How to Make a Paper with Generative Artificial Intelligence Explicit: An Example for a Non-Comotive Peer Review System

Generative artificial intelligence can be useful in the peer review process. Pick out the main points and areas for review after you have read the manuscript. Then, use the AI to help organize and articulate your feedback (without directly inputting or uploading the manuscript’s text, thus avoiding privacy concerns). For example, you might instruct the AI: “Assume you’re an expert and seasoned scholar with 20+ years of academic experience in [field]. On the basis of my summary of a paper in [field], where the main focus is on [general topic], provide a detailed review of this paper, in the following order: 1) briefly discuss its core content; 2) identify its limitations; and 3) explain the significance of each limitation in order of importance. A professional tone is maintained throughout.

Giving precise instructions is a key to success no matter which generative-ai tool you choose. The clearer you are, the better. “I’m writing a paper on topic for a leading academic journal.” What I tried to say in the following section is [specific point]. Ensure each paragraph flows into the next by re-wording it. Remove jargon. Talk with a professional tone. You can use the same technique again later on, to clarify your responses to reviewer comments.

The first reply might not be perfect, but it is a collaborative and iterative process. You might need to make changes to your instructions if you are talking about a concept with a colleague. It’s the interaction that improves the results. Don’t hesitate to say “this isn’t what I meant” if something doesn’t quite hit the mark. Let’s adjust this part.” Or you can commend its improvements: “This is much clearer, but let’s tweak the ending for a stronger transition to the next section.”

After evaluating a paper and observing its pros and cons, I might feed these into CHATGPL and ask it to draft a letter for the author. Highlight the manuscript’s key issues and clearly explain why the manuscript, despite its interesting topic, might not provide a substantial enough advancement to merit publication. Avoid jargon. Be direct. Maintain a professional and respectful tone throughout.” It might take a few tries to get the tone and content right.

I’ve found that this approach both enhances the quality of my feedback and helps to guarantee that I convey my thoughts supportively. The result is a more positive and productive dialogue between editors and authors.

What can students learn if their work is written by a generative AI tool? An update from Generative AI for the plagiarism detection company

Students have submitted more than 22 million papers that may have used generativeai in the past year according to new data released by the plagiarism detection company.

Students also aren’t tempted by only ChatGPT and similar large language models. Word spinners are an example of a software that rewrites text, and may be less obvious to a teacher if she knows the work is being generated by artificial intelligence. Annie Chechitelli, the company’s chief product officer, said that the company’s artificial intelligence detector has been updated to detect word spinners. It can also flag work that was rewritten by services like spell checker Grammarly, which now has its own generative AI tool. What students can and cannot do becomes more complicated with the addition of generative artificial intelligence components.