AI is enabling historians to analyze vast amounts of historical data more efficiently than traditional methods. By employing machine learning and deep neural networks, researchers can examine historical documents, such as astronomical tables and court records, to uncover patterns and connections that would be difficult to identify manually. This approach allows for a broader analysis of historical records, correcting distortions that arise from examining documents in isolation.

Historians face several challenges when using AI, including the risk of introducing bias or inaccuracies into the historical record. Machine learning models may struggle with poorly handwritten texts or regional dialects, leading to misinterpretations. Additionally, there is concern about the potential for AI to generate false records or misrepresent historical figures, which could distort our understanding of the past.

Several notable projects are leveraging AI to enhance historical research. For instance, the Venice Time Machine aims to digitize 1,000 years of Venetian state archives, using deep learning to reconstruct historical social networks. Another project, called CorDeep, developed by the Max Planck Institute, classifies content from historical documents, while the Ithaca project by DeepMind focuses on reconstructing missing portions of inscriptions from ancient texts. These initiatives demonstrate the potential of AI to uncover new insights into history.