The Year Ahead: AI in Scholarly Publishing 2024

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The Year Ahead: AI in Scholarly Publishing 2024

For the last year and a half, the media and publishing world have generated a lot of buzz and discussion about one particular disruptive technology—artificial intelligence (AI). Though AI is not new to the publishing ecosystem, the launch of ChatGPT and the increased daily usage of Large Language Models (LLMs) for web research, writing assistance, and idea generation has raised questions (and problems) with how developer OpenAI trained its chatbot, how we are using this tech in our daily and professional lives, and what it all means for the future.

As an industry innovator in the use of AI to automate workflows and one of many entities experimenting with new applications of this technology, KGL is taking this opportunity at the start of the year to boldly forecast where AI will take scholarly publishing and beyond during 2024.

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Essential AI Reading: 5 Recently Published Must-Read Books

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Essential AI Reading: 5 Recently Published Must-Read Books

There is no shortage of books being published every year on this hugely important topic – some offering practical solutions towards working with AI to enhance our lives and others painting a pessimistic picture of the future. But with such a fast moving landscape, the bestselling AI titles from just a few years ago are already losing their relevance. With this in mind, here is a list of our recommended AI books that have been published within the last year.

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What to Make of ChatGPT in Scholarly Communications?

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What to Make of ChatGPT in Scholarly Communications?

No matter what you are reading, watching, or listening to, everyone today is talking about ChatGPT and how it can help our daily lives and, perhaps, even our work. Released in November 2022 by OpenAI, ChatGPT is an Artificial Intelligence chat bot that “interacts in a conversational way” and it can “answer follow-up questions, admit its mistakes, challenge incorrect premises, and reject inappropriate requests.”

ChatGPT was quickly embraced by the world for fun and frivolous purposes, but it has also been used to write press releases, news articles, corporate documents, and even essays and journal articles. Though many industries are jumping to see how this new AI can help their business, there are just as many who are being more cautious. In scholarly publishing, there has been much debate about how this new AI can help our industry. KGL has pulled together a round-up of some of the most recent articles to help you make your own decision about ChatGPT.

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Trends in Peer Review: Preprints, Open, AI, and Professional Support

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Trends in Peer Review: Preprints, Open, AI, and Professional Support

A central pillar of academic publishing, peer review has always been a hotly debated, highly politicized, and controversial subject in the industry, and with good reason. While trends frequently come and go, its central premise—the requirement to have scholarly research scrutinized by fellow academics—eternally prevails. But, so do many of the challenges associated with peer review, such as the slowing down of publication, a lack of resources, poor transparency, potential bias and unfairness.

In the midst of the pandemic, the traditional peer review process was left looking tired and exposed, as a deluge of important scientific research required far more dynamic systems of approval to fast-track research and meet the needs of the global battle against COVID-19. As a result, we witnessed a rise of preprints, not to mention subsequent retractions, and an increase in paid peer reviews, as an already time-poor pool of academics found itself stretched more than ever before and demanding remuneration for the overtime.

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Fast-Tracking COVID-19 Research

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Fast-Tracking COVID-19 Research

Five Questions for Debbie McClanahan, KGL’s VP of Journal Publishing Services

I wanted to look deeper into other areas of the research workflow that can be expedited in the cause of helping authors and publishers vet and distribute important discoveries. So I consulted one of our internal experts, KGL’s Debbie McClanahan, VP of Journal Publishing Services, to draw on her decades of experience helping academic publishers take their content from accepted manuscript to copyedited, typeset and verified articles available for download.

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How Publishers Can Put AI to Use in the Pandemic

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How Publishers Can Put AI to Use in the Pandemic

Earlier in the year we predicted how artificial intelligence could impact the industry in 2020—with AI applications being created and perfected to increase discoverability, improve user experience, automate tedious clerical work, analyze trends, and expand the peer review pool. We also noted that publishers were beginning to feel less tentative about adopting these solutions into their workflows. At the time, we could not have imagined that a global pandemic would disrupt the industry and society in the way that it has. So in light of recent events, we wanted to revisit a few ways this technology can immediately be used to assist researchers, publishers, and the wider world.

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AI 2.0: Machine-Generated Content, Intelligent Automation, and the Future of Academic Publishing

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AI 2.0: Machine-Generated Content, Intelligent Automation, and the Future of Academic Publishing

Every year at the Frankfurt Book Fair, there is a buzzword or phrase that continues to pop up on panels, in articles, and in conversations and meetings. In the past, we have seen ‘big data’ and ‘blockchain’ dominate the headlines, but this year’s buzz word (or acronym) was ‘AI,’ as publishers, information professionals, service providers, and the media debated how this technology can be used in the industry.

Because machine learning and artificial intelligence are integral to KGL’s work helping to alleviate pain points for publishers, we partnered with Springer Nature to host a panel entitled “AI 2.0: Machine-Generated Content, Intelligent Automation, and the Future of Academic Publishing.” On the panel, speakers from KGL (Cenveo at the time), HighWire, and Springer Nature talked about everything from workflow automation and high-speed publishing, to companies that use machine learning and AI for discovery, peer review, and even highlighted emerging technologies which allow publishers to offer a broader range of tools and services to serve researchers and authors.

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AI Goes from Disruptive to Imperative

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AI Goes from Disruptive to Imperative

This article first appeared in the Publishers Weekly Frankfurt Show Daily on October 16, 2019.

Publishers have looked on as machine learning technology has developed—but now it’s time to leap.

Over the course of the last five years, AI, natural language processing (NLP), and machine learning (ML) have been much talked about, as well as trialed and tested, in the publishing industry. These technologies are often the focus of panel discussions at conferences such as this one, discussions that have illustrated how AI could be used for a variety of purposes: discovery, peer review, bestseller predictions, and, perhaps most importantly, improving publisher efficiency.

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