The rise of artificial intelligence (AI) and machine learning has brought and will continue to bring many changes to higher education. They have the potential to positively impact administrative services, student services, and instruction (especially through adaptive learning) by giving students personalized support and more efficient access to relevant resources. However, AI and machine learning have the potential to eliminate certain jobs, causing a concern about the future of the workforce, and these technologies may compound preexisting inequities by perpetuating human biases in algorithms that ultimately go unchallenged. With this issue page, we hope to explore the ways institutions are currently using AI and machine learning and investigate how these changes are helping or hindering student success.

WCET Resources
Frontiers Blog
External Resources
Additional Resources
- A University Leader’s Glossary for AI and Machine Learning - Inside Higher Ed
- Artificial Intelligence in Higher Education - The Learning House
- How Algorithms Discriminate Based on Data They Lack: Challenges, Solutions, and Policy Implications
- Artificial Intelligence and Bias - IBM
- Algorithmic Justice League
- Fair is Not the Default - Google Design
- The Algorithms Aren't Biased, We Are - Medium | MIT Media Lab
- Algorithmic bias detection and mitigation: Best practices and policies to reduce consumer harms - Brookings
- Big Data And The Problem Of Bias In Higher Education - Forbes
- 5 Ways Artificial Intelligence May Influence Higher Education Admissions & Retention - Wiley Education Services
- The Future of Jobs and Jobs Training - Pew Research Center