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.

The fact that there are dozens of paraphrasing tools out there that can help users rephrase entire papers within seconds has provided further ammunition to bad actors looking to plagiarize and churn out fraudulent manuscripts at a faster pace. While the challenges for publishers battling ills such as plagiarism and paper mills continue to become more complicated, I posit that human intervention (human intelligence tasks aka HITs in MTurk parlance) coupled with the prowess of AI detection tools could present a viable way forward.

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.