Scholarly Communication Support: Planning, Conducting, Disseminating, Promoting, & Assessing Research

"The issues with generative AI chatbots are known: accountability, potential to propagate bias, and not-always-reliable accuracy. But they can also help us humans to think in different and creative ways, and to streamline tedious tasks, which may ultimately be a boon for burdened researchers.

“'Think of GPTs not as a database but as a large collection of extremely smart economists, historians, scientists, and many others whom you can ask questions,' says..." "Tyler Cowan, economist and author of “How to Learn and Teach Economics with Large Language Models, including GPT,” a paper with relevance far beyond economics."

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First of all, differentiate between GenAI chatbots, such as ChatGPT or Claude, and other kinds of AI-powered research tools which may be trained to identify or connect scholarly research, such as Elicit or Research Rabbit. If you want to experiment with using AI in your research activities, ensure you choose a tool appropriate for each given purpose.

With regards to chatbots like ChatGPT, Litmap's Project Lead, Digl, suggests:

DO consider using ChatGPT to:

1. Summarize existing papers. Use handy tricks like “Give me 5 bullet points with a 300 word maximum” to get swift responses.

2. Create a paper outline

3. Rephrase and fix grammar. Plus, you can ask for explanations.

4. Write code

DON'T use ChatGPT to:

1. To find references or papers. ChatGPT is notorious for making up references, including author names, titles, and years of publication. You can even accuse it of doing so, and it happily fesses up.

2. Learn new information. Use summaries as guidelines or pointers to prioritize. Not checking ChatGPT’s responses means potentially trusting its hallucinations.

3. Write your finished text for you.

4. Math, maybe. This was a more serious issue at the launch of ChatGPT, but has potentially since been resolved with recent updates.

Ultimately, any uses of AI in scholarly research and writing should at a minimum reflect these core principles:

• Substantial human contribution;
• Human vetting and guaranteeing, human accountability for accuracy;
• Acknowledgement and transparency regarding AI use.

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IRB Applications

If you plan to use generative AI tools to analyze data from human subjects, you are encouraged to be transparent and specific about this in your IRB application.

• Name the tools you intend to use and how you intend to use it.
• Provide links to the vendor's data security and privacy policies.
• As part of the informed consent process, include an opt-out option for participants who may not want an LLM to process their personal data.

GenAI has has pros and cons for conducting research and writing papers.