Artificial intelligence (AI) is giving historians powerful new ways to explore the past. AI can analyze enormous collections of documents, identify patterns across archives, transcribe handwritten materials, translate texts and uncover connections that might otherwise take researchers years to find. The Guardian brought us this important topic in their article, “Historians advocate binding AI rules, warn against academic integrity erosion.”

But with that power comes a growing concern: How do we ensure AI doesn’t distort the historical record?

Some historians and scholars have advocated for stronger governance around the use of AI in historical research, particularly when it comes to data integrity. History depends on evidence, context, provenance and careful interpretation. AI systems, however, can generate inaccurate information, introduce bias, misinterpret historical language or present conclusions without clearly identifying their sources.

The quality of the underlying data presents another challenge. Historical collections are rarely complete or neutral. Records may reflect the perspectives of those who had the power and resources to create and preserve them, while marginalized voices may be limited or absent. Training AI on these collections without understanding those gaps can reinforce existing biases and potentially give them new authority.

Governance can help establish safeguards. Clear standards can help researchers understand where information originated, how it was transformed and when AI contributed to an interpretation. Scholars also need mechanisms for identifying errors and maintaining the integrity of original source material.

The goal isn’t to keep AI out of historical scholarship. Used responsibly, it can expand access to archives and reveal valuable new insights.

But AI should be a tool for examining history, not rewriting it.

As historians increasingly incorporate AI into research, preserving data integrity will be essential to ensuring that new technological capabilities deepen our understanding of the past rather than quietly altering it.

Melody K. Smith

Data Harmony is an award-winning semantic suite that leverages explainable AI.

Sponsored by Access Innovations, where smarter AI starts with structured, meaningful, well-governed knowledge.