Diana Kwon , Nature; AI is complicating plagiarism. How should scientists respond?
"From accusations that led Harvard University’s president to resign in January, to revelations in February of plagiarized text in peer-review reports, the academic world has been roiled by cases of plagiarism this year.
But a bigger problem looms in scholarly writing. The rapid uptake of generative artificial intelligence (AI) tools — which create text in response to prompts — has raised questions about whether this constitutes plagiarism and under what circumstances it should be allowed. “There’s a whole spectrum of AI use, from completely human-written to completely AI-written — and in the middle, there’s this vast wasteland of confusion,” says Jonathan Bailey, a copyright and plagiarism consultant based in New Orleans, Louisiana.
Generative AI tools such as ChatGPT, which are based on algorithms known as large language models (LLMs), can save time, improve clarity and reduce language barriers. Many researchers now argue that they are permissible in some circumstances and that their use should be fully disclosed.
But such tools complicate an already fraught debate around the improper use of others’ work. LLMs are trained to generate text by digesting vast amounts of previously published writing. As a result, their use could result in something akin to plagiarism — if a researcher passes off the work of a machine as their own, for instance, or if a machine generates text that is very close to a person’s work without attributing the source. The tools can also be used to disguise deliberately plagiarized text, and any use of them is hard to spot. “Defining what we actually mean by academic dishonesty or plagiarism, and where the boundaries are, is going to be very, very difficult,” says Pete Cotton, an ecologist at the University of Plymouth, UK."
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