The Radical Changes AI Is Bringing To Higher Education

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From the printing press to typewriters to personal computers to the internet, technology has been instrumental in reshaping higher education over the past 500 years. At the same time, much of that reshaping has been closer to the edges rather than a complete upheaval. Artificial intelligence has the potential to transform and redefine higher education at its core, and will likely do so in the next year. Using a modified quote from ChatGPT, AI is coming to higher education like a squirrel on espresso!

As with other industries, AI is set to redefine higher education, for better and worse. Here is a select set of areas that will be impacted:

1. Meet the AI Professor. AI in the form of a fully interactive, avatar professor, will equal and exceed the best versions of the best professors at any university; responsive, responsible, available day and night, informed with staggering amounts of knowledge, and demonstrate pedagogical approaches that match the personalized needs of any student. The fear that faculty jobs are at stake is a real one, and the roles of faculty members are sure to change. Rather than the sage on the stage, a professor’s role will be the guide on the side. Their job will be to provide community building among groups of students and offer additional personalized ways to introduce students to using AI in the workplace, such as using AI in health research. In this redefined role, professors will serve as subject matter experts and ensure that the AI professor’s responses are sound and don’t go off the rails. Finally, they will play a role, at least initially, in what the students will be assessed.
2. Valid and Reliable Assessment. The current approach to testing in higher education, including multiple choice tests, blue book essays, group projects, and in-class presentations, is at best, a proxy for learning. Moreover, the professorial subjectivity problem of assessing student competence is historically an ongoing challenge. Some professors give up, which has led to grade inflation, while others have used protected systems of tenure to resist changes to their teaching performance. Going forward, professors, industry experts, and curriculum experts will determine what is assessed (e.g., content and skills), and AI will be able to judge with vastly more objectivity the students’ ability to demonstrate competence, including durable skills sought in industry. For example, presently, professors can lecture on what is involved in effective negotiation skills, but AI can objectively assess a student’s ability to demonstrate effective negotiation skills with different types of AI negotiators.
3. Personalized Education. Students come with different sets of skills when they enter college, largely based on their K-12 experiences. If they are relatively well-prepared, they can overcome any deficiencies in educational approach (e.g., poor teaching, inadequate out-of-the-classroom support). However, many students do not complete their studies because student learning approaches and needs are not well-matched with the abilities of universities. AI will provide an approach to self-paced learning that brings students along based on their learning needs, which means that students will have to demonstrate competence in academic and professional areas before proceeding. Rigorous standards and expectations can then be applied more fairly, and employers will have more accurate approximations of student skill levels when they graduate.
4. Affordability is the Best Ability. A comprehensive AI approach to higher education holds the promise that online education has never been able to fulfill: real affordability. Although online education expanded access, the cost of education is still out of reach for many, and it opened the door for predatory practices by some higher education institutions that resulted in large debt without a degree for many students. Moreover, the online approach was largely similar to what was done in-person, that is, professors with varying degrees of pedagogical competence assessing students with poor proxies of learning (e.g., multiple choice tests). Moreover, any cost-savings were largely accomplished by decreased personalization. An AI-integrated approach could prompt increased expectations and outcomes for faculty (i.e., facilitate 10 courses per year rather than 4), more effective academic support services, such as AI tutors, resulting in less staff and fewer administrators. In addition, the traditional, and expensive, campus model of thousands of students with resources coming to a common site, could evolve into neighborhood campuses that further increases access and lowers costs. In sum, the addition of AI should lead to a subtraction of expenses, particularly for nonprofit enterprises.
5. Limited Multidisciplinary College Majors for Lifelong Careers. In response to the recent challenges in higher education, universities have started to eliminate majors to save on costs. At first glance, this could seem problematic; however, having more majors does not necessarily make for good educational opportunities. Many universities boast 50-60 majors as a positive attribute; however, the reasons for a major have never been clear when not linked to job prospects. Moreover, siloing disciplines with limited career options rather than integrating multiple disciplines for multiple lifelong careers is a significant shortcoming of many current majors. AI should result in a few multidisciplinary majors (e.g., business/entrepreneurship, investigative, medical and behavioral health, computer science, arts), that in turn afford students the opportunity to enter multiple lifelong careers.

In all, AI-integrated higher education has the potential to hold much promise. Of course, the potential has already been met with a backlash. Similar to the church’s reaction to the printing press, higher education institutions are spending a disproportionate amount of time attempting to limit the use of AI, assuming the current educational model should go unchallenged and unchanged. Rather than covering one’s ears, the key will be to limit the potentially ineffective aspects of AI by opening up the higher education enterprise (e.g., open-source the educational approach to ensure adequate critique). If done well, AI can revolutionize higher education for the better.