IN FEBRUARY, GOOGLE released an upgraded version of its Gemini artificial intelligence model. It quickly became a publicity disaster, as people discovered that requests for images of Vikings generated tough-looking Africans while pictures of Nazi soldiers included Asian women. Building in a demand for ethnic diversity had produced absurd inaccuracies.
Academic historians were baffled and appalled. “They obviously didn’t consult historians,” says Benjamin Breen, a historian at the University of California, Santa Cruz. “Every person who cares about the past is just like, ‘What the hell’s going on?’”
Rewriting the past to conform with contemporary political fashions is not at all what historians have in mind for artificial intelligence. Machine learning, large language models (LLMs), machine vision, and other AI tools instead offer a chance to develop a richer, more accurate view of history. AI can decipher damaged manuscripts, translate foreign languages, uncover previously unrecognized patterns, make new connections, and speed up historical research. As teaching tools, AI systems can help students grasp how people in other eras lived and thought.
Historians, Breen argues, are particularly well-suited to take advantage of AI. They’re used to working with texts, including large bodies of work not bound by copyright, and they know not to believe everything they read. “The main thing is being radically skeptical about the source text,” Breen says. When using AI, he says, “I think that’s partly why the history students I’ve worked with are from the get-go more sophisticated than random famous people I’ve seen on Twitter.” Historians scrutinize the results for errors, just as they would check the claims in a 19th-century biography.
Diese Geschichte stammt aus der June 2024-Ausgabe von Reason magazine.
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Diese Geschichte stammt aus der June 2024-Ausgabe von Reason magazine.
Starten Sie Ihre 7-tägige kostenlose Testversion von Magzter GOLD, um auf Tausende kuratierte Premium-Storys sowie über 8.000 Zeitschriften und Zeitungen zuzugreifen.
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