Navigating the AI Landscape in Scholarly Publishing: 5 Key Insights

Navigating the AI Landscape in Scholarly Publishing: 5 Key Insights

Navigating the AI Landscape in Scholarly Publishing: 5 Key Insights

Recently, we had the privilege of attending an enlightening webinar hosted by the ALPSP on the uses of AI in scholarly publishing, and discovered how AI tools are already shaping the publishing landscape in ways we never imagined. We're excited to share our five main takeaways with you.

But first, let's demystify AI. It's not just a buzzword; it's a vast umbrella term encompassing a vast suite of solutions designed to tackle various tasks using computers. From statistical learning tools to more recent chatbots and generative technology, AI has been around for a long time and is now revolutionising how we approach scholarly publishing.

So, what did we learn?

  1. Choose the Right Tool for the Job: Just like you wouldn't use a hammer to tighten a screw, each AI tool is tailored for specific functions. ChatGPT might struggle with basic Maths but is excellent with blocks of text, and Midjourney can create fantastic graphics but is not suitable for writing speeches. Among the many mentioned in the webinar, Bloom, Claude 2.0, and Dall.E have amazing potential and are designed and tested specifically for scholarly research and publishing. Also let’s not forget about the many plugins for ChatGPT (nearly a thousand already in use!). Understanding the strengths and limitations of each tool is key to maximising their utility. 
  2. Quality Data In, Quality Results Out: Garbage in, garbage out—this holds very true for AI. The quality of the data we feed AI directly impacts the outcomes. Moreover, biases or gaps within the data can lead to bias in AI-generated content. Awareness of these biases is crucial as AI uncovers patterns that human eyes might miss.
  3. Unlocking the Potential of AI: AI isn't just a tool; it's a catalyst for innovation. In scientific research, AI has boosted incredible advancements in cancer detection and data analysis, for instance. Legitimate use of chatbots helps with breaking writer’s block, turning bullet points into full prose, changing tone of your writing, and helping non-native speakers with fluent idiomatic writing. Looking specifically at scholarly publishing, generative AI can be used for editorial, production and reader engagement tasks, such as manuscript assessments, typesetting and indexing, enriching metadata, providing summaries and synthesis, aiding discoverability, and generating alternative formats like audio, video or different language content to increase accessibility. However, leveraging AI requires diligence and transparency to harness its full potential.
  4. Proceed with Caution: While AI holds immense promise, it's not without its pitfalls. AI tools aren't yet validated for peer review and critical appraisal, posing concerns about quality control and confidentiality breaches. Additionally, reliance on AI shouldn't overshadow the importance of honing essential skills like critical appraisal and writing abilities.
  5. Disclosure is Key: While the publishers’ consensus is that AI isn't to be listed as an author, its use should be transparently disclosed in research papers. Details about the version and model used must be included in the methods or acknowledgments section to uphold research integrity, and, where possible, prompts and data fed to the AI tool should be included as well. 
Artificial Intelligence

In essence, using AI in scholarly research can have enormous advantages, as long as one respects the key principles of honesty, transparency, accountability, care, and rigour. It's about striking a balance between embracing innovation and upholding academic standards: remember to detail how the tools were used, check for inadvertent plagiarism, ensure tools are validated for that use and always consider if there are better alternatives. You are ultimately responsible for the output, not the AI tool.

As we navigate the ever-evolving landscape of scholarly publishing, let's remember that AI is a tool—a powerful one, but a tool nonetheless. With transparency, diligence, and a commitment to excellence, we can harness the transformative potential of AI while preserving the integrity of scholarly research.

For further discussion on this and many other topics, we encourage you to visit ALPSP for wonderful insights and more resources and discussions. And if you’re interested in further uses of AI for commercial publishing, make sure to check out the recording of our very own LinkedIn Live event where we spoke to some amazing AI experts in Publishing! 




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