"The surveillance strategy relies on detection, an arms race we have already lost. AI-detection tools are biased, easily circumvented and prone to false positives."
"Students generally don't cheat because they lack moral fiber; they cheat because they are navigating a system of incentives that prioritizes efficiency over learning."
"When we grade on high-stakes curves, offer little feedback and demand perfection on the first try, we are signaling that the product matters more than the process."
"I believe too often we build courses that punish the very thing learning requires: making mistakes."
Faculty development at Georgia State University reveals a growing concern over student cheating with AI. Workshops on preventing digital dishonesty are in high demand, reflecting faculty anxiety. Two main strategies have emerged: surveillance, which relies on flawed AI-detection tools, and supplication, which attempts to encourage responsible AI use. However, these approaches fail to address the root cause of cheating, which stems from a system that prioritizes efficiency over genuine learning and punishes mistakes rather than fostering a growth mindset.
Read at Inside Higher Ed | Higher Education News, Events and Jobs
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