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The Machine Didn’t Cheat: Students, Faculty, and the Human Problem

Sun, August 9, 10:00 to 11:00am, TBA

Abstract

In this project, we examine how artificial intelligence (AI) is transforming education, not as the primary issue itself, but as a reflection of deeper human challenges. How do faculty, students, and administrators perceive and respond to AI in education, and what do these perspectives reveal about deeper issues in teaching, learning, and integrity? We use qualitative data, including in-depth interviews with faculty and administrators and observations in classroom and workshop settings, to highlight these voices. While AI is often blamed for encouraging academic dishonesty, we argue that the real issue lies in how people use and respond to the tool. Our early findings suggest that AI highlights problems that were already present. Students often feel pressure to perform and may look for shortcuts. Professors face new challenges in defining what counts as original work, and schools struggle to apply older rules to new technologies. Ultimately, we suggest that AI itself is not the one “cheating.” Instead, it reflects the choices people make and the systems that shape those choices, showing that the true challenges in education are human ones rooted in responsibility, fairness, and the ability to adapt to change. The significance of our work lies in moving beyond headlines about AI threatening education and instead asking what the rise of these tools reveals about the culture of teaching and learning itself. By gathering voices from across different levels of education, this research will provide insight that can guide more thoughtful policies, classroom practices, and support systems. The findings will help educators and institutions move past a fear of AI toward a deeper understanding of the human choices that shape how technology is used in education.

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