Point of Contention: Should college students use generative AI to complete their academic tasks?

Main takeaway: Training people to navigate LLMs and identify generated bodies of work remains important; however, establishing an academic foundation must take priority.

I do not believe that students should use generative AI when completing assignments. When approaching AI, students must consider the consumer-producer relationship. LLMs are trained on human data, and as LLM users, our continued usage only trains them further. While LLM users may find great use in this tool’s ability to produce quick results, even at a systemic level, we must remain cognizant of the true winners: AI developers and companies.

The other half of this relationship- you, us, the consumers, can easily measure the detriments done unto us. Consider this quote from Jon Cheung describing the dangers of AI exacerbates biases:

“For A.I. image generators trained on biased datasets. They will fill the Internet with biased images, which will then be fed back into datasets for other A.I. image generators, that will then create even more biased images and so on and so forth, thus creating a vicious feedback loop which will both spread and intensify existing biases” (2023).
Scholars are expected to possess critical-thinking skills that transcend bias. Therefore, learning students should not expect A.I. image generators to teach us anything except about A.I. image generators.

The strongest weapon against ignorance has always been curiosity and knowledge. AI actively degrades our cognitive ability- our ability to think critically. The MIT study we discussed in class demonstrates this degradation clearly, describing essays as soulless and lacking originality (2025, p.72). Otherwise known as cognitive debt, which “defers mental effort in the short term but results in long-term costs, such as diminished critical inquiry, increased vulnerability to manipulation, decreased creativity” (2025, p. 151). In other words, AI feeds us biased visual information while concurrently degrading our skills to properly navigate its output.

These various practices in class have led me to be extremely cautious about how many “menial tasks” I delegate to LLMs. I hope to remain cognizant of how much I truly value my mind, and I hope that everyone reading this feels similarly. To me, these fears are inherently linked to illnesses like dementia or Alzheimer’s. The only exception is that we as consumers, are actively inflicting this illness upon ourselves, individually and as a society.

That being said, I do find it important for consumers to know their product, especially as it infiltrates its way into seemingly every crevice of society and life. As scholars and as informed users, we must understand its strengths to know its weaknesses, and vice versa. And as AI continues to grow, it will almost become inevitable to avoid it- for instance, Copilot and Google’s AI-generated overviews. I urge everyone to be diligent of their regular practices, especially ones that seem free…

Citations:

Cheung, Jon. “How AI Image Generators Make Bias Worse.” LIS, 21 Aug. 2023, https://www.lis.ac.uk/stories/how-ai-image-generators-make-bias-worse.

Kosmyna, N., Hauptmann, E., Yuan, Y. T., Situ, J., Liao, X.-H., Beresnitzky, A. V., Braunstein, I., & Maes, P. (2025). Your Brain on ChatGPT: Accumulation of Cognitive Debt when Using an AI Assistant for Essay Writing Task [Preprint under review]^[1][2]. MIT Media Lab^[1]. https://www.brainonllm.com/