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Speaker 3: In the world of educational research, is a famous video
Speaker 3: of a boy named Sean. I don't mean famous in
Speaker 3: a sense that it has a million views on YouTube.
Speaker 3: I mean that in the circle of people who think
Speaker 3: about teaching and how to make teaching better. The video
Speaker 3: has been written about in journal articles and shown over
Speaker 3: and again in college classrooms. It's a ten minute clip
Speaker 3: of a third grade class somewhere in Michigan. It was
Speaker 3: filmed in January of nineteen ninety, so the video is
Speaker 3: a bit grainy. The teacher's name is Deborah Lowenberg Ball.
Speaker 3: She's a professor at Michigan State University who is part
Speaker 3: of her research. Teaches a one hour math class at
Speaker 3: a local elementary school on the day in question. Miss
Speaker 3: Ball begins by asking her students about the previous day's lesson,
Speaker 3: which was about even and odd numbers.
Speaker 4: I would like to hear from as many people as possible,
Speaker 4: what comments you had, reactions you had to be in
Speaker 4: that meeting yesterday.
Speaker 3: A little boy with black hair raises his hand. His
Speaker 3: name is Sean.
Speaker 4: Hello.
Speaker 5: I don't have anything about the meeting yesterday.
Speaker 4: That was Sean was.
Speaker 3: Thinking about the number six.
Speaker 5: So I was thinking that it's a it's an idd
Speaker 5: it can be an odd number two because there could
Speaker 5: be two, two, four, six, two, three twos and two
Speaker 5: threes and add Antonisina two thinks make Italy two things.
Speaker 3: And Sean doesn't understand what odd and even means. He
Speaker 3: thinks that just because you can break down six in
Speaker 3: an odd number of parts and an even number of parts,
Speaker 3: that six must exist in some magical middle category. And
Speaker 3: when you listen to the Sean videotape, you keep waiting
Speaker 3: for the teacher to say, oh, no, Sean, you misunderstand.
Speaker 3: But Deborah Ball doesn't do that. She never tells him
Speaker 3: he's wrong. Instead, she simply asks him to explain his thinking.
Speaker 2: And the two things that you put together to make
Speaker 2: it were odd right?
Speaker 6: Three and three are each old and thinks Roba so.
Speaker 3: Two or even bald and asked the class to give
Speaker 3: their views. Other students jump up and explain their theories
Speaker 3: on the blackboard. For the next fifteen minutes, she defintely
Speaker 3: guides the class through an in depth investigation of what
Speaker 3: she calls shawn numbers until Sewn himself realizes that the
Speaker 3: real meaning of odd and even is something different than
Speaker 3: he had imagined. And now he gets it.
Speaker 5: I've been great, Thank you for when you are in love.
Speaker 3: I don't want to focus just on how little Sean
Speaker 3: finally made his own way to the right answer. I'm
Speaker 3: interested in what his teacher did to get him there.
Speaker 3: Deborah Ball worked magic. She never told Sean the right answer,
Speaker 3: She just led him to a place where he could
Speaker 3: discover it for himself. My name is Malcolm Glawo. This
Speaker 3: is season six of Smart Talks with IBM, where we
Speaker 3: offer our listeners a glimpse behind the curtain of the
Speaker 3: world of technology and artificial intelligence. In this season, we're
Speaker 3: going to visit companies as varied as Laurel and Ferrari
Speaker 3: and tell stories of how they're using artificial intelligence and
Speaker 3: data to transform the way they do business. This episode
Speaker 3: is about the promise of a radical new idea called
Speaker 3: responsive teaching, the kind of teaching that took place that
Speaker 3: day in Shawn's classroom, and whether artificial intelligence can help
Speaker 3: us train the next generation of teachers to be as
Speaker 3: good as Deborah Ball. Before we talk about how AI
Speaker 3: could transform the way we train teachers, I want to
Speaker 3: go back for a moment to the famous video of Sean.
