Why Education Matters More Than Ever in the Age of Artificial Intelligence
The rapid progress made by Large Language Models (LLMs) over the past two years has fueled speculation that artificial intelligence (AI) will soon make college education—particularly liberal arts education—irrelevant. According to this view, individuals would be better off skipping college and entering the workforce directly. However, this assumption is misguided. While learning through practical experience is undoubtedly valuable, it is effective only when individuals possess a solid understanding of which jobs and skills are likely to be in demand in the future. Given the uncertainty surrounding the future of work, advising young people to abandon higher education and enter the labor market prematurely would be misleading.
Geoffrey Hinton, a pioneer of modern AI, once compared advances in artificial intelligence to navigating through fog—you can see the path ahead, but not far beyond it. This metaphor captures the central challenge facing educators today: preparing students to function effectively in an uncertain and rapidly evolving technological landscape. The solution does not lie in training students for specific tasks that may soon become obsolete, but in helping them develop adaptability and intellectual flexibility.
From this perspective, education—especially higher education—becomes more important than ever. Since it is impossible to predict which skills will dominate the future job market, focusing on foundational abilities is essential. Liberal education emphasizes “how to think” rather than “what to do.” It cultivates reasoning, critical reading, clear writing, and the ability to evaluate evidence—skills that are far more enduring than narrowly defined technical competencies.
This emphasis on fundamentals does not imply ignoring technical skills. On the contrary, students must learn how to work effectively with AI technologies. However, the goal should be to develop informed and critical users of AI, not passive consumers of automated outputs. Teaching mathematics, science, critical thinking, engagement with foundational texts, and the evaluation of arguments remains essential. These skills enable individuals to stay ahead of technological change rather than be controlled by it.
Questions about what to teach and how to teach it will inevitably generate debate. While there may be broad agreement on the importance of core concepts, the specifics will evolve over time. Historical experience with earlier technologies offers valuable insight. The introduction of calculators and computers did not eliminate the need to teach arithmetic; instead, students continued to learn mathematical principles and how these tools function. Likewise, spelling and grammar remain important despite the widespread use of digital aids.
AI demands similar adjustments across disciplines. LLMs are now highly proficient at tasks such as summarizing texts, identifying central ideas, drafting content, and even programming—activities traditionally considered central to education. These tasks should not be removed from curricula; rather, their educational purpose must shift. Students must develop a deeper understanding of underlying concepts and logic.
The claim that AI will reduce the need for formal education rests on the assumption that users already know what questions to ask and how to interpret the answers. In reality, only exceptional individuals can fully benefit from AI without strong educational foundations—and they would likely succeed regardless. If AI is to benefit society as a whole, it will require greater investment in education, not less.
Dr. Vandana Kanaskar
Assistant Professor