AI in the Universities: A Matter of Degrees
“We are currently preparing students for jobs that don’t yet exist, using technologies that haven’t been invented, in order to solve problems we don’t even know are problems yet.”
~ Richard Riley, US Secretary of Education 1993-2002
From Ivy League schools to small, regional or state campuses, universities have long been familiar with students utilizing outside help with their coursework. Students used it for what may politely be called “short cuts”, or less politely, plagiarism, to write term papers and complete other assignments. Many probably used them in high school as well.
Before AI, a story made the rounds about a term paper that was submitted by a wealthy student. Unfortunately for the student, the paper still had the actual author’s bill to purchase the paper folded into the back page.
Students were also known to avail themselves of files in their fraternity or sorority house that held previously completed term papers and old tests. For those without such access, term-paper writing services were happy to take students’ money for ready-to-go papers they could submit as their own.
Currently AI merely facilitates, broadens, and simplifies a system that has operated for some time. As in other areas of university life, using a short-cut to help write or even fully complete written assignments has its drawbacks for those who choose to go that route. For one thing, if you’re in school to learn, using AI certainly circumvents that goal!
Also, AI-authored papers often give the game away. Since students rarely write as well as Alice Walker or Philip Roth, and teachers can utilize a combination of behavioral clues, stylistic analysis, and specialized detection tools to identify AI-written work. These “tells” are true across many university disciplines.
Given how quickly AI is developing, it is not beyond the realm of possibility that it will eventually learn to write like a freshman and to otherwise adjust to similar criteria while defeating detection tools.
Bottom line effects
But AI’s impact on higher education isn’t confined to term papers.
Educating students and advancing knowledge are noble goals, but fundamentally universities are businesses that, “purchase equipment, consume supplies, and employ labor to create products and services, which they sell at a price.” They meet their financial needs with a combination of tuition, fundraising, government support, public sector collaborations and endowment income.
Of course, universities having financial difficulties is hardly new since a reduction in any of these resource streams, such as when the federal government cuts off research funding, will make budgeting woes even worse.
When faced with decreasing revenue, universities respond like any other business. They will look for ways to cut expenses. They do so through hiring freezes, reducing staff, deferring maintenance, and cancelling programs. Even while in peak financial health, universities hire low-paid, temporary instructors and eliminate less popular majors. That trend has increased. In addition, then as now, they raise fees and tuition. These increased charges have resulted in massive borrowing by students. Thanks to a largely uncooperative federal government, these loans are proving increasingly difficult to repay.
AI’s impact on employees
Many clerical, administrative, and data entry roles are being impacted by AI, putting employees at the greatest risk of being replaced. Since salaries comprise a major part of university budgets, using AI to handle tasks formerly done by humans can offer significant savings. At budget-stretched universities, even the tenure track faculty find their job security at risk and raises becoming increasingly rare.
For the next several years, the university departments most likely to see their professors replaced by AI are the ones already under severe pressure: the humanities and the social sciences. Over the past decade, as the declining number of both undergraduate and graduate students majoring in these fields demonstrates, U.S. students have voted with their feet and left these disciplines.
In terms of technology, AI accelerates and broadens already existing technology. As nearly all U.S. college and university students have both a cell phone and a computer, during the COVID pandemic, faculty taught many, if not most, of their classes online. Many still do.
And AI will be able to take that further by personalizing student learning experiences while encouraging innovation and increasing efficiency. If these trends continue, student bodies and campuses will become smaller, and the students who are there will mostly major in disciplines that require hands-on learning.
On the horizon
Bill Gates believes that AI will begin to replace teachers within the next decade. Disappointingly— at least for the current university fiscal hawks—eliminating all faculty is not that simple. Some disciplines, including healthcare practice and the arts, are unable to be taught effectively without at least some human involvement. While AI-enabled robots excel in patience, high-repetition tasks, and fostering low-anxiety environments, they lack the emotional intelligence, adaptability, and human connection essential for deep, pedagogical, and social-emotional teaching.
To many observers, AI development, adoption, and capabilities have outpaced safety, regulation, and organizational structure. But if we jump beyond the current chaos, the future impact of AI on the very essence of universities will likely be profound. Starting with the physical campuses.
Additional impacts
The labor markets predicted to be most impacted by AI include management, business/finance, computer/math, architecture/engineering, life/social sciences, legal and arts/media. Add to the list downsized university faculties replaced by AI and their associated support staff.
When humans are no longer required for these jobs, neither is the real estate. Personalized teaching will increase remote learning thereby reducing the need for lecture rooms, residential halls, dining facilities, and social student centers. Empty libraries, administrative buildings, and faculty offices are significant financial burdens.
And then there is sports. University co-curricular activities foster social development through clubs, networking, internship opportunities, physical activities, and cultural exchanges. While an important component of student social life, intercollegiate sports expenditures have doubled in the past 20 years. Despite the influx of outside money from TV contracts and other sources, many universities devote nearly 20% of their revenues toward these programs. Will universities be able to justify the expense of these programs, stadiums, and other athletic facilities when there are significantly fewer students on campus?
Degrees of change
At some future point, AI will be able to perform many of the tasks for a variety of professions, particularly knowledge-based, “white collar” occupations—although the displacement may not be as widespread as some have thought. And human workers will still be needed for some hands-on tasks such as gardening, dishwashing, baristas, home health workers, etc. But the impact of AI on nearly every aspect of higher-learning will unquestionably be widespread.
Universities need to plan strategically for the financial impacts of decreased demand for specific majors, significantly lower on-campus attendance, empty buildings, and a vastly different, possibly degraded, college life experience.
Sprawling university campuses may become a memory as the land and buildings become data centers or other corporate facilities, while independent research transforms into commercialization. Intercollegiate sports programs may shift into hyper-personalized experiences with optimized performance but fewer or radically transformed teams, games, and schedules.
Outlook
At the end of the 19th century in London, it was feared that horse manure from the animals pulling coaches and wagons would eventually bury the metropolis. Then along came the automobile. London and other cities were of course not buried, although the slow adoption of automobiles over horse-drawn carriages did bring about many other problems along with its many benefits.
And while US culture generally wants things to happen rapidly, university implementation of AI will, in all probability, also be slow, uneven, and full of unforeseen implications. But much of AI’s impact on a university’s fundamental structure, finances, and essential essence is easily predictable. Those institutions of higher education that anticipate and proactively prepare for these changes will be better positioned to remain the vital and consequential centers of learning and research that they are today.
For more stories, insights and guidance on navigating the evolving landscape of AI and other related issues, stay tuned to our blog for future updates and expert analyses.
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