Generative AI's appeal highlights a systemic issue in education. When grades—impacting financial aid and job prospects—are tied solely to finished products, students rationally use tools that shortcut the learning process to achieve the desired outcome under immense pressure from other life stressors.
Schools ban AI like ChatGPT fearing it's a tool for cheating, but this is profoundly shortsighted. The quality of an AI's output is entirely dependent on the critical thinking behind the user's input. This makes AI the first truly scalable tool for teaching children how to think critically, a skill far more valuable than memorization.
The proliferation of AI leaderboards incentivizes companies to optimize models for specific benchmarks. This creates a risk of "acing the SATs" where models excel on tests but don't necessarily make progress on solving real-world problems. This focus on gaming metrics could diverge from creating genuine user value.
AI excels where success is quantifiable (e.g., code generation). Its greatest challenge lies in subjective domains like mental health or education. Progress requires a messy, societal conversation to define 'success,' not just a developer-built technical leaderboard.
Data shows the vast majority (80%) of high school students use AI tools to explain concepts or brainstorm ideas. The rate of students admitting to cheating on entire assignments remains a consistent minority (~10%), suggesting AI is a new method for cheating, not a cause for a massive increase in it.
Using generative AI to produce work bypasses the reflection and effort required to build strong knowledge networks. This outsourcing of thinking leads to poor retention and a diminished ability to evaluate the quality of AI-generated output, mirroring historical data on how calculators impacted math skills.
ASU's president argues that if an AI can answer an assignment, the assignment has failed. The educator's role must evolve to use AI to 'up the game,' forcing students to ask more sophisticated questions, making the quality of the query—not the synthesized answer—the hallmark of learning.
While AI can accelerate tasks like writing, the real learning happens during the creative process itself. By outsourcing the 'doing' to AI, we risk losing the ability to think critically and synthesize information. Research shows our brains are physically remapping, reducing our ability to think on our feet.
In an age where AI can produce passable work, an educator's primary role shifts. Instead of focusing solely on the mechanics of a skill like writing, the more crucial and AI-proof job is to inspire students and convince them of the intrinsic value of learning that skill for themselves.
Instead of policing AI use, a novel strategy is for teachers to show students what AI produces on an assignment and grade it as a 'B-'. This sets a clear baseline, reframing AI as a starting point and challenging students to use human creativity and critical thinking to achieve a higher grade.
Instead of allowing AI to atrophy critical thinking by providing instant answers, leverage its "guided learning" capabilities. These features teach the process of solving a problem rather than just giving the solution, turning AI into a Socratic mentor that can accelerate learning and problem-solving abilities.