Rewind: How AI is fueling an existential crisis in education

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Then use AI agents to automate tedious tasks and grow your business. Go to hostinger.com slash decoder to bring your idea online for under $3 a month. Use promo code decoder for an extra 20% off. Support for today's show comes from CNN. Do you want to live forever? Influential journalist Kara Swisher is taking a hard look at the longevity industry to separate the influencer hype from evidence-backed science. In her new CNN original series, Kara's talking to Silicon Valley power players and trying out the latest in anti-aging technology to see what works and what's a waste. Kara Swisher wants to live forever. New series now streaming with a CNN subscription. Go to cnn.com slash subscribe to get started and save 40% for a limited time. Terms apply. Hey everybody, it's Nilay. Decoder's off today while the team and I are cooking up a lot of really great stuff for the upcoming weeks. We'll be back with an all-new interview on Monday. In the meantime, we really wanted to highlight this episode we first aired back in the fall because it's about a huge subject, AI in schools. The school year is starting to wrap up now around the country and we're now closer to figuring out how to thread the needle about generative AI in education than we were back in September. Lots of people are worried about students using ChatGPT to cheat on assignments, and that is a problem. But really, the issues go a lot deeper to the very philosophy of education itself. Dr. Adam Dubé, an expert in educational technology from McGill University, joined me on the show to talk through how generative AI fits into education right now and where it might be heading in the future. We also talked to a whole lot of actual teachers. You'll hear their voices throughout this episode. And we kept hearing one thing over and over again. What are we even doing here with AI? What's the point of this? It's a big question with not a lot of answers. Here it is, AI in education. Enjoy. Hello and welcome to Decoder. I'm Nilay Patel, editor-in-chief of The Verge, and Decoder is my show about big ideas and other problems. We've talked a lot about generative AI on the show lately, which is a very big idea that is causing quite a few problems. And one thing we keep hearing about over and over again is that generative AI is causing a lot of problems in schools. There are a lot of people out there, including many of the listeners of the show who email us, who are worried about the obvious problem, students using ChatGPT to cheat on assignments. But when our team went and poked at the story, they found that the issues in education with AI go a lot deeper, to the very philosophy of education itself. We sat down and talked to a lot of teachers. You'll hear a lot of their voices throughout this episode. And we kept hearing a common theme. What are we even doing here in higher ed? Now, every teacher is having a different experience with AI in the classroom and with their students. But the common thread is that so many of those experiences feel bad. A few teachers talked to us find tools like ChatGPT are helping their workflow, but a lot of others are facing those deep existential questions like you just heard from Evie. Luckily, there are experts in education and educational technology who research what's going on in a more detailed way. So I sat down with Dr. Adam Dubay from McGill University to talk about how generative AI is fitting into education right now and where all of this might be going in the future. Support for the show comes from Zapier. Let's face it, talking about AI has become more than a trend. It's practically a daily discussion. But simply talking about AI trends doesn't help you become more efficient at work. For that, you need the right tools. You need Zapier. Zapier is how you break the hype cycle and put AI to work across your company. 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Your domain, website, email marketing, AI tools, and AI agents. You can create websites, online stores, and even custom apps without coding or design skills. Then, use AI agents to automate tedious tasks and help grow your business. Turn your one day into day one. Go to Hostinger.com slash Decoder to bring your idea online for under $3 a month. Plus, get an extra 20% off with promo code Decoder. That's less than the price of a cup of coffee per month. That's Hostinger.com slash Decoder. Promo code Decoder for an extra 20% off. Welcome back. I'm talking with Dr. Adam Dubé about what his research is saying about Generative AI in schools. Before the break, we were talking about how all of this is just new technology. And as a result, it's kind of a mess. Students are using it to cheat, although maybe not as many as we're worried about. Teachers are feeling pretty confused about how to respond. And there's just not a lot of clarity from anyone in response. That kind of usage is leading to pretty whiplash policies across schools at every level. There's the, we're going to ban it entirely kind of movement. The schools in my kids' district, they've just fully banned smartphones from schools. That's here in New York. That's statewide. There's, we have to put AI everywhere to get these kids ready. There's EdCon saying just, let my robots teach your kids. This is a pretty wild mishmash of policies and approaches. What is the general shape of it that you've seen? It is very fractured. And it depends on who the leader of that school system is and on their view of technology and then on the broader community around that school. The parents in that community, do