The strength of artificial intelligence lies in its ability to process and analyze huge amounts of data. It can find patterns, tease out connections, even find related data, but AI lacks the spark of creativity necessary to make inferences from the data or to understand what the data actually mean or how they can be used. Additionally, generative AI tools like ChatGPT are known to “hallucinate” or generate false statements. This limits AI’s usefulness in research. The two most effective use cases for AI in research are:
As a search tool. AI’s strengths make it highly effective in assisting researchers with secondary research or literature reviews by identifying papers related to your topic. AI should NOT be used as the only tool for secondary research, though. While it is able to process vast quantities of published texts, it is constrained by copyright and licensing considerations to searching and analyzing only those materials freely available on the public web or for which the AI provider has purchased licensing rights. Currently, no AI research assistants can fully access the majority of material behind paywalls, which includes most scientific and technical research papers. For this reason AI should always be used in conjunction with traditional database searches.
As a summarizing tool. Generative AI can be used effectively as a tool for summarizing or paraphrasing other people's work or creating abstracts of your own papers. Generative AI should be used with care for these purposes. AI algorithms cannot truly understand the passages they're asked to review or summarize and rely instead on comparing the text to other text samples or iteratively replacing words and rearranging text—a process known as "patch writing." Without true understanding of the original text, generative AI can introduce misinterpretations and other errors or, if used in research papers or assignments, open the author to charges of plagiarism. A close reading of the results is essential to ensure the AI did not misrepresent the original text or replicate the original too closely.
Researchers should NEVER submit the key parts of their research or manuscripts for analysis to any of the AI tools for any reason. By doing so, the text of your manuscript becomes part of the dataset used by the AI and thus becomes publicly accessible and can be considered published. This can jeopardize your ability to publish the manuscript in most academic journals, as the manuscript would have already been published. It can also prevent you from being able to patent any inventions discussed in your manuscript because the information shared with the AI can be considered prior art of disclosure by the patent office.
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