AI in the Classroom: Why AI-Powered Personalized Learning Might Not Deliver on its Promise
This episode of Class Disrupted examines whether AI-powered personalized learning can truly deliver on its promise in K-12 education. Host Michael Horn and co-host Diane Tavenner speak with Benjamin Riley of Cognitive Resonance, who argues that current AI systems lack a theory of mind and other cognitive capacities essential for genuine personalized learning. The conversation explores the gap between AI hype and the realities of how humans think and learn.
This story was produced through MarketScale. See how Education Technology teams put it to work with Executive Thought Leadership.
Promoted content from The Future of Education with Michael Horn on MarketScale.
Key takeaways
AI systems currently lack a 'theory of mind,' a core human cognitive capacity, which limits their effectiveness as personalized learning tools.
Despite rapid technological advances, AI-powered personalized learning may fall short of its promise because it doesn't replicate human cognition.
Studying how AI differs from human thinking can still yield valuable insights into human cognition and learning science.
Get featured
Want MarketScale to feature Education Technology?
Book a 15-minute demo and we'll map your Education Technology expertise to the content buyers are searching for.
AI is everywhere—and it’s evolving rapidly. From predictive algorithms to large language models like ChatGPT, artificial intelligence is reshaping how we work, communicate, and learn. As schools explore AI in the classroom, educators and researchers are asking: Does AI really understand us? Or are we projecting human-like thinking onto systems that are fundamentally different? The stakes are high: while AI promises personalized learning at scale, it may be missing key ingredients of how humans truly think and learn.
So what does it mean to say that “AI doesn’t think like us”? And if that’s true, what are the implications for education?
In this episode of Class Disrupted, part of The Future of Education podcast, co-hosts Michael Horn and Diane Tavenner welcome Benjamin Riley, founder of Cognitive Resonance. Riley brings a thoughtful, research-grounded skepticism to the hype around AI. He’s deeply curious—but not convinced—that current tools can meet the cognitive and cultural demands of education.
The key topics of conversation…
- Why AI lacks a “theory of mind”—a crucial human capacity—and what that means for student learning.
- Why the dream of personalized AI in the classroom may fall short, despite technological advances..
- How studying AI can still teach us about human cognition, even if the machines don’t “think” like we do.
Benjamin Riley is the founder of Cognitive Resonance, a consultancy focused on applying cognitive science to improve decision-making, particularly in education and AI. He previously founded and led Deans for Impact, a national nonprofit transforming teacher preparation to improve student learning outcomes. With a background in law and public policy, Riley has held roles ranging from Deputy Attorney General in California to policy leader at NewSchools Venture Fund and a public policy fellow in New Zealand’s Ministry of Education.
Part of this channel
The Future of Education with Michael Horn
Michael Horn interviews the people redesigning how students learn
Your experts belong here
Every story in MarketScale Education Technology starts with a company putting its implementation leads, instructional designers, and district partners on the record. Buyers are already reading this topic. The only question is whose experts they find.
Procurement teams read long before they ever call, and your implementers get to answer their questions first.
About the author
Michael Horn speaks and writes about the future of education and works with a portfolio of education organizations to improve the life of each and every student. He is the co-founder of and a distinguished fellow at the Clayton Christensen Institute for Disruptive Innovation, and host of the Future of Education podcast on MarketScale.
