Why AI Doesn’t Think Like Us

Techno-optimists have high hopes for how AI will improve learning. But what’s the merit of the “bull case”, and what are the technology’s risks? To think through those questions, Diane Tavenner and I sit down with Ben Riley of Cognitive Resonance, a “think and do” tank dedicated to improving decisions using cognitive science. Ben evaluates the cases made for AI, unpacks its potential hazards, and discusses how schools can prepare for it.

Diane Tavenner:

Hi there, I'm Diane, and what you're about to hear is a conversation Michael and I recorded with our guests, Ben Riley. It's part of our series exploring the potential impact of AI in education, where we're interviewing optimists and skeptics.

Here are two things from the episode that I keep thinking about:

First, our conversations are starting to make me wonder if AI is going to disrupt the model of education we've had for so long, as I think Ben perhaps fears, or if it's actually going to strengthen and reinforce our existing models of the schoolhouse with classrooms filled with a teacher and students.

The second thing that I was really thinking about and that struck me was that Ben's sort of one case for what could be beneficial about AI is something that's directly related to his work and interest in understanding the brain. And kind of how learning occurs. To be fair, there's a theme emerging across all the conversations we're having with people where they see value in the thing that they value themselves. And perhaps that's an artifact of the early stages and who knows, but it's making me curious.

And speaking of curious, a reflection I'm having after talking with Ben is about the process of change. Ben is a really well reasoned, thoughtful skeptic of AI's utility in education. He comes to his views at least partially from using AI. I would consider myself much more of an optimist and yet I'm finding myself a little bit annoyed right now, that every time I want to write an email or join a meeting or send a text or make a phone call that I've got AI pretty intrusively jumping in to try to help me. And it's really got me thinking about the very human process of change, which is one of the many reasons why I'm really looking forward to sense making conversations with Michael after all of these thought provoking interviews.

In the interim, we'd both love to hear your thoughts and reflections. So please do share. But for now, I hope you enjoy this conversation on Class Disrupted.

Michael Horn:

Hey, Diane. It is good to see you again.

Diane Tavenner:

You too. And I'm really excited to be back. Coming off of our last conversation around AI and education, it's making me even more excited about what we're going to be learning in this series. And I think today will be no exception in really stretching our minds and our thinkings about the possibilities, the limitations, the potential harms of AI and its intersection with education.

Michael Horn:

Yeah, I think that's right, Diane. And to help us think through these questions, today, we're bringing someone on the show that I think both of us have known for quite a long time. His name is Ben Riley. He previously founded the Deans for Impact in I believe 2014. And Deans for Impact is a nonprofit that connects cognitive science to teacher training. And then Ben stepped aside a couple years ago, and has most recently founded Cognitive Resonance, which is a think and do tank, in its words, and a consultancy organization that's really, its focus actually is on this topic of AI and learning, which is perfect and makes Ben the perfect guest for us today. So, Ben, welcome.

Ben Riley:

Thanks so much for having me. We'll see if you still think I'm the perfect guest by the end of it, but I appreciate being invited to speak to both of you.

Ben Riley’s Journey to the Work

Michael Horn:

Absolutely. Well, before we get into a series of questions that we've been asking our guests, we'd love you to share with the audience about how you got into AI so deep, specifically because I will confess and I'll give folks background, I've been reading. I've actually been an editor on a couple of the things that you've submitted into Education Next on AI, and I found them super intriguing. And then somehow I had no idea that you created this entire life for yourself around AI and education. And you have some language on this that I think is really interesting on the site where you say the purpose is to influence how people think about Gen AI systems by actually using the lens of cognitive science. And you believe that will help make AI more intelligible, less mysterious, which will actually help influence what people do with it in the years to come. And then you write that you see it as a useful tool, but one with strengths and limitations that are predictable. And so we really have to understand those if we want to harness them in essence. So how and why did you make this your focus?

Ben Riley:

Yeah. Well. And thank you for clearly having read the website's cognitiveresonance.net or the substack Build Cognitive Resonance, in many ways, the organization reflects my own personal journey because several years ago I started to become aware that something was happening in the world of AI, and at the time it was called deep learning, and that was the phrase that was starting to emerge. And to be completely candid, my focus has always been, and in some ways still very much is on how human cognition works. And so AI, artificial intelligence, is considered kind of one of the disciplines within cognitive science, along with psychology and neuroscience and linguistics, philosophy. There's like it's an interdisciplinary field. And for me, quite honestly, AI was sort of like this thing happening somewhere over there that I had maybe a loose eye on. And I got in touch with someone named Gary Marcus at the time, and we'll come back to Gary in a second, and then just said, hey, Gary, can you explain deep learning to me and what it is and what's going on? And that, you know, sort of began that conversation. And then quite frankly, I just kind of squirreled away and didn't think much about it. And then, like it did for all of us, ChatGPT came into our lives. And I was stunned. I was completely stunned when I first sat down with it and started using it. And what really irked me was that I didn't understand it. You know, I was like, I don't get how this is doing, what it's doing. So I am now going to try to figure out how it's doing, what it's doing. And that is not easy. At least it wasn't easy for me. I don't think it's even now. I don't think it's easy for those who might have spent their entire lives, much less those of us who are coming in late in the game or just trying to make sense of this new technology in our lives. And what I was able to draw upon was both sort of the things that I do know and have learned over the last decade plus around human cognition and frankly draw on a lot of relationships I have with people who are in cognitive science broadly, and just start having a bunch of conversations, doing a bunch of reading, and really trying to, you know, build a mental model of what's taking place with these tools and with large language models specifically. And when I finished all that, I thought, well, geez, it seems like, you know, that took a lot of work. Maybe it would be helpful to sort of try to pass this along and bring others into the conversation. So that's really the thesis of Cognitive Resonance.