One of my favorite movies of all times is 2001: A Space Odyssey, in which an artificial intelligence, HAL, is the star. As we head into the second decade of the 21st century, AI is clearly beginning to play a role in areas like ed tech — but HAL isn’t quite yet in the picture (if you have an android phone, ask Google to “open the pod bay doors” for a little surprise).
Even before I moved back to Silicon Valley four years ago, I was intrigued with some of the claims being made about the use of artificial intelligence (AI) in higher education. As I learned more about companies that were using machine learning and AI, there seemed to be a great deal of promise, but it’s also clear that AI isn’t quite yet ready to run our lives.
My hardware engineer husband is skeptical about the current level of sophistication of AI. As a a decision-making mechanism, self-driving cars are often the first thing people think of when they hear about AI. Given current levels of development, AI seems to have more uses in higher education as compared to the automotive world. Using AI for a chatbot, for example, doesn’t have much impact if it makes a mistake in responding to a question. The cost is low for a bad answer — however, using AI to drive a car can be deadly if it makes a mistake, and so we always seem to be a few years away from self-driving cars taking over our streets.
There are several areas in which AI can play a role in higher education:
- AI for grading students’ written answers
- Bots that answer students’ questions
- Virtual personal assistants for personalized tutoring
- Adaptive content recommendations and testing
- Virtual reality and computer vision for immersive ‘hands-on’ learning
- Simulations and gamification with rich learning analytics
As a teacher, I’m excited about the possibilities for the use of AI in grading, simulations, and creating adaptive content. As an administrator, I understand the importance of AI in developing data analyses and predictive analytics. As with any technology, however, it is important to keep in mind the impact the technology may have on equity and diversity issues. Although answers that chatbots may give might not have much of an impact on a student, if AI is used in admissions or enrollment processes, it is important to ensure that there is no risk of built-in discrimination. As researchers at IBM note, “AI systems are only as good as the data we put into them. Bad data can contain implicit racial, gender, or ideological biases.”
Overall, I think that AI has great potential for improving a variety of processes in higher education, but we need to keep in mind the ultimate goals of those processes. Our institutional structures aren’t always designed to promote equity, and it will be important that the technology we use doesn’t incorporated those biases.
About the author:
Terri E. Givens is the former Provost at Menlo College in the San Francisco Bay Area; Professor of Government and European studies at The University of Texas at Austin; Vice Provost overseeing undergraduate curriculum and spearheading global initiatives as its chief international officer. She formed The Center for Higher Education Leadership (CHEL) to provide academic leaders with information and a supportive community for improving management and leadership skills in an environment of changing demographics, financial challenges, and advances in educational technology. CHEL was born of Terri’s experiences navigating these fields and learning along her journey through academe, from professor to vice-provost and provost at universities in Texas and California.