Speaker 3: In the video, the teacher Deborah Ball doesn't have a
Speaker 3: predetermined plan that she's imposing on the class. She's improvising,
Speaker 3: making up her approach as she goes along, responding to
Speaker 3: her student's odd theory about the number six. Second, she's
Speaker 3: taking Sean seriously. She's not dismissing his theory. She's listening
Speaker 3: to him and trying to understand the problem from his perspective.
Speaker 3: And Thirdly, and most importantly, she's not force feeding him
Speaker 3: the right answer. She's being patient. She's waiting to see
Speaker 3: if with just the right subtle hints, he can get
Speaker 3: to the right answer on his own. Improvisation empathy patients.
Speaker 3: That's responsive teaching.
Speaker 7: What I think about in terms of responsiveness is more like,
Speaker 7: I think that students need to have a sense of
Speaker 7: agency in what happens in the classroom, and like authentic
Speaker 7: agency where they can be legitimized as knowers.
Speaker 3: I spoke to a physicist at Seattle Pacific University named
Speaker 3: Amy Robertson, a longtime advocate for responsive teaching. She uses
Speaker 3: the Sean video in her classroom.
Speaker 7: You have to trust that kids have a way of
Speaker 7: doing that and that, like heard, what she mostly did
Speaker 7: was to facilitate a conversation and to say you have
Speaker 7: to listen to them talk.
Speaker 3: No one told him he was wrong, that's right, and
Speaker 3: then he goes, He goes. I didn't think of it
Speaker 3: that way again.
Speaker 7: I thank you for bringing it up.
Speaker 3: You've expanded my understanding. Thank you for bringing it up again.
Speaker 3: It's like this, I love, I love.
Speaker 7: I Responsive teaching, as I think about it, is kind
Speaker 7: of rooted in this like Eleanor Duckworth's work around the
Speaker 7: Having of Wonderful Ideas, where she says, like, the goal
Speaker 7: of education is for students to have wonderful ideas and
Speaker 7: to have a good time having them.
Speaker 3: But I love that. I've never heard that. What a beautiful,
Speaker 3: succinct way of summing up the purpose of education. Yes,
Speaker 3: responsive teaching is beautiful. It's rare to find a new
Speaker 3: teaching idea that everyone loves. This is one of those
Speaker 3: rare ideas. Watching the Deborah Ball classroom, all I could
Speaker 3: think was, I really really hope my daughters get to
Speaker 3: experience a math class like that. Far too many kids
Speaker 3: are convincing themselves at far too young an age that
Speaker 3: math isn't for them, and responsive teaching is a way
Speaker 3: to solve that problem. But here is the issue. It's
Speaker 3: really really hard to teach responsive teaching. Robertson says that
Speaker 3: teaching exists in a cultural environment where the teacher is
Speaker 3: expected to be the source of truth that teaching is
Speaker 3: about the immediate correction of error and not letting a
Speaker 3: child wander down the pathway of their own misunderstanding. Responsive
Speaker 3: teaching is deeply counterintuitive, and the only way to understand
Speaker 3: its beauty is to do it over and over again.
Speaker 3: Aspiring teachers need a way to practice. For as long
Speaker 3: as there has been technology, people have turned to digital
Speaker 3: machines to solve problems. My father was a mathematician and
Speaker 3: I remember him coming home in the nineteen seventies with
Speaker 3: a big stack of computer cards in his briefcase that
Speaker 3: he used to program the main frame back the office. Today,
Speaker 3: with the rise of artificial intelligence, the scale and complexity
Speaker 3: of the problems technology can help us solve has jumped
Speaker 3: by many orders of magnitude. You must have worked with
Speaker 3: a with a million customers who are experimenting with lll ms.
Speaker 3: Has there been one use case that you were like, WHOA,
Speaker 3: I had no idea or just simply that's clever. I'm
Speaker 3: speaking to Brian Bissel, who works out of IBM's Manhattan office.
Speaker 3: He helps IBM customers discover how best to get AI
Speaker 3: to work for them.
Speaker 8: There is one, but I don't think I can talk
Speaker 8: about it.
Speaker 3: Unfortunately, Wait, wait, you can't tease me like that, can
Speaker 3: you wait? Disguise disguise it for me, Just give me
Speaker 3: a general.
