How is AI Changing What it Means to Learn? Pt. 1
A student perspective
Back in December, we asked students: How is AI changing what it means to learn?
Part of our mission at AI Consensus is to elevate the voice of students in education, which we believe is crucial for the conversation around AI and education. We are experiencing the impact — positive and negative — of these tools in real time, and can bring in unique perspectives on their role in the learning process. Students are young, idealistic, and bold, bringing forth striking and original ideas.
Seventy students wrote back, and we selected ten of these voices that capture experiences ranging from Alzheimer’s research to poetry, late-night grinds and foreign uber-rides.
In the coming weeks, we will feature these compelling perspectives in two parts, and hope they’ll inspire new thought and ideas about the way AI is changing what it means to learn.
AI for Learning: Wielding a Double-Edged Sword by Malavika Anand Srivathsa
As a graduate student pursuing a degree in Human Development and Education, I have devoted considerable time to contemplating the implications of artificial intelligence on the global education system and its learners. Generative AI has empowered young individuals to transform their imaginations into reality, providing them with tools to be creative. No idea is too fantastical or unattainable; anything conceived by the mind can be realized and shared. Illustrations can be crafted, stories written, and music composed. This boundless potential can enhance children's creativity, encourage them to take ownership of their learning and expression, and bolster their sense of self-efficacy. Furthermore, humans now possess unprecedented access to vast information resources at their fingertips. In a world where knowledge equates to power, AI holds the potential to serve as an equalizer by ensuring equitable access across diverse communities.
While I am captivated by AI's possibilities, I am also skeptical of the opportunities it can deny us, if not utilized responsibly. Reflecting on my experiences as a high school senior and undergraduate student, I recall meticulously pouring over books and journal articles in search of insights on whatever topic I was interested in or researching. Today, with a well-crafted prompt and a mere click, I am presented with a distilled version of information on virtually any subject. It is concise and quickly satiates my intellectual curiosity. There is little noise but there is also little depth. I find myself no longer pausing to ponder or fervently search for further information on topics of interest. I also miss out on complementary facts that could enrich my understanding of the subject or that would lead me to pursue another search. In this manner, AI may inadvertently limit what it means for us to learn, be patient and nurture curiosity as human beings.
Everything appears to be within reach, yet nothing is fully grasped. I believe it is imperative for learning designers and educators to acknowledge and address this challenge when creating educational experiences. Students should be encouraged to engage in deep, independent thinking and to utilize AI as a means to expand and enrich their learning journey.
dAwning tIme by Mara Dumitru
AI challenges what it means to learn because it learns from us. Say I do not have an original drive to learn and create in a certain field, and therefore decide to produce a project based solely on the ideas of others. Artificial Intelligence can surely surpass this unoriginal creation of mine because of its greater knowledge. So why learn? Just like the meaning of this poem, it is up to you. One may choose to be reminiscent in the thought that they will never be able to create something better than AI, stinging their passion for learning. Such as a student studying for an exam late at night, contemplating the purpose of their education. However, I believe that AI can create what humankind has no original drive to do, leaving time and room for me and you to find and pursue what we truly desire to. AI creates by copying ideas from human’s past works, however, it cannot mimic our originality, at least not quite yet. Which means it can take over these projects that one may not have the drive to do and instead we can focus on contributing to this world with our individual driving passion. A literal simplistic meaning to this poem might seem pessimistic, but a broader view beyond reading the words shows originality in the way they are shaped, meant, and capitalized. I am different from AI.
Thinking in Autocomplete by Pedro Henrique Goncalves de Paiva
The keyboard backlight flashes on, brightening up the keys. When I launch my browser, a single typed letter of a ‘c’ brings on the autocomplete with a suggestion: ChatGPT.com. The action has become second nature, showing how artificial intelligence has been entering into the habits of our lives. But this tiny behavior indicates a greater and more subtle change: AI is changing the very ground of what and how we learn and, in the process, giving birth to a different notion of what being a student means.
Not too long ago, if I needed something explained—a complex equation of chemicals, say, or the stratification of a Shakespearean soliloquy—I'd open a book, scroll down on online message forums, or ask a teacher after class. Today, I can write a sentence in a chat field, and a computer immediately gives the solution. This change feels liberating at times, but it also makes me wonder if we’re losing some essential part of learning: the long, winding process of figuring something out, with its eventual, surprising clarity. Whenever I open ChatGPT, I ask myself if I’m cutting corners or simply using resources better. The reality may be a combination of both—AI can be a teacher who speeds up the process and a curse if I don't watch my step.
This duality speaks of the possibility and the risk of AI. Teachers are freer than ever from memorized reciting and can apply their efforts toward engaging with their students. I've felt this in my classroom. Students come more prepared for class because of how concepts are explained —"tell me this like I am 10 years old"— and professors don't need to explain the same thing to different people, and more of their time can be allocated to more substantial discussions. They've also been more of a mentor, assisting me in understanding rather than teaching me facts. That human element—the ability to sense a student’s confusion or anxiety—is something no algorithm can replicate.
