Admittedly, while working on my physics homework this week, I got stuck on a problem and turned to generative artificial intelligence. 

Within five seconds of copying and pasting the questions, the solution was outlined in front of me, explained point by point. 

Still confused on one part of the solution, I asked for clarification, and again, almost instantaneously, a thorough breakdown of the math was right in front of me. 

I get the appeal of using generative AI — it’s incredibly convenient, and dare I say, can be a great teacher — but using it comes at a deep personal cost. 

While we have become accustomed to many of our peers making declarations of finally quitting nicotine, coffee or Instagram, I think it’s time that as students we decide to quit using generative AI — myself included. 

The personal cost of using generative AI isn’t entirely our fault — our education system simultaneously rewards us and punishes us for using it — but beyond the highly nuanced discussion surrounding AI, there is the grim reality that AI might not be all that was promised to us. 

AI use by students neatly falls into the box of neoliberal educational values, which assert that the goal of education is to prepare students to get jobs and contribute to the market. 

When education is viewed as a market-driven commodity, it becomes an individual investment rather than a public good. 

This framework pushes aside arts and humanities for higher demand disciplines like STEM and business, which have high returns in the market, and pairs well with generative AI, which caters to the capitalistic values of increasing productivity and results. 

With an emphasis on employability, the outcome overrides the process, and students are incentivized to get the highest grades they can, with generative AI often becoming a crutch to achieve this. 

While many professors discourage and prohibit AI use, the education system in which they work strongly rewards it, putting students in a position to ignore restrictions on AI use. 

According to the 2025 AI in Education Trends Report conducted by Copyleaks, which drew from more than 1,100 U.S. college students in two-year, four-year and graduate programs, 90% of have used AI academically, with the top motivations for AI use being to save time and improve quality.  

Students are faced with a clear tradeoff: use generative AI, get work done faster and get a higher grade, or do the work entirely yourself, invest more time, risk a lower grade and prioritize learning. 

When a college education is viewed as a personal investment, rather than a public good, and our education prioritizes output, students are motivated to get the best return on their investment, making generative AI the clear winner to this tradeoff.

Alternatively, in a system that prioritizes learning, the intuitive choice switches: the process becomes more important than the result, and the knowledge we gain is the capital we earn rather than the grade itself. 

If our education was about learning rather than grades, generative AI would lose its appeal to students and value would be seen in the effort we put into our education. 

AI distracts us from the reason we actually get an education, not just a degree. 

Ironically enough, while AI caters to capitalistic values of increasing efficiency, it simultaneously disincentivizes the user from developing skills like creativity and critical-thinking that will actually make them marketable.

The National Association of Colleges & Employers identifies problem-solving skills as the number one attribute employers seek on a candidate’s resume, a skill AI dependence fails to teach. 

Rather than taking the time to consider issues, work through problems or brainstorm ideas ourselves, we are spoonfed (potentially incorrect) AI answers that allow us to bypass the struggle and practice necessary for cultivating our intellect. 

This is where generative AI fails us. 

While using generative AI may make us look better on paper, it prevents us from learning the skills that can only be gained through the process, and misleads employers of our actual abilities.

In the age of AI, students must make the radical choice to prioritize learning, even when it isn’t immediately rewarded, and find value in education and knowledge itself.