively generated plausible hypotheses in medical diagnostics.

The model provided reasonable explanations in criminology and cosmology.

Results suggest LLMs can assist in complex problem-solving tasks.

Abstract

This study evaluates the GPT-4 Large Language Model's abductive reasoning in complex fields like medical diagnostics, criminology, and cosmology. Using an interactive interview format, the AI assistant demonstrated reliability in generating and selecting hypotheses. It inferred plausible medical diagnoses based on patient data and provided potential causes and explanations in criminology and cosmology. The results highlight the potential of LLMs in complex problem-solving and the need for further research to maximize their practical applications.