Since I entered the college atmosphere, the number of AI chatbots I have seen split-screened or hidden in the corners of students’ desktops has become impossible to ignore. Notably, research has found that over half of U.S. college students use artificial intelligence in their coursework weekly. Artificial intelligence has slowly embedded itself into the “college experience,” as many universities partner with companies such as Claude and ChatGPT to offer students their services for free, despite having anti-AI policies within coursework requirements. Interestingly, while AI has been shown not to improve long-term learning by bypassing critical thinking processes, colleges are seeing the percentage of students receiving A grades increase drastically in courses considered “AI-exposed.” AI-exposed courses are courses where take-home or individual assignments susceptible to AI assistance carry more weight than monitored coursework like proctored tests or in-person exams. The harm this realization carries is that college students are being rewarded with better grades and even incentivized by their campus to utilize these AI tools, while diminishing their own learning capabilities. However, an even bigger problem exists within this conversation that I, as someone who makes an effort not to use AI, can’t help but ask: what happens to the students who aren’t using AI to help with coursework? When campuses begin rewarding and neglecting the advantages AI-empowered students hold over their AI-reserved peers, what emerging consequences and gaps do these institutions foster as they prepare students for the workforce?Â
It’s obvious to see the temptation behind using these AI systems for homework or to develop quick, comprehensive study guides. Nearly nine in ten monthly users of AI say understanding complex material is a key motivator behind AI use, with saving time on assignments and improving grades following closely behind. With these incentives in mind, who could possibly be the students not using AI? Well, survey results show male students report more frequent AI use than female students, with additional numbers revealing women are more likely to question AI’s accuracy or have ethical reservations about AI. This makes sense when looking at separate studies that show men are more likely to be praised and even receive manager support for using AI in the workplace than women are. Ethical reasons, such as AI water use or privacy and security concerns, are highly influential factors when considering personal AI usage regardless of gender, but when gender begins to play a factor in AI’s role in the job market, you begin to see a pattern in who these LLM’s seek to benefit. Still, these instances only reflect individuals who actively choose to avoid AI technology (even though in some cases it is hardly a choice).
Apart from these revelations, research focused on college students who frequently utilize AI in classes uncovered prevalent socioeconomic and racial disparities throughout its findings. And with what we’ve learned about AI so far, is this really surprising? Consider the background of a student coming into college from an underfunded school that may not be able to invest in the best AI technologies or be able to teach useful knowledge on how to best utilize AI resources. Here, AI creates an unfair advantage, as revealed through the digital divide, that wealthy students possess over primarily students of color and lower-income families that threatens to greatly widen the academic achievement gap. Unequal access to AI tools has the potential to negatively impact academic performance and hurt future career opportunities, ultimately influencing who gets represented in a workforce where AI competency is essential to succeed. Overall, as AI’s progress and normalization in current society show no sign of stopping, and as we are all only one monthly fee away from having our notes and schoolwork completely automated by these LLM’s, it’s worth asking who gets to use AI safely, who gets access to the best of these models, and what that means for the future value of college education.