Can AI Learn to Cite Sources Like a Genealogist?
As artificial intelligence systems grow more advanced, researchers are exploring whether AI can be trained to follow citation guidelines used by genealogists and historians. Proper source citation is crucial for validating facts and tracing information back to its origins. However, some formats like Elizabeth Shown Mills' Evidence Explained have intricate rules that may prove challenging for AI to learn.
On one hand, AI shows promise for understanding context and extracting key details necessary for citations, like author names, titles, publication dates, and page numbers. With enough training data, an AI agent might learn to identify those elements and assemble them into a properly-structured citation.
However, some aspects of evidence analysis may be more difficult to automate. Determining the quality and reliability of a source requires human judgement. An AI system would struggle to evaluate issues like potential author bias or recognize inconsistencies within a source. It may have trouble distinguishing between similar but distinct source types that require different citation formats.
Adapting to new source materials could also pose a problem. An AI agent with fixed training on certain citation styles and source types might fail to properly cite an unfamiliar resource unless the system can continue learning. The many potential exceptions and niche cases in detailed citation formats could prove challenging for AI to cover exhaustively.
In the future, AI assistance could aid historians and genealogists in quickly compiling citations, but human oversight would still be necessary. While AI shows promise for understanding key patterns, only human intelligence can make evaluative source analysis judgments required for fully valid citations. Advances in AI may one day get close to mimicking formats like Evidence Explained, but cannot yet match a trained genealogist's citation skills.