According to a Northeastern University/Gallup poll, most Americans are optimistic about artificial intelligence’s (AI) impact on their futures while, at the same time, expecting the net effect of AI to be an overall reduction in jobs. If we manage AI effectively, I believe it can be a net benefit to both society and the economy.
The question is: How will higher education manage AI?
Unfortunately, higher education does not have a reputation for managing change effectively. Our experience is much more one of coming late to the party—and not of our own accord. We cannot and should not do this with AI.
First, much of the expertise to develop AI is coming from university laboratories, with AI hot spots in university centers such as Boston, San Francisco, Chicago, and the Research Triangle of North Carolina. If we can develop AI for businesses at home and abroad, why can’t we do the same for ourselves?
Second, many creative applications of AI have already been developed to solve problems within the university. Certainly, enrollment-management processes as well as today’s learning management systems look nothing like those of 20 years ago. These changes are clear applications of AI.
Is #AI a game-changer for #highered?
At the end of the day, however, the application of AI within the university is quite limited.
Where are the higher-ed AI opportunities?
To find opportunities for AI growth within the university, we need to distinguish between activities that are uniquely human as opposed to those that can be computerized. Individuals excel at defining problems, distinguishing between “good” and “bad,” at idiosyncratic tasks such as detecting false positives, and in developing novel combinations not anticipated by previous experience. Computers excel at tasks that involve well-understood rules and procedures.
Furthermore, human decision making is enhanced when it occurs in groups. Social facilitation, cooperation, division of labor, and the collecting of different perspectives, knowledge, and experience all combine to enhance decision making by groups.
Of course, neither individuals nor groups are without their problems. Individuals can be slow and inefficient in their decision making, to say nothing of the limits a single individual’s knowledge and experience. Likewise, groups can be guilty of premature closure, becoming too risky or too conservative because of preconceived expectations and group think. Much of the work of organizational psychology has focused on how to manage individual and group decision making so as to keep the good and minimize the bad.