Recently, I had the privilege of participating in a panel discussion on “Advancing Education in the AI Era: Promises, Pitfalls, and Policy Strategies” hosted by the Center for AI Policy in Washington, D.C. The event, held in the hallowed (not a word I use lightly) precincts of the US Capitol building, provided a unique opportunity to explore the complex landscape of AI in education. Before the panel, I reached out to my network for their thoughts and suggestions.
The response was amazing—a range of diverse perspectives that enriched my contribution and underscored the complexity of our task. Of course, I have my own take on these issues, and my comments at the panel were my own, but I would be remiss if I did not acknowledge how much these responses meant to me, as fodder for thought.
In this blog post I seek to summarize the comments, to make a record of them for the future. Let’s dive in.
One theme was the potential of AI to provide personalized learning experiences. These ragned from imagining curricula co-designed by AI, tailored to individual student needs, leading, hopefully, to greater engagement and learning. It’s was not just about content delivery, though. AI could revolutionize assessment too. One idea that stood out was that of creating less intrusive evaluation methods which could mean more time for actual learning and less time worrying about grades.
But it was not all rosy. AI in education comes with its fair share of thorny issues which my respondents were not hesitant to point out.
Environmental concerns loom large. Can our planet afford the fact that these AI systems are energy-hungry beasts. Then there’s the potential impact on the educational profession. Automation is coming for educational support roles. What happens to those professionals? And finally how can we forget about bias. The fact that AI systems may inadvertently reinforce existing inequalities in knowledge and language is something I have written about extensively on this website.
Ethics is another minefield that came up, often in the form of concerns around data use, privacy, consent and copyright. And what about the sanctity of the teacher-student relationship? Will AI disrupt it? Enhance it? Or fundamentally alter it?
Underlying all of these concerns was a recognition that the pace of change is dizzying. How do we craft educational policies that can keep up? We need flexible frameworks. Adaptable, yet clear. Protective, yet not stifling.
A tall order but not one that the respondents shied away from.
Balance was a key term used in this context, in that we need to embrace AI’s potential without rushing headlong into adoption. Slow and steady wins the race, despite the chaotic rate of change.
Given the people I hang out with, it was not surprising that quite a few comments focused on teachers and they needed to be at the forefront of any discussions around policy. It seemed to me that this was based on a respect for their contextually grounded knowledge and expertise. And instructional designers got a shout-out as well, emphasizing the manner they bridge technological capabilities and educational needs.
Then of course, given the multifaceted nature of the challenges, there were shoutouts to the importance of interdisciplinary collaboration, in research, practice and policy making. And to not losing sight of certain human-centered fundamentals skills: critical thinking, creative problem-solving, effective communication.
My heartfelt thanks to Abhishek Bagchi, Jacqueline Chauser, Christopher Davis, Thomas B Frøsig, Purnananda Guptasarma, Amelia King, Daniel G. Krutka, Lindsey McCaleb, Jonathon Richter, Mamta Shah, Dipendra Subedi, Daire Maria Ni Uanachain, Mary Wever, and Alex U., for sharing their thoughts. Though I may not have exactly captured all of what you suggested, your insights were invaluable in helping me think through these complex issues as I planned what I would talk about.
The event was recorded, and I hope to share the video soon. This conversation is too important to be confined to a single room, even if it’s in the US Capitol.
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