Bridging History with AI A Comparative Evaluation of GPT 3.5, GPT4, and
  GoogleBARD in Predictive Accuracy and Fact Checking
Davut Emre Tasar Ceren Ocal Tasar
The rapid proliferation of information in the digital era underscores the
importance of accurate historical representation and interpretation. While
artificial intelligence has shown promise in various fields, its potential for
historical fact-checking and gap-filling remains largely untapped. This study
evaluates the performance of three large language models LLMs GPT 3.5, GPT 4,
and GoogleBARD in the context of predicting and verifying historical events
based on given data. A novel metric, Distance to Reality (DTR), is introduced
to assess the models' outputs against established historical facts. The results
reveal a substantial potential for AI in historical studies, with GPT 4
demonstrating superior performance. This paper underscores the need for further
research into AI's role in enriching our understanding of the past and bridging
historical knowledge gaps.