they have a negative attitude towards technology? Right now there's a big anti-screen movement that's happening. We see cell phone bans, concerns about social media from parents. This is increasing. You have the larger community influencing the way that school leaders think about technology. But then you've got some school leaders who are saying like, okay, we're resource constrained. Our budgets are being cut and they're seeing technology as potentially a way to save money. And so they're turning to generative AI as a way to maybe make up for not having enough educators in their classrooms. Or maybe they truly believe that it's a transformational tool, but you can't, there is no one consistent system. It varies almost from school district to school district. And I've spoken with school leaders across our provinces because we run education at a provincial level. There's no federal sort of oversight. All the principals complain that there's no overarching guidance, that everyone has had to figure it out by themselves. And that leaves it up to the factors at the local level influencing whether or not AI is seen as a potential positive or negative and whether or not it's a positive or negative for teachers, the admin, or for students. There's also differences there. A lot of teachers think students shouldn't be using it, but it's okay for them to use it. Or the admin thinks this is going to help us save time for teachers marking students' assignments so we can save some money there. But we don't want our students using it, but we're going to use it to analyze student data. Right? So there's even a mismatch and a disagreement within schools about the role of generative AI. Right now, these systems are being sold to educators to generate lesson plans, to evaluate student work, to do learning analytics. And if you're having this deployed in your school and before you teach a class, you're being told, it's like, okay, well, we're going to cut back on how much teacher preparation time there is, but we bought Magic School for you. And so it's going to generate a lesson plan for you, so don't worry, you're going to have plenty of time to do it. It's like, actually, keep track of how much easier it is to generate your lesson plans and do your work with these tools. A few of the teachers we spoke with really were excited by the idea that generative AI could be a time-saving tool and actually help them out when it comes to managing a busy workload with too few resources. I'm Paul, and I teach middle school science in Raleigh, North Carolina. And the thing that has me most excited about generative AI technology is the way that it unlocks teachers' ability to do better teaching in ways that many of us really want to. We're constantly being told about new research that shows that there are better ways to teach, but many of these strategies and techniques, they require a lot of time and effort for us to, like, learn more about them and to build content with them. By partnering with an AI tool like ChatGPT, a lot of this becomes way more doable. And so I find that I'm able to integrate better strategies into my teaching because I know that I have support when it comes to building new materials with those strategies highlighted. That's all pretty interesting, but Paul's position is part of a distinct minority, certainly, at least amongst the teachers who spoke with us. Here's Evie Maine again. Despite many attempts to incorporate it into my workflow, I've found that Gen AI is more trouble than it's worth. And that's beyond the simple fact of the technology's unethical, plagiaristic roots and environmental destruction. Just purely on a utilitarian level, I can do better work much faster when it comes to designing course materials. At most, I would use ChatGPT to clean up auto-generated YouTube captions, but YouTube's already improved this on their own end, so it's kind of a moot point. And then sometimes, as some teachers told us, generative AI can make things actively worse than they were before. My name is Anne Rubinstein. I'm a historian and a professor of history at York University. One of the things that I do as a scholar is I help prepare collections of documents from the past on specific topics that are then published as part of a digital history project that goes out to university libraries mostly. Because I am a historian of Mexico, the documents that I'm preparing for them are Mexican, and they're in Spanish. The publisher decided that we should, along with providing the original documents, we should provide translations into English since that's the language that the majority of people using these teaching tools are going to be comfortable with. So great. I said, great, I've got a friend who's a translator. We'll get them to translate these documents. No problem. And they said, oh, no, no, we've bought new software that will translate for us, and we don't need to go to the expense and trouble of hiring a human translator because this translation software is going to be great. And I was skeptical, but I said, sure, let's try it. And so we tried the software, and here's what it did. It hallucinated. It made crap up. It inserted entire sentences, and in a couple of cases, entire paragraphs into the document that did not exist in the original. If you don't understand why that is a very, very big problem in a collection of translated primary source documents for history students, I invite you to come take some history classes, and then you'll understand why that's an enormous problem. Luckily, the publisher also understood this was an enormous problem. So what they decided to do was hire a translator whose job