Researchers appear to be becoming more divided over whether generative artificial intelligence should be used in peer review, with a survey showing entrenched views on either side.

A poll by IOP Publishing found that there has been a big increase in the number of scholars who are positive about the potential impact of new technologies on the process, which is often criticised for being slow and overly burdensome for those involved.

A total of 41 per cent of respondents now see the benefits of AI, up from 12 per cent from a similar survey carried out last year. But this is almost equal to the proportion with negative opinions which stands at 37 per cent after a 2 per cent year-on-year increase.

This leaves only 22 per cent of researchers neutral or unsure about the issue, down from 36 per cent, which IOP said indicates a “growing polarisation in views” as AI use becomes more commonplace.

Women tended to have more negative views about the impact of AI compared with men while junior researchers tended to have a more positive view than their more senior colleagues.

Nearly a third (32 per cent) of those surveyed say they already used AI tools to support them with peer reviews in some form.

Half of these say they apply it in more than one way with the most common use being to assist with editing grammar and improving the flow of text.

A minority used it in more questionable ways such as the 13 per cent who asked the AI to summarise an article they were reviewing – despite confidentiality and data privacy concerns – and the 2 per cent who admitted to uploading an entire manuscript into a chatbot so it could generate a review on their behalf.

IOP – which currently does not allow AI use in peer reviews – said the survey showed a growing recognition that the technology has the potential to “support, rather than replace, the peer review process”.

But publishers must fund ways to “reconcile” the two opposing viewpoints, the publisher added.

A solution could be developing tools that can operate within peer review software, it said, which could support reviewers without positing security or integrity risks.

Publishers should also be more explicit and transparent about why chatbots “are not suitable tools for fully authoring peer review reports”, IOP said.

“These findings highlight the need for clearer community standards and transparency around the use of generative AI in scholarly publishing. As the technology continues to evolve, so too must the frameworks that support ethical and trustworthy peer review,” Laura Feetham-Walker, reviewer engagement manager at IOP and lead author of the study, said.

tom.williams@timeshighereducation.com

Now, the company’s “Hear the Highlights” feature has extended to all users, CNBC reported Sunday (Sept. 14), arguing this could replace user-created reviews as the main source of product information.

Among the advantages here, the report added, is that artificial intelligence (AI) won’t suffer from cognitive overload from combing through thousands of reviews. 

“It’s important to recognize where AI is currently strong, such as in automation and pattern recognition, and where it still falls short, like in judgment-heavy tasks,” said Ankur Edkie, co-founder and CEO of Murf AI, which develops AI voiceovers. “A key question is whether there’s a way to factor in customer context as an input while generating these summaries.”

The value of AI, according to Edkie, is determining the right “problem-capability fit.” Without that, he added, a sense of “gimmickry” is likely to filter through thanks to AI fatigue, which he says consumers are likely feeling by now.

PYMNTS has contacted Amazon for comment but has not yet gotten a reply.

The CNBC report also noted that the tendency of AI to focus on common themes can water down responses even as it summarizes them, taking out the detailed personal experiences found in human reviews.

“AI might overlook unique insights or niche needs that don’t align with the majority of responses,” said Brian Numainville, principal at consumer research firm Feedback Group. “Additionally, the ability to critically interpret reviews — like spotting biases or trusting certain reviewers — is diminished with AI summaries.”

Nauman Dawalatabad, a research scientist at Zoom Communications, offered his opinion that the technology is on its way to improving customer experience.

“I take it as technology helping us to make informed decisions,” he said, pointing to the mental fatigue and wasted time that can result from working through customer reviews.

Meanwhile, recent research by PYMNTS Intelligence shows that AI shopping adoption has begun to gain traction with younger and middle-aged consumers. The research found that 32% of all consumers said they have used or would use generative AI for shopping.

“Bridge millennials — older millennials straddling Gen X — lead the way, with 38% reporting AI use for shopping,” PYMNTS wrote last month. “Zillennials are close behind at 36%, followed by millennials at 35%. Gen X is next, at 33%, while Gen Z comes in at 31%. Baby boomers show some traction as well, with 28% using gen AI for shopping.”