Maintaining trust in the learning process
Academic integrity has always been the foundation of higher education. Yet the rise of generative AI has created a new level of uncertainty in classrooms and assessment spaces. Students can now produce essays, code, or research summaries within seconds. The challenge is not that students are using AI, it is that the traditional markers of originality and authorship are harder to verify than ever.
Detection tools were expected to solve this problem, but research shows they often create more harm than good. Some systems flag human writing as AI generated. Others allow AI written content to pass without notice. International reports highlight dramatic increases in academic misconduct cases, particularly where institutions rely heavily on flawed detection technology. The result is a landscape where genuine student work can be questioned while AI generated work slips through unchallenged.
AI has also forced us to reconsider the very definition of plagiarism. Is it misconduct to ask AI for an outline? What about using it to rewrite a paragraph? Students are already using these tools, and they often see them as no different from spell checkers or grammar assistants. Educators must determine how to draw clear lines between acceptable support and the outsourcing of intellectual labor.
If we want academic integrity to survive this moment, we cannot rely on detection. We must redesign assessment practices. Assignments that require process, reflection, revision, and personal context are far more resilient to AI misuse. In the end, AI should enhance learning, not replace it. Our job is to ensure students still develop their own voice, judgment, and scholarly identity.
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