it was to go through these machine-translated documents and restore accuracy and clarity to them. And that ended up costing just about twice as much as just hiring a human translator would have done. In a strange way, it might help when the hallucinations are incredibly obvious because then you can tell that the tool isn't working for you. But sometimes it can be a lot harder to spot if a tool is actually saving you time or improving your work when you first start using it and then generative AI produces polished content and answers to questions so quickly that it feels like it's giving you something meaningful. Is it actually saving you time? I speak to teachers and they say, well, I use generative AI and it helps me generate my lessons. It helps me write emails. Actually monitor and try to keep track of, is this actually speeding things up? There's a lot of research that shows that, say, for example, with coders, they actually end up being slower when they use these systems because they have to fix all the mistakes. And I think that we might see a similar pattern that happens with educators. They're using these tools to be more efficient, they think. But if they actually tracked how long it takes them to generate a lesson versus how long it takes to fix the lessons that generative AI produces, it might not actually be faster. I see some educators that are enthusiastic about the time saving it can give them, but I'm not sure it's actually saving anybody time. So from the teacher's perspective, generative AI tools is a workplace Sure, if it's right. What if it was truthful? Well, then people might stop using it as frequently, and then maybe it's not as engaging and motivating. And so the question is there, do we think, as an educational tool, it's good to somehow generate curiosity if the thing is lying to you about the information? It's like, would that be okay if it was a human being? It's like, well, here's our teacher, Jerry. He's in the class. He always lies to the students when they ask him questions, but he constantly, but he gets them going. And it's like, well, that seems like a really weird position to take when we translate this over. There are some core skills that you should definitely have to learn. I actually think math is one of them. But I, you know, I do have friends who are like, screw it. I have a calculator. I can literally Google the answer to unit conversion, and I will never think about it again. ChatGPT is that on a massive scale, right? You can just hand over some amount of skills to this robot about thinking about a lot of things. And maybe you'll just not be motivated to learn those skills because you know there's a backstop. Whether or not the backstop hallucinates, you'll know there's a backstop, and you'll never be motivated to learn those skills. Have you seen that dynamic play out? The classic example, as I said, is the calculator, and some people say that it didn't matter that we put calculators in classrooms. I actually had a colleague who I will say that looked at this throughout the 90s and 2000s in Canada, and we actually saw a decrease in math scores directly correlated with increasing calculator use. Because when you're using a tool to do thinking for you, you're not practicing and actually encoding the information well enough to actually recall it later on. And so it's not surprising that when people use generative AI to do work for them, that they're not able to do it independently. Being able to store information in your memory requires effortful practice. It requires effortful memorization. It requires reflection. It requires thinking about, okay, what am I trying to understand and connecting that to my other understanding? That's what builds a strong knowledge network. And when you use systems that just generate answers on your behalf, you don't engage in those practices. It just gives you the response and you passively consume it, and maybe you don't reflect on it. So it's not surprising that with the use of generative AI, one of the big effects that we see is that people are able to produce maybe work that looks more polished, but they don't remember the work that they actually wrote. That MIT study is the example that a lot of people have heard about where they had people writing essays with or without ChatGPT or Google, and students had very poor memories for the essays that they wrote using ChatGPT. Well, that's because they actually weren't reflecting on their writing. They weren't engaged in the work that it takes to actually form substantial memories that you can remember later on. Now, should we care? That's the thing. Who cares if you can produce the product and if you can produce the work in the end? It's like, it doesn't matter. Well, if we think of a future down the line where if you're using these tools to produce a piece of work, who is actually able to evaluate whether or not that work is any good if everyone is just in the same level of expertise of just, I've used all these tools to produce the work. You actually don't have the internal knowledge. You don't have the internal skill set to say, like, is this good writing? Is this a strong idea or not? You don't know anything about the literature. You don't know anything about the area that you're actually studying because you just use these things as the reference. The people always say, I don't need to count. It's like, well, I can just use a calculator. Well, I bet that person doesn't have to do mathematics in their job every single day. Right? So they're not regularly having to do unit conversion on the fly. So it doesn't really matter because they don't use it. But in your profession, in