Below are comments we gathered from several academics and industry folks which you are welcome to use.
We asked our experts these questions: How would you describe the potential for artificial intelligence in higher education? Do you see opportunity, roadblocks, or danger ahead? Do you have a dream of what AI could mean (by way of functionality) to faculty?
Rich Ross, PhD, Assistant Professor, General Faculty at University of Virginia
While many are developing ways to have AI replace interactions, I think that AI should be viewed through the lens of maximizing each interaction: students interacting with each other, and instructors interacting with students. To me, the biggest danger with AI and related tools is that we’ll reduce the quality and frequency of these interactions without reducing the tedium of many tasks that we should automate. Ideally, AI would automate most or all of the “low-impact” activities and allow me to maximize time spent helping students understand and synthesize the concepts in my courses.
Eric Wang, PhD, Senior Director, Turnitin AI, at Turnitin
When used strategically, AI can be highly effective in cutting down repetitive, administrative tasks—such as gathering data or organizing workflows. Though, it is key that AI is used as an assistive tool and that ultimately a human reviewer is making the decisions—whether they be in admissions, assessment, or other areas of the university. AI is not infallible when asked to perform complex human judgments. AI is trained on datasets that are based on human behavior, and if biases exist in the data, AI models will build on these biases to make predictions. Therefore, AI can amplify underlying bias when it is used without care. Institutions can help mitigate these issues by working with companies and partners that are committed to fairness, accessibility, and inclusivity in product design, rather than as an afterthought.
Melvin Hines, CEO and Founder of Upswing
As colleges are struggling to do more with less, and particularly as community colleges find themselves competing increasingly with well-moneyed national institutions for students in their local neighborhoods, AI tools will move from being a nice luxury to a survival necessity. However, AI can't be used to replace the human touch. As within other industries, forcing students to interact with inadequate AI tools will only serve to increase student dropouts. My dream would for AI to be used to help students navigate the myriad of problems they must overcome in order to be a student. It would also allow admins to recognize where students face barriers and how they can decrease them.
Nathan Thompson, PhD, CEO and Co-Founder at Assessment Systems
The role of artificial intelligence in higher education is still not fully explored and realized, even though the pandemic certainly hastened the adoption of many technologies. The greatest opportunity is that it can help to bring quality education to more people, by improving relevant components such as placement, instruction, and assessment. For example, adaptive placement testing and adaptive learning could drastically reduce the time needed for a student to achieve some certain level of skills or educational degree. The greatest danger, or perhaps remaining opportunity, is how to best leverage the human element of higher education. Personally, the greatest value I received was not what I learned in textbooks, but the mentorship from key professors that guided me into my future profession that I now love, and changed the way that I think. How can AI make faculty more efficient so that they continue to make such an impact?
Jenny Amos, PhD, Teaching Professor, Laura Hahn Faculty Fellow, University of Illinois Urbana-Champaign
Artificial Intelligence (AI) can be used to help us determine student pathways to success that were not readily apparent. For instance, is a particular pre-requisite course really needed to proceed in the curriculum? What other potential pathways exist? This type of thinking could have huge advantages to rethink pre-requisites in terms of whole courses and, instead, see them as a list of skills and knowledge needed with more flexible pathways to achievement.
A potential danger of AI in education is an overreliance on algorithms to predict final course scores early in a course. These algorithms do not take into account the growth potential in the human mind to change behaviors and change the course moving forward. While input from algorithms like these can be used to notify faculty of student progress as early warning signs, they also represent confounding sources of information and are not deterministic on their own, just a starting off point for conversation.