What is the value of machine learning or generative AI in historical research?
Short answerIt can be another analytical tool for bridging gaps, but its conclusions remain judgments shaped by training and design rather than automatically correct answers.
NotesHistorians already make careful judgment calls when evidence leaves gaps, so computational assistance is not rejected in principle. The concern is that users may mistake machine output for certainty and overlook assumptions supplied by programmers and training data. A system built mainly by modern technical specialists may also struggle to reconstruct the mental world of earlier generations, a central skill of historical interpretation. AI is therefore treated like a colleague whose reasoning can be useful, challenged, and rejected when the evidence does not support it.