your daily lives, access to information really does matter. If you have to grab something, you don't want to have to turn to an external tool to make a judgment in a moment. I shouldn't have to be talking to you in this conversation and then having ChatGPT open over here to ask it things so I can have a conversation with you. That wouldn't be an actual productive conversation. It would impede how well I interact with my daily lives and do my job. And so it does matter when we don't actually know things and have a knowledge base on which we work. So then teachers are left with the challenge of getting students not to let ChatGPT do the thinking for them, at least not in class. Sometimes addressing it head on is the way to go. Here's Anne Rubinstein again. What I've worked out to do with the first year undergraduates, especially, is not so much to tell them that they can or can't use this stuff to help them in their process of becoming history students, but to think with them about the ways in which this particular kind of software is likely to lead to bad results for historians in particular. What I tell them is, as historians, we have a social responsibility to get our facts exactly right. Not only to say exactly when the specific event happened, but if we're quoting to back up our assertions, which we frequently do, we have to say who was speaking and also how we know what words they said and also to quote their words precisely in the precise order, not to add any, not to leave any out, and to say where and when this quotation was made and to put it in its context. Once we've sort of gone through that with the beginning history students, then I talk to them about ChatGPT and similar software, and I say, okay, how does it work? And I pretend to be slightly more naive than I actually am. And I say, okay, explain to me how this works. And usually in any group of, say, 10 or more undergraduates, one of them is going to have a very clear understanding of how this software works. So I get them to explain it to me and incidentally to explain it to themselves and each other. And we talk about how the software can't, by its nature, actually know a thing. What it can tell you is what order words are likely to be in. And if we're very lucky, what'll happen in the classroom as we're figuring this out together, going over it together, is that someone will say, oh, so they're bullshitting. And I say, yes, that's bullshit. And then we talk about what bullshit is and why we want to avoid bullshitting and why bullshitting is sometimes useful and important in life. But historians aren't allowed to bullshit. We absolutely cannot bullshit. We are the only people in the world who are never, ever allowed to use bullshit. And so then the lesson is, you can use ChatGPT and similar software for all kinds of things, but you cannot use it in conducting historical research or writing about history because it is the exact opposite of what historians are supposed to do. What Anne just described, being able to talk through the reasons why you would or wouldn't want to use a specific tool, is really important. Because ChatGPT is just that, a tool. And students who are under a lot of different pressures might reach for any tool they have at hand. And maybe, aside from that 10% Adam told us about who are happy to just cheat, maybe it's not hard to see what pressure students are reacting to. In a way, they're just behaving rationally inside of the system that they're a part of. And that itself is a kind of problem. Are the educational systems we've set up actually designed to prioritize learning as an incentive for the students? I'm Brian S. and I teach technical communications at a Midwestern Research 1 university. I have a lot of engineering majors in my classes and my job is to teach them how to speak about engineering things to non-engineers. The big effect large language models have had on my job and my students is that it's really forced me to recognize how differently I see what's valuable in the classes from at least some of my students. In my classes, I teach a lot of how to write things. Some of it is format, but more of it is about tailoring a message to an audience, translating concepts from expert to non-expert. But as with most writing classes, the grades are based on the finished product, the user manual or the proposal or the report. I use those to evaluate how well the students have internalized the tools I've been showing them how to use. LLMs promise that they can create those documents without having to learn all those intermediate steps. And when they're being used by a person who already has those skills, they can take some of the grunt work out of it. My students don't have those skills yet. And if they lean on LLMs now, they'll never develop those skills. But for a pretty good size portion of my student body, that's not a problem because, one, they have limited time and they have physics exams and so on. And two, because they get graded on the finished product. For me, the finished product doesn't really matter. I've read enough proposals for free student parking on campus for multiple lifetimes. But for them, it matters because it can affect their academic standing, potentially their financial aid, et cetera, et cetera. And students are under tremendous pressure that affects how they approach their college education. My university largely has students who are focused on getting out of here and getting a job. A lot of them work full time or are full time caregivers or have some kind of equivalent everyday pressure on them. They're taking multiple courses at a time. They're trying to make it all work out