Speaker 8: It was about the ability to pull certain types of
Speaker 8: information out of documents that you you wouldn't think you
Speaker 8: would be able to get the model to do, and
Speaker 8: be able to do that at a very large scale.
Speaker 3: Bissile's point was that we are well past the stage
Speaker 3: where anyone wonders whether a I can be useful. The
Speaker 3: real question now is what problems do we want to
Speaker 3: use it to solve? Where it can make the biggest difference,
Speaker 3: And Basil saw lots of opportunities in education.
Speaker 8: I have two kids, one in middle school and one
Speaker 8: who just graduated high school, and I'm well aware of
Speaker 8: students using things like chat GPT to do their homework.
Speaker 8: And it's very easy to take tools like that and
Speaker 8: even IBM's own large language models and just take a problem,
Speaker 8: a piece of homework, something you want written, and drop
Speaker 8: it into that and have it generate the answer for
Speaker 8: you and the student. The user in that case hasn't
Speaker 8: done any work, they haven't put any real thought into it.
Speaker 3: To Basil, that's the wrong use of AI that's technology
Speaker 3: making is dumber. What we really want is technology that
Speaker 3: makes us smarter. Basil explain to me that there are
Speaker 3: now two big tools being used for AI productivity, AI
Speaker 3: agents and AI assistants. Let's start with AI agents. AI
Speaker 3: agents can reason plan and collaborate with other AI tools
Speaker 3: to autonomously perform tasks for a user. This will gave
Speaker 3: me an example of how college freshmen might use an
Speaker 3: AI agent.
Speaker 8: As a new student, you may not know how do
Speaker 8: I do with my health and wellness issue? So many
Speaker 8: credits are going to get for this given class. You
Speaker 8: could talk to someone and find out some of that,
Speaker 8: but maybe it's a little bit sensitive and you don't
Speaker 8: want to do that.
Speaker 3: Bisill told me you could build an AI agent, a
Speaker 3: resource for new students that helps them navigate a new campus,
Speaker 3: register for classes, access the services they need, and even
Speaker 3: schedule appointments on their behalf, which in turn buys them
Speaker 3: more time to focus on their actual school work.
Speaker 8: We can see patterns of how agents and assistants can
Speaker 8: help employees and customers and end users be more productive.
Speaker 8: Automate workflows are not doing certain types of repetitive work
Speaker 8: over and over again. And streamlining their lives and making
Speaker 8: data more accessible to them twenty four hours a day.
Speaker 3: But Bissil says you can also use AI assistance in
Speaker 3: the education space. AI assistants are reactive as opposed to
Speaker 3: AI agents, which are proactive. AI assistants only performed tasks
Speaker 3: at your request. They're programmed to answer your questions, and
Speaker 3: as it turns out, AI assistants are now being used
Speaker 3: to further the responsive teaching revolution, which is why I
Speaker 3: found myself on a beautiful Georgia spring day not long ago,
Speaker 3: on the campus of Kansas State University, sitting in a
Speaker 3: classroom with two researchers, one of them Professor Dabe Lee.
Speaker 3: Let's go into the journey of building this thing. You
Speaker 3: started w by taking a course.
Speaker 9: What was the course you took, Yeah, so it was
Speaker 9: offered by Coursera. It was designed by IBM AI Foundation
Speaker 9: for everyone.
Speaker 3: In her AI Foundation's course, Lee learned how to build
Speaker 3: an AI assistant using IBM Watson X. That course took
Speaker 3: how long to take.
Speaker 9: It was not to know it was like fourteen weeks.
Speaker 3: Lee's idea was to train an AI assistant on classroom
Speaker 3: data to play the role of sean A digital persona
Speaker 3: of a nine year old who likes math but doesn't
Speaker 3: always understand math, and that AI assistant she thought could
Speaker 3: be used to train preservice teachers or teachers in training
Speaker 3: who are preparing to enter one of the most challenging
Speaker 3: professions in the modern world.
