Bias Awareness in Scholarly Publishing

Bias Awareness in Scholarly Publishing

Earlier this year, we published a report entitled Diversity, Equity and Inclusion in Educational Content: What You Need to Know Now, providing publishers with a starting point and ongoing solutions for how to make their content more representative of the audience engaging with it. 

As publishers and their stakeholders begin to work toward making their content more inclusive, one of the most difficult challenges they face is not recognizing their own implicit biases and how they might impact the quality and reach of their publications. 

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

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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How Journals Can Improve Gender Diversity in Peer Review

How Journals Can Improve Gender Diversity in Peer Review

Research increasingly shows how gender affects the peer-review process, and how it doesn’t. For example, some studies indicate that editor gender appears to have some influence over gender diversity among peer reviewers, but gender of authors, editors and reviewers may not necessarily influence which papers are accepted or rejected.

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Bias in AI: Lessons for Publishers

Bias in AI: Lessons for Publishers

During the Frankfurt Book Fair, we teamed up with Springer Nature to host a panel debate entitled “AI 2.0: Machine-Generated Content, Intelligent Automation, and the Future of Academic Publishing” in which speakers from KGL (Cenveo at the time), HighWire Press, and Springer Nature explored ways in which publishers are implementing artificial intelligence and machine learning.

During the discussion, the panelists were asked if there are any drawbacks for publishers relying on this technology to automate processes. Jim Longo, VP of Product Management for HighWire, noted that one of the challenges that has come up is the issue of bias. Because humans are at the heart of writing the code or training machines to perform tasks, the technology is reliant on the perspectives and experiences of those individuals creating the algorithms that could inherently lead to unintended bias.

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

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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