On the other hand, there's the reality of data reliance—my data, your data, our collective input. Everything I write and every edit I do contributes to a network of pattern-creation, recommendation-spewing machinery. The good part is personalization: they can shape lessons for me, for my abilities and deficits, leaving me with the belief the coursework has been modeled on me. The shadow, however, of data collection. Where do my difficulties and intellectual questions end up after being logged? Who, exactly, has access to this data, and what could be done with it down the road?
This tension between empowerment and privacy is what I find most impressive about learning with AI. It makes me more reflective on what I am doing with the technology. Should I rely on AI to check every assignment, or do I set boundaries to ensure I still learn the “old-fashioned” way? Should I embrace the convenience of chatbots for fast answers or remain cautious about the digital trail I leave behind? There are no easy answers, but even facing them represents a giant step towards being a more reflective learner. I'm starting to see that the big takeaways might not be the facts or formulas I can easily find. But instead, it's understanding how these computer programs change how I think.
My relationship with the zombie cells of the brain by Victor Onuh
As I began working on my Capstone project on Alzheimer’s Disease in my third year of college, I was confronted with several unfamiliar terms like "prion-like behavior of tau," "proteopathic seeding," and the "glymphatic system." These terms, which I had either never encountered or only vaguely understood, and many other complex neurological words were crucial to the literature review I was writing on senolytic interventions as a potential treatment for Alzheimer’s disease. This project required me to read over a hundred scientific papers and synthesize their insights into a cohesive narrative to produce a high-quality literature review.
However, the process was daunting, as scientific papers that should have taken thirty minutes to read stretched into hours, as I toggled between Google searches and additional research articles, often leading me in circles rather than closer to clarity. But when I discovered AI tools like Typeset, ChatGPT, and later Liner AI, I uncovered a paradigm shift that reshaped how I engaged with complex ideas.
My first experience using Typeset AI transformed my approach to reading dense scientific papers. Instead of passively highlighting terms like “microglial phagocytosis dysfunction,” I began interrogating the tool: “Explain this sentence as if I’m a first-year neuroscience student.” Typeset didn’t just simplify complex language — it taught me to think analogically. For instance, it likened proteopathic seeding to “a corrupted ile spreading in a computer network,” crystallizing an abstract concept into a tangible framework. This wasn’t mere translation; it was cognitive scaffolding, allowing me to climb from confusion to mastery.
Yet the true turning point came when I integrated ChatGPT into my workflow. While Typeset clarified complex language, ChatGPT became my research assistant, helping me connect ideas across disciplines. Once, I was stuck on conflicting findings about senolytics (drugs that target senescent cells), I prompted: “Analyze how senolytic treatment mechanism for Alzheimer’s disease compared to other neurodegenerative diseases.“ It provided a breakdown of inflammatory pathways across conditions and pointed me to a 2022 study on Parkinson’s disease that I had overlooked. This wasn’t about outsourcing thinking; it was about accelerating connections between disciplines, a crucial skill in advancing medical research. What once felt like an insurmountable challenge turned into an exhilarating learning experience, culminating in a literature review that I recently submitted to the Journal of Alzheimer’s Disease Reports for potential publication.
Through my experience, I have realized that AI is not just changing what it means to learn—it’s redefining what we consider worthy of learning. In the era prior to the development of AI tools like Typeset and ChatGPT, my education prioritized memorizing pathways like the MAPK cascade; now, tools like ChatGPT allow me to offload rote recall and invest energy in higher-order tasks. For example, during a debate about whether Alzheimer’s drugs should target cellular senescence or amyloid plaques, I used AI to simulate a dialectic: “Argue against the amyloid hypothesis using evidence from failed clinical trials, then rebut your own position.” This forced me to confront nuances no single paper had clarified.
Nevertheless, AI’s role in education is a double-edged sword. When wielded thoughtfully, it amplifies human intellect, fostering creativity and accelerating comprehension. However, over-reliance on AI poses the risk of a decline in critical thinking skills, as passive consumption replaces active engagement. The challenge, then, is not merely how AI transforms learning but how we, as learners, choose to engage with it. An Oscar-winning director, John Knoll, once remarked, “Any tool can be used for good or bad. It’s really the ethics of the artist using it.” The same principle applies to AI in education.
For students like me who aspire to contribute meaningfully to fields like neuroscience, AI is not just a convenience but a catalyst for intellectual growth. By democratizing access to information and augmenting our cognitive capacities, AI empowers learners to go beyond traditional barriers to knowledge. In this evolving educational landscape, learning is no longer confined to rote memorization but is instead characterized by deeper exploration, interdisciplinary connections, and, ultimately, the pursuit of innovation. AI is not replacing the learning process—it is redefining it, making it more dynamic, personalized, and boundless than ever before.
Stay tuned for the remaining four works that will be published next week! Following the essay contest submissions, we will continue to feature more student voices, providing opportunities to consider and interact with different perspectives from those who are most closely experiencing the evolving.
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