Speaker 9: So when you think about the teacher education and a
Speaker 9: major challenge that teacher education phase is that we need
Speaker 9: children to practice with. We need instructors who will give
Speaker 9: the instruction on the pedagogical skills. So when you look
Speaker 9: at the education program, we have coursework in field experience,
Speaker 9: and in those two areas there is something missing all
Speaker 9: the time.
Speaker 3: Li says that pre service teachers often lack access to
Speaker 3: both students and experienced teachers during their education.
Speaker 9: So what we try to resolve is that we have
Speaker 9: this virtual student for pre service teacher to work with
Speaker 9: so that they can practice their responsive teaching skills.
Speaker 3: The first AI assistant Lee created is g Wu gi Wu,
Speaker 3: emulates the persona of a nine year old third grade girl. Then,
Speaker 3: with the help of one of her collaborators, a researcher
Speaker 3: at Canazon named Sean English, she created two more AI assistants,
Speaker 3: Gabriel and Noah, each of which have their own distinctive characteristics.
Speaker 3: So how are gabriel and Noah different from.
Speaker 9: G Wu Gabrielle? My first one is very short answered.
Speaker 9: If you ask an open ended question, he will answer
Speaker 9: it in a close way. So I use that characteristic.
Speaker 9: And that's the problem that most teachers actually base. They're
Speaker 9: asked children who are shay, who are reserved, and who
Speaker 9: would not share much of their thoughts. So we wanted
Speaker 9: that characteristic in some characters, and we use Gabrielle to
Speaker 9: have that characteristic.
Speaker 3: And Noah. What'snawah's personality?
Speaker 6: How do he playful? Cheery, bright and energetic?
Speaker 3: That's Sean English professor, Lee's fellow researcher.
Speaker 9: And Jewu is articulated and kind of smart, but he
Speaker 9: she has her own way of thinking.
Speaker 3: I would end up spending a lot of time with
Speaker 3: jie Wu. She's something of a character. I asked Sean
Speaker 3: about the process of creating these AI assistants. What does
Speaker 3: building the content side of the AI assistant entail? Sean?
Speaker 9: What?
Speaker 6: It sets up a series of actions, effectively, which are
Speaker 6: response cases. You can kind of think of them as
Speaker 6: you have a series of questions that you tie to
Speaker 6: an intent, and then that intent has reactions from the bot,
Speaker 6: and so effectively, if we were looking to say make
Speaker 6: a hello action, we would have all the different ways
Speaker 6: that people could say Hello, Hello, what's up, how you doing,
Speaker 6: and all that kind of stuff.
Speaker 3: Sean says, the longer the list of potential responses, the better,
Speaker 3: But AI's responses don't just follow the list. The AI
Speaker 3: assistant uses those suggested responses to come up with a
Speaker 3: universe of other responses, and in that process sometimes it
Speaker 3: comes up with things that just don't make sense.
Speaker 6: And from a technological standpoint, while AI is a fantastic tool,
Speaker 6: AI can hallucinate, which I mean, just give things that
Speaker 6: it's just straight up made up. There's a famous example
Speaker 6: of this called the three rs is where you ask
Speaker 6: a popular large language model how many RS are in strawberry,
Speaker 6: and it gives you the wrong answer, and he repeats
Speaker 6: that result repetitively. You always want to have a human
Speaker 6: interacting with the system to be able to go, hey,
Speaker 6: that's a little crazy. I don't think that's exactly what
Speaker 6: we're going for here.
Speaker 3: That's why it's good to have someone like Sean English
Speaker 3: around to step in and get the model back on track,
Speaker 3: and over time, when the model has enough training, it's
Speaker 3: ready for the teachers in training. One of the rollouts
Speaker 3: of Jiwu, Gabriel, and Noah was with the teacher training
Speaker 3: program at the University of Missouri.
Speaker 10: I was just kind of excited to see what the
Speaker 10: program was and what it was going to be doing.
Speaker 3: This is Logan Hovis, a junior at Missouri on the
Speaker 3: path to becoming an elementary school teacher.
