Category: Artificial Intelligence, Future of Higher Education;
Reading Time: ~4 minutes
Artificial Intelligence (AI) is here to stay, so why not utilize it to benefit academia?
In the first of a thought-provoking two-part article series on Minding the Campus, Joe Nalven explores the idea that AI can be used beneficially in the university. He believes that “AI can be a method to reconfigure university education—not in its totality, but as a way to integrate and reintegrate learning across disciplinary silos.” This is certainly an interesting idea, but why AI is necessary to undermine disciplinary silos and how it can do so must be fleshed out first.
Educational fields often become siloed, and have done so since the medieval university. This is a problem still facing the modern university, one that shields the “larger educational enterprise from cross, multi, trans, and inter-disciplinary practices—not to mention how education maps onto reality outside the university.” Many colleges and universities fail to de-silo academic fields on their own, and lose out on congruent research opportunities and more institutional depth. Nalven proposes a solution possible with AI,
All communication within each and every discipline—whether mathematical symbols, human language, research reports, publications, lectures, designs, plans, robotics, image generation, speech recognition, computer vision, and on and on—is reducible to code. Machine language, now structured as Large Language Models (LLM), can talk across these ostensibly separate fields of inquiry.
Nalven’s thought process led him to pose a question to Bard, an AI chatbot, asking it “Would AI LLMs undermine academic silos since LLMs code all information that can cross disciplinary boundaries?” Suffice to say, the chatbot’s response was thorough, and that “yes … AI LLMs have the potential to revolutionize the way we do research and scholarship.” This is because AI LLMs can process information faster while exploring new ideas and possibilities—without human restraint.
Now comes the how. Nalven suggests a hypothetical art exhibit as means to challenge an institution’s disciplinary silos, co-curated by a LLM and a human. He writes,
Wearing an artist’s hat, I propose a campus art gallery as a framework to discuss how AI can re-integrate several university disciplines—art practice, art history, semantics, cognitive science, computer programming, data training for LLMs, bias, law, economics, epistemology, and more. A campus art gallery can reintegrate education with an LLM model that is part curator of existing data and part generative tool that can create new data combinations. Other places in the university can illustrate additional examples of re-integrating disciplinary silos.
Nalven’s points are an intriguing thought experiment. If AI is in fact “here to stay,” shouldn’t colleges and universities find a way to utilize it for good? Already, students abuse AI to write papers, translate passages of text, cheat on tests, and more. So rather than continue to feed into the “don’t use it because I said so” modus operandi—where administrators and professors believe if they ignore AI’s existence and merely tell students not to use it, problems created by AI will simply vanish—wouldn’t it be better to employ AI capabilities to enhance research and improve educational experience?
It is not an understatement to say that AI is a controversial topic, and one that’s been highly debated. Some people feel strongly one way or the other about AI, and the rest are in between. Perhaps the answer is to employ AI in the way Nalven suggests. Perhaps there’s another way to employ AI, or not at all. Either way, this merits further discussions on the direction of higher education with and without AI, as we grapple with the myriad of problems created by humans. All food for thought.
Until next week.
Kali Jerrard
Communications Associate
National Association of Scholars
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