Google's NotebookLM (formerly Gemini Notebook) is becoming a practical tool for historians conducting research and analyzing primary sources, but experts warn that the technology's accuracy problems pose serious risks to historical scholarship. An editor and writer specializing in Civil War history has documented both the genuine benefits and significant pitfalls of using AI for historical work, offering a cautionary roadmap for other scholars navigating this rapidly evolving landscape.

What Can NotebookLM Actually Do for Historical Research?

NotebookLM and similar large language models (LLMs), which are AI systems trained on vast amounts of text data to predict and generate human-like responses, have proven surprisingly useful for specific historical tasks. Rather than replacing historians, the tool functions as a research assistant that can handle time-consuming administrative work. One historian used NotebookLM to transcribe a 35,000-word Civil War veteran's novel that was originally published across multiple issues of an Australian newspaper in the 1880s. While every word still required manual verification against the original source, the AI saved hours of manual typing.

Beyond transcription, historians are discovering other practical applications for the technology:

• Data Organization: Creating detailed character lists, family trees, and narrative timelines for complex historical texts and stories
• Editorial Support: Conducting basic grammar, spelling, and punctuation checks on manuscripts before final review
• Content Analysis: Identifying missing or indecipherable words in primary source documents and suggesting interpretations
• Multimedia Creation: Generating podcast-style chapter analyses and audio content from written historical materials
• Research Brainstorming: Helping uncover questions readers might have about a historical narrative and identifying strengths and weaknesses in arguments

Why Are Historians Concerned About AI-Generated Historical Content?

Despite these practical benefits, historians are raising serious alarms about how AI is being used to create and distribute historical information online. The core problem is accuracy. AI systems are trained on content scraped from the internet, and when that content contains bias or inaccuracies, those errors get amplified and redistributed as fact. Google's AI Overview feature, which summarizes search results for users, has become a particular concern. Many people trust these summaries without verification, but historians report finding factual claims in AI Overviews that do not actually appear in the linked sources.

The problem extends beyond text. An explosion of historical content creators are using AI image generation tools to create or "enhance" historical photographs and illustrations, often introducing significant errors. These include fake headgear, fantasy uniforms, and weapons that never existed. When these distorted images appear on blog posts, YouTube channels, and book covers, they undermine the credibility of the historical content itself, even when the writing is accurate.

How to Verify AI-Generated Historical Information

• Request Specific Citations: Ask AI tools for the exact quote, page number, section reference, and direct link to the source material before accepting any historical claim
• Cross-Check Every Fact: Independently verify information by consulting the original source document rather than relying on AI summaries or overviews
• Scrutinize Images Carefully: Examine historical images for signs of AI manipulation or generation, including anatomically impossible details, inconsistent lighting, or distorted period-appropriate items
• Prioritize Authenticity: Avoid using AI-generated or heavily "enhanced" images in historical publications; preserve original materials with minimal alteration

What Does the Future of AI-Assisted History Look Like?

As AI tools become more capable and widespread, historians face a choice: adapt or risk becoming obsolete. However, adaptation does not mean abandoning scholarly rigor. Instead, historians are discovering that their lived experience and direct engagement with historical sites, archives, and communities represent something AI cannot replicate. A historian noted that AI cannot physically visit museums, libraries, and archives to page through unpublished materials, nor can it capture the emotional and intellectual journey of conducting original research.

The emerging consensus among historians is that the future belongs to those who pair rigorous historical research with authentic lived experience. This approach, sometimes called "quasi-reporting, quasi-experiential" history work, combines traditional scholarship with personal narrative and direct observation. As AI-generated content becomes increasingly prevalent across the internet, readers are growing fatigued by generic, AI-produced material and are actively seeking authentic storytelling from real people with genuine expertise and experience.

For historians willing to embrace AI as a tool while maintaining strict standards for accuracy and authenticity, the technology offers real productivity gains. But the responsibility to fact-check, verify sources, and preserve historical integrity rests entirely with the human scholar. AI can simulate experience and knowledge, but it cannot replace the judgment, accountability, and ethical commitment that define serious historical work.