Speaker 11: Obviously a little skeptical when he said it was so
Speaker 11: to you know, be like talking to a student. You're like,
Speaker 11: there's no way this AI thing is going to totally
Speaker 11: sound like a second grader or a third grader, Like
Speaker 11: it's going to sound like an adult, or it's going
Speaker 11: to sound like a robot that knows all the answers.
Speaker 10: And it really didn't. It really was like talking to
Speaker 10: a child.
Speaker 11: It was very very well developed in the way that
Speaker 11: you really sit there and you feel like you're talking
Speaker 11: to a kid.
Speaker 3: Her point wasn't that Jiwu and her fellow avatars were
Speaker 3: equivalent to real kids. Of course not, but for someone
Speaker 3: starting out, someone who was already nervous about being plunged
Speaker 3: into a classroom of nine year olds, Jeewu was like
Speaker 3: a warm up before a baseball game.
Speaker 11: What I can think of is like, you know how
Speaker 11: when you're at batting practice for baseball or softball, you
Speaker 11: have those automatic pitchers that throw them because you're working
Speaker 11: on your skill as the hitter. What can I do differently?
Speaker 11: What am I doing wrong? But that doesn't replace the
Speaker 11: game and what you do in a game. But this
Speaker 11: is you getting to practice your own skills to be
Speaker 11: better when you go in a game. And I think
Speaker 11: that's kind of what the AI software feels like for us.
Speaker 3: In batting practice, the pitches don't come as hard and
Speaker 3: fast as the pitch is in a real game, but
Speaker 3: you get to stand at the plate and the pitcher
Speaker 3: throws you dozens of balls over and over again in
Speaker 3: a concentrated block that allows you to work on your
Speaker 3: swing closely and carefully.
Speaker 10: There's a lot less stimulus going on around because the
Speaker 10: classroom is very very busy. It's wonderful, it's beautiful, but
Speaker 10: it's very very busy, so sometimes it's hard to keep
Speaker 10: you know, that focus in on the tasks that they're
Speaker 10: doing at hand, and also in the teacher setting, you're
Speaker 10: also kind of always looking around making sure that other
Speaker 10: students are doing what they're supposed to be doing, but
Speaker 10: also like if they need any help, if everything's going
Speaker 10: okay in the classroom. So being on the Jiwu chat,
Speaker 10: it was just nice that you didn't have to do
Speaker 10: any of the extra work to keep the focus on there,
Speaker 10: and it also felt you did have to feel the
Speaker 10: student's nervousness of being one on one with you, and
Speaker 10: also as a teacher, it was a lot less pressure
Speaker 10: too because I was like, Okay, I'm taking this series.
Speaker 10: This is a student I'm questioning, but.
Speaker 11: I also know I'm probably not going to hurt someone's
Speaker 11: feelings right now, and that's terrifying to think I'm going
Speaker 11: to ask the wrong question and upset the child because
Speaker 11: I've done that.
Speaker 3: We think of the typical use of AI as a
Speaker 3: tool for speeding things up. That's what we always hear
Speaker 3: that the introduction of AI to problem X gave an
Speaker 3: answer in minutes when solving problem X used to take weeks.
Speaker 3: But we shouldn't forget another use that it allows us
Speaker 3: to slow things down. Hoves, if she wanted to, could
Speaker 3: spend a whole weekend practicing with ji Wu. A real
Speaker 3: nine year old will get frustrated on board with the
Speaker 3: fumbling novice after ten minutes, but gi Wu ji Wu
Speaker 3: will happily answer questions for as long as it takes
Speaker 3: for the people who want to learn to be responsive
Speaker 3: to learn how to be responsive. At the end of
Speaker 3: my time at Kennesas State, Sean and Dabe led me
Speaker 3: to a small table where Dabe had set up her laptop.
Speaker 3: In the corner of the screen was a chat box
Speaker 3: of the sort we've all seen and used a thousand times.
Speaker 3: Ji Wu began. She had been given a math problem.
Speaker 4: Rutle, who are of three fourth cup of a flower
Speaker 4: to the ball thanks to the added another three six
Speaker 4: is cup. It's a total amount of flower the use
Speaker 4: greater or dan or a less than one cup? How
Speaker 4: much flower.
