Ethan Mollick, Associate Professor at the Wharton School, recently concluded in conversation with the CEOs of Turnitin and GPTZero that, “There is no tool that can reliably detect ChatGPT-4/ Bing/ Bard writing. None!” Even if some of the AI-detection tools do develop the capability to detect AI writing, users don’t need sophisticated tools to pass ChatGPT detectors with flying colors — making minor changes to AI-generated text usually does the trick.
This thoughtful Scholarly Kitchen piece takes a look at how ChatGPT has penetrated scholarly writing and publications, the consequences and useful detection. What is required is this kind of sober reflection on the stakes and risks, as well as useful strategies to respond to the situation.
In this article, we explore how HITs and not simply more AI tools (to detect the use of generative AI tools) could be the way forward as a reliable and scalable solution for maintaining research integrity within the scholarly record.
ChatGPT has deeply penetrated the scholarly ecosystem
While ChatGPT continues to witness unprecedented usage, stakeholders across industry verticals are not only excited, but also worried about how it could impact businesses, education, creative (including research) output, and much more. There is an increasing realization that ChatGPT in itself is not going to be a “solve-all” tool; hallucinations, inherent biases, and the inability to assess the quality and validity of research are just some of the limitations that limit the free use of LLMs.