Policing plagiarism of ideas in generative AI-assisted research writing

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Policing plagiarism of ideas in generative AI-assisted research writing

Commentary: Onus is on researchers to use GenAI responsibly and ensure integrity, proper attribution

• Plagiarism of ideas harms the research environment by eroding trust among scientists
• Beyond researchers, plagiarism is an ethical concern for students, professionals in law, business and medicine
• 'Checking AI output is still the simple and only way to ensure content is correct and reliable'

CHICAGO --- As more people - including researchers - use generative artificial intelligence (GenAI) in their writing, it's becoming increasingly important to define what plagiarism looks like and how to police it.

A new commentary written by researchers at Northwestern University and the National Institutes of Health (NIH) that will publish May 18 in Nature Machine Intelligence weighs various options on how to define plagiarism in research manuscript writing in the ever-evolving world of GenAI.

The commentary argues plagiarism in manuscript writing harms the research environment by eroding trust among scientists, misrepresenting the origin and authenticity of scholarly work, and discouraging innovation and original inquiry.

Currently, most plagiarism policies address two types of plagiarism: plagiarism of original works, such as text or verbatim plagiarism, and plagiarism of ideas. Since GenAI tools can easily rephrase text, verbatim plagiarism is becoming less of an issue. But plagiarism of ideas, which is essentially a form of intellectual theft, is still an important concern because a GenAI tool may plagiarize underlying ideas without giving appropriate credit.

"It is fine and in fact helpful to use GenAI to increase the readability of writing and bounce ideas back and forth, but we know these tools frequently make mistakes of fact and accuracy and have enormous social and environmental impacts," said corresponding author Mohammad Hosseini, assistant professor of preventive medicine in the division of biostatistics and informatics at Northwestern University Feinberg School of Medicine. "Checking AI output is still the simple and only way to ensure content is correct and reliable."

Because plagiarism of ideas is difficult to detect and enforce, the commentary recommends that definitions of research misconduct - which includes plagiarism as well as data fabrication and falsification - be revised to include that misconduct may be committed by a person when using GenAI tools.

"If a person using GenAI tools does not do their own background research and carefully review the GenAI's output, they may not be aware that the tool has plagiarized," Hosseini said. "By revising the definition, we're hoping to make it clear that those who use GenAI tools are responsible for avoiding plagiarism, which will ultimately promote more responsible use of GenAI tools."

Enforcement of plagiarism goes beyond researchers

When universities or funders conclude that a researcher has committed research misconduct, they may impose sanctions with serious adverse career consequences, including retractions, loss of current funding or debarment from future grants, termination of employment or revocation of academic degrees. But the study authors said this discussion goes beyond writing in the research world.

"Non-researchers should also use GenAI in responsible ways," Hosseini said. "Plagiarism is an ethical and legal concern not just for researchers but also for students and those working in various professions, such as law, business and medicine."

The commentary is titled, "Plagiarism of ideas in the age of generative artificial intelligence." David Resnick, a senior bioethicist at the NIH, is a co-author.

Funding for the commentary was provided by the Intramural Research Program of the NIH and the National Center for Advancing Translational Sciences (grant UM1TR005121) of the NIH.