Speaker 10: They can use.
Speaker 3: That's a simulation of Giewu speaking. We pause it for
Speaker 3: a second. So Jewu is trying to solve this problem.
Speaker 3: And the first thing she does is she draws a
Speaker 3: rectangle on the screen. This is a common tactic of
Speaker 3: nine year olds try to visualize the fractions. And she
Speaker 3: divides it into four pieces. And now she's gonna color
Speaker 3: in three of the four pieces. Yes, so she's representing
Speaker 3: this is quite good. She's representing three quarters on the screen.
Speaker 4: This is three sixes.
Speaker 3: So now Jiwu does another rectangle with six boxes and
Speaker 3: colors in three of them.
Speaker 4: Okay, together makes sikes going off.
Speaker 3: So then she counts up all the colored boxes and
Speaker 3: that's her numerator, and counts up the total number of
Speaker 3: boxes and that's her denominator. Ji Wu had counted the
Speaker 3: colored boxes and landed on an answer. When you add
Speaker 3: three quarters of a cup and three sixths of a cup,
Speaker 3: you get six tenths of a cup. So, according to
Speaker 3: ji Wu, Martin has less than one cup. And she
Speaker 3: thinks she solved the problem.
Speaker 9: Yes, okay, so it's less than one cup.
Speaker 3: Yeah, so she says it's less than one cup. Now,
Speaker 3: oh my god, this is hard. So the question is
Speaker 3: what do I, as a teacher say to Jiwu. We
Speaker 3: were off. The rules were simple. I couldn't give ji
Speaker 3: Wu the answer or explain to her what she was
Speaker 3: doing wrong. I had to be Deborah Ball. I had
Speaker 3: to help her find the way herself. The chat box
Speaker 3: in the corner of the screen was waiting for my
Speaker 3: first question. I thought for a moment and started typing,
Speaker 3: do you think the boxes in the red rectangle are
Speaker 3: the same size as the boxes in the blue rectangle.
Speaker 3: Then I turned to Sean and dabey, is that a
Speaker 3: good question?
Speaker 2: Yeah, serious thing.
Speaker 9: Yeah, that's a good question.
Speaker 3: Jewu doesn't mess around. She answers immediately. So Ju says,
Speaker 3: the blue and red pieces are not the same sizes.
Speaker 9: Oh so you understand now, gu knows that side differences.
Speaker 3: She's pretty smart here.
Speaker 9: Yeah.
Speaker 3: Then I asked, if they are not the same size,
Speaker 3: do you think you can add them together? Jiwu answered
Speaker 3: right away. Jiwu says, I have learned that I could
Speaker 3: add any numbers in grade two. So three p three
Speaker 3: is six and four to six is ten.
Speaker 9: Yeah, so she is using the knowledge of edge intiquers
Speaker 9: into adding fractions.
Speaker 3: Now I'm stumped. So now I have to somehow lead
Speaker 3: her to figure out a way to get her to
Speaker 3: understand that we're dealing with a different kind of problem,
Speaker 3: a harder problem. Amy Robertson had told me that learning
Speaker 3: how to do responsive teaching properly was really hard, and
Speaker 3: now I understood why. I had to put my mind
Speaker 3: inside the mind of a nine year old. I had
Speaker 3: to internalize her knowledge base and assumptions and keep in mind,
Speaker 3: I haven't been nine for a very long time. I
Speaker 3: honestly had no idea what to say next. I thought
Speaker 3: for a moment, I asked what I quickly realized was
Speaker 3: a hopelessly convoluted question. Dobby and Sean had built a
Speaker 3: mentor into the system, an experienced, responsive teacher who supervises
Speaker 3: the session and offers advice. My mentor noticed that I
Speaker 3: was struggling, told me to simplify my question. Grader Dobby
Speaker 3: was trying to help me too, She suggested, why not
Speaker 3: just ask ji Wu if three quarters is bigger or
Speaker 3: smaller than one half?
Speaker 9: So we are trying to help her to think about
Speaker 9: faction in a more conceptual way.
