Can Teachers Rely on AI-Generated Feedback Amid AI Hallucinations?
- Brian Woods
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- Mar 4, 2024
- 2 min read
Updated: Nov 4, 2024
Despite the enthusiasm for AI, its unpredictability remains a significant concern, particularly in education, where accuracy and trust are essential. While many recognize that AI can grade assignments, provide feedback, and generate narrative report cards, few truly understand how it processes information—even its developers don’t fully grasp its inner workings. This lack of transparency becomes especially troubling when AI "hallucinates," generating false or fabricated information due to inadequate or poor-quality data. Without reviewing with a discerning eye, it is possible one might overlook the AI’s falsely generated responses as useful.
AI hallucinations raise serious questions about the reliability of AI-generated feedback. Since personalized feedback is crucial for student growth, such errors can lead to significant consequences. If an AI system frequently generates incorrect or misleading information, it becomes difficult for educators and students to trust its guidance. Even if a teacher is able to provide a scoring rubric or criterion to score essays against, the feedback provided could be rudimentary at best. As a result, teachers may need to thoroughly review or expand upon all AI-generated content, which negates any time-saving advantages that AI is supposed to offer. This flaw adds an extra burden on educators who are seeking streamlined solutions. Until AI programmers address issues like hallucinations and unpredictability, it may remain underutilized rather than becoming the autonomous assistant many envision.
To address these concerns and build trust, AI must be trained on high-quality datasets covering all subjects and grade levels, ensuring that the feedback is accurate and age-appropriate for easy comprehension. AI can only accurately score essays when it has been properly trained with large amounts of data to learn effectively. Hundreds of thousands of labeled essays are typically used to train robust models. Even a bare minimum of tens of thousands would be essential for training AI with simpler essay models and goals. Additionally, collaboration between software developers and educators is essential to validate the accuracy of AI-generated content. Neglecting these improvements undermines AI’s potential efficiency and impact. Until a more reliable solution for AI-based feedback is developed, it's difficult to imagine teachers fully trusting or adopting it.
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