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Post: Three Predictions For How AI Will Reshape Academia

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Three Predictions For How AI Will Reshape Academia
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Jozef Gherman is the CEO & Founder of Undetectable AI: StealthGPT . getty The current state of artificial intelligence in academia is in constant flux. Each university will inevitably be somewhat defined by its AI policy, but certain trends are bound to sweep academia at large.

With a background in generative AI, I can see the wave of superior chatbots and new technologies coming toward higher education, the universities attempting to protect student learning and the next generation surfing that wave with impeccable competency.

I want to speculate on the near future that builds upon a present where AI tools with large language models like ChatGPT can write essays, AI detectors like Turnitin can spot the watermarks of AI writing and AI tools with natural language processing aim to bypass those detectors by making text more human-like.

As much as the use of AI threatens student development by depriving them of learning outcomes like attaining critical thinking faculties and a sense of real-world consequences, tech developers still want the next generation of students to be fully functional human beings. The three parties—tech, faculty and students—must work together to make a future that benefits everyone using AI technology.

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Here are three predictions for how AI will reshape academia for each of these groups. More In-Class And Less Take-Home Assignments

If generative AI poses a problem for professors demanding their students’ learning experiences come without any caveats, students should expect in-class assignments to take the place of take-home assignments. These in-class assignments might take the form of long-answer worksheets or full essays asked to be started and finished in class.While this approach prevents students from using AI to write their essays and ensures they are not engaging in AI plagiarism, it is also important to consider that this forces students to write and think in an environment that might not be conducive to their […]

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