Priya Lakhani (7:35)
And then it hallucinated and confabulated and you were like, big Tech. Seriously, you had one job to do. Sam Altman with all that money and it's making stuff up, right? And then for the lawyer who shared it in a courtroom and got fined, sheer humiliation and embarrassment for those people. And I think we've ended up with this sort of sinking realization of acceptance, right, that the shortcuts don't really replace the work. They're very helpful, but we still need to learn. We need to produce. And we need to think now, when we read those long answers that an LLM chatbot gives us, it feels very fluent when you read it, doesn't it? The problem is, is that fluency we often mistake for learning. And that is why people we know, not us, of course, but they end up with this sort of illusion of competence, like they know everything, right? What we actually know about learning is that learning requires what researchers called a productive struggle. It's this sort of mental effort, right, that builds understanding. Now, my top learning techniques, I've got four of them that all involve a productive struggle, and they improve outcomes. We've seen them work. Three of them are about memory. This is really important. Memory and understanding are two sides of the same coin. If you think about it. We draw on what we remember in order to shape what we think. If we can't recall it, we can't use it. So the first important one is retrieval. This is simply the act of recalling from our brain. So students in a study were given a passage, right? And it's the students who only read it once, but then try to recall it from their memory. Who could remember it far better than students who just read it over and over and over again? The second is spacing. And this is essentially students who then space their learning over time. So rather than cramming things all in one go, students that can do that active process of retrieval over time, because then you're essentially going through that productive struggle over and over again. The third, we don't like this one, but it's just generation, right? So students in a study were given word pairs like rapid, fast, and cold and hot. But then another set of students were just given the first word, and then a cue like the F, they had to come up with fast. Students who have to generate the answers themselves, even if they get them wrong initially, create a stronger memory trace. They remember more in the end. And then the fourth is reflection. When we reflect on our work and we are given structured feedback in three very specific ways. How am I learning right now? What is my learning goal? And then what are the gaps to get to that goal? What do I need to do those students improve their outcomes? Now, you'll find that these four techniques have something in common. They are harder. They all involve a productive struggle. We know sustained mental effort strengthens the parts of the brain, and it's positively correlated with growth in the brain. There was an amazing study in my home city of London with black taxi drivers. Now, if you're a cabbie in London, you Have to pass a test call the knowledge. You have to memorize 26,000 streets in the city of London. You're not allowed to use navigation apps now. Wow. Exactly. Right? Isn't that crazy? Yeah. No Uber drivers for them. Right? And so neuroscientists scanned their brains and they found that parts of the hippocampi in the brain, this is the part of the brain that's responsible for spatial memory and navigation, were larger in parts with experienced cabbies, because you have to build all of those mental models. You have to generate new routes every time you have a new passenger. And so they say that that growth, because of the positive correlation with what they have to do, is really meaningful and telling. And it is no different for learning. Durable learning does not come from shortcuts. It comes from certain types of effort. And this is why AI is amazing for education. Because AI can spot patterns in how we all learn. It can spot patterns in how concepts across subjects connect. It can predict if you don't know something and provide you with that material at the right time. It can provide us with timely, targeted interventions and give teachers those insights. It can predict when you're just about to forget something and give you that material at just the right time. It can force you to generate an answer rather than just reveal the answer. And it can provide amazing structured feedback against expertly designed rubrics from teachers. So AI, well designed can be phenomenal in education. And we've seen it work. Now a lot of people come to me, students and adults, and they say, but why bother? Because we've got gps, right? We have AI. We can Google the answer to absolutely anything, so we don't need to do this anymore. That's not true if you think about AI. AI is our history predicting our future. It is brilliant at space spotting patterns in data. It has been amazing as a partner in remarkable breakthroughs like drug discovery and protein folding, new materials and crystals. But the thing is, none of that happens with AI in isolation. We humans, we frame the questions, we set the goals, we chose the data sets. We decide which discoveries matter. Our knowledge is is not just trivia. It is the raw material of thinking and discovery. AI is not there to replace our expertise. It's there to allow our expertise to expand. And if you think about powered flight, penicillin, electricity, AI itself, humans learned. They went through that productive struggle, right? They built domain expertise, and from that, they took a leap in their imagination and they created innovations. So for students who want to cheat and want to use AI to do their homework, for us lifelong learners, right, who are reading and reading and reading and reinforcing that illusion of competence. Just remember, you do not get the growth unless you go through the struggle. So whether AI is good or bad for education is totally up to you. Are we designing it well and are you using it to complement or to replace human cognition? So the next time you're learning and you want to invest in yourself, educate yourself, you want to grow, and maybe take that leap in imagination, just remember, mental effort is not a flaw in the process. It is a critical feature that allows learning to stick, allows us to build expertise and fuel human ingenuity. Thank you so much for listening to me and good luck with your AI journey.