Speaker 3: This time, Jiwu understood. She wrote back, three quarters is
Speaker 3: larger than one half? I wrote back, is three sixths
Speaker 3: of a cup bigger or smaller than one half? Jewu said,
Speaker 3: I'm confused.
Speaker 2: Oh no, I've confused, gi Wu.
Speaker 9: But it's good she's understanding. She's realizing her misconception. So
Speaker 9: she's getting confused.
Speaker 3: She says, I'm confused. Three quarters is pretty close to
Speaker 3: one and adding three six would make it go over one.
Speaker 2: Oh, so she's got the answer.
Speaker 3: Yeah, But then she says, but there are six pieces
Speaker 3: out of ten, which is less than one, so I
Speaker 3: don't get it.
Speaker 9: So she's the point that, oh this, I have something
Speaker 9: wrong here. That's a good sign.
Speaker 3: She's getting there.
Speaker 9: Yeah, she's getting there, but.
Speaker 3: I still have to get her. She has to get
Speaker 3: the six pieces out of ten.
Speaker 2: Out of her head.
Speaker 3: Yeah, I have no idea how to do that? What
Speaker 3: he and she thinks she's confused when she has Actually
Speaker 3: she's figured out the answer. Yeah, she did, So we
Speaker 3: have advance. Even in my stumbling and bumbling, we've made
Speaker 3: some progress, and.
Speaker 6: Very notable progress.
Speaker 3: My conversation with jie Wu went on for some time,
Speaker 3: and eventually I got there. Jie Wu found her way
Speaker 3: to the right answer. She said, I have more than
Speaker 3: one cup of flower. The mentor chimed in. I got
Speaker 3: a little emoji that made me feel good, And when
Speaker 3: it was over, I realized two things. The first was
Speaker 3: I needed more batting practice, much more, and that batting
Speaker 3: practice was really really easy to do, because someone has
Speaker 3: gone to the trouble of building me my very own
Speaker 3: baseball diamond and given me a pitcher who had thrown
Speaker 3: me baseballs all day long. The second thought was that
Speaker 3: I've been thinking about AI all wrong. I have interpreted
Speaker 3: a lot of the talk about the promise of AI
Speaker 3: to be about replacing human expertise. I had actually thought
Speaker 3: when I first heard about Dabe's project that that's what
Speaker 3: Dabe and Sean were doing, creating an AI to teach
Speaker 3: students by passing the teacher altogether. But if you did
Speaker 3: it that way, you had missed the magic of the classroom.
Speaker 3: Remember Eleanor Duckworth's quote, the goal of education is for
Speaker 3: students to have wonderful ideas and have a good time
Speaker 3: having them. I think we often focus on the first
Speaker 3: part of that formulation, the wonderful ideas, but neglect the second,
Speaker 3: the good time having them. Real learning is born in pleasure,
Speaker 3: in community, in playful discussion, in a group of kids
Speaker 3: coming together to solve a problem, and all of that
Speaker 3: magic only comes from human interaction from a teacher who
Speaker 3: is skilled enough to inspire a class of nine year olds.
Speaker 3: We don't want AI assistants to replace the teacher. We
Speaker 3: want AI assistants to help teachers turn themselves into even
Speaker 3: better teachers. Smart Talks with IBM is produced by Matt Romano,
Speaker 3: Amy Gaines McQuaid Lucy Sullivan and Jake Harper. We're edited
Speaker 3: by Lacy Roberts, Engineering by Nina Bird Lawrence, mastering by
Speaker 3: Sarah Brugerer. Music by Gramoscope. Special thanks to Tatiana Lieberman
Speaker 3: and Cassidy Meyer. Smart Talks with IBM is a production
Speaker 3: of Pushkin Industries and Ruby Studio at iHeartMedia. To find
Speaker 3: more Pushkin podcasts, listen on the iHeartRadio app, Apple Podcasts,
Speaker 3: or wherever you get your podcasts. I'm Malcolm Gabo. This
Speaker 3: is a paid advertisement from IBM. The conversations on this
Speaker 3: podcast don't necessarily represent IBM's positions, strategies, or opinions.