“AI detection” tools may only create more headaches for both teachers and students.
. But a new study indicates that such solutions may only create more headaches for both teachers and students. These AI detection tools are severely biased, the authors found, and inaccurate when it comes to non-native English speakers.
A Stanford University team led by senior author James Zou, an assistant professor of Biomedical Data Science, as well as Computer Science and Electrical Engineering, recently amassed 91 non-native English speakers’ essays written for the popular Test of English as a Second Language assessment. They then fed the essays into seven GPT detector programs.
. “If you use complex and fancier words, then it’s more likely to be classified as ‘human written’ by the algorithms.”Zou’s team then went a step further to test the detection programs’ parameters by feeding those same 91 essays into ChatGPT before asking the LLM to punch-up the writing. Those more “sophisticated” edits were then thrown back through the seven detection programs—only to have many of them reclassified as written by humans.
So, while AI-generated written content often isn’t great, neither apparently are the currently available tools to identify it. “The detectors are just too unreliable at this time, and the stakes are too high for the students, to put our faith in these technologies without rigorous evaluation and significant refinements,” Zou
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