Speaker 1: Brought to you by Toyota. Let's go places. Welcome to
Speaker 1: Forward Thinking. Hey there, and welcome to Forward Thinking, the
Speaker 1: podcast that looks at the future and says we don't
Speaker 1: need no education. Yes we do. We just used a
Speaker 1: double negative. I'm Jonathan Strickland, I'm Lauren Vocal, I'm Joe McCormick.
Speaker 1: That was a good one, actually, thank you. Yeah. Once
Speaker 1: once in a while I pick one that's actually si
Speaker 1: appropriate for the podcast. Today we're gonna tell me appropriate
Speaker 1: at all for the podcast for anyway. So today we're
Speaker 1: gonna talk about science fiction and education, the future of
Speaker 1: what education might be. Uh. And the reason for this
Speaker 1: is because obviously we just did a video about what
Speaker 1: the future of education is all about, and uh, if
Speaker 1: you look to science fiction, there's some interesting concepts of
Speaker 1: what we could see as part of our educational uh
Speaker 1: experience in the future. The one that we often think of,
Speaker 1: at least here in the office, because uh, it made
Speaker 1: such a big splash when it first debuted, is the matrix, right, right,
Speaker 1: So in the concept of the matrix, you've got characters
Speaker 1: who have these these computer jacks that are built into
Speaker 1: them huge hole in the back of your head. Right
Speaker 1: right right at the top of your spine base of
Speaker 1: your skull, and you can plug in what looks to
Speaker 1: be a an inconveniently large plug into the back of
Speaker 1: your skull, and then that allows you to do a
Speaker 1: couple of things. One, it allows you to enter the matrix.
Speaker 1: This this virtual environment we plug into the the program. Yeah. See,
Speaker 1: it's so far in the future. I don't understand why
Speaker 1: they don't have wireless access to the matrix. Yeah, well,
Speaker 1: I mean clearly looks cooler. Yeah, I don't understand why
Speaker 1: they're using humans as opposed to cow I thought about it. Now.
Speaker 1: If you remember in the movie, they can kill you
Speaker 1: just by unplugging you while you're plugged in. If you
Speaker 1: had wireless access and then suddenly you had interference in
Speaker 1: the signal, I guess that would kill you. What's interfering though,
Speaker 1: it's just them, I don't know. Suddenly somebody moves a
Speaker 1: big lead sheet between you and the and the router
Speaker 1: and then you die, right right, Okay, you know what
Speaker 1: We're getting far away from what I'm trying to get
Speaker 1: at at this conversation already, and we haven't even gotten
Speaker 1: into it. The point being that in the context of
Speaker 1: the matrix. Uh. While you get plugged into this virtual environment,
Speaker 1: one of the other things that can happen is that
Speaker 1: using this connection to computers, this physical connection between the
Speaker 1: person and the computer, you can download information from a
Speaker 1: computer or have a computer upload information into you, and
Speaker 1: then use that information in a meaningful way within the
Speaker 1: context of the matrix, like piloting a ship or kung fu, yes,
Speaker 1: I know kung fu, or becoming an expert at at
Speaker 1: weapons systems, all this sort of stuff. And uh, at
Speaker 1: least within the context of the matrix, as far as
Speaker 1: I tell now, granted I have to in full disclosure,
Speaker 1: I only watched the first film, and then I tried
Speaker 1: to get through the second film twice. Second film. Yeah,
Speaker 1: that's pretty much how I am. Wouldn't it be nice
Speaker 1: if they made sequels? Yeah? At any rate, The point
Speaker 1: being that that it seemed to me that the knowledge
Speaker 1: you gained through that computer link up into your brain
Speaker 1: really was only um uh, something you could put to
Speaker 1: use within the matrix itself, right right for for most
Speaker 1: human beings. The way that it worked in the films
Speaker 1: was that you most people could could learn this thing
Speaker 1: that they would know within the confines of the matrix
Speaker 1: computer program, and then once you got back into reality, um,
Speaker 1: which was a sucky place to be, you wouldn't know
Speaker 1: it anymore, right, except they would occasionally the raves. That
Speaker 1: was the that was the one part that wasn't too sucky.
Speaker 1: That's actually not all that implausible when you think about it,
Speaker 1: because apart from the sort of like the instantaneous downloading part,
Speaker 1: it's possible to learn a virtual skill that has no
Speaker 1: correlation in the real world. Like you can be the
Speaker 1: best shot in the world at Halo, but that doesn't
Speaker 1: mean you can actually do combat and operate an assault
Speaker 1: rifle in real life. Well sure, I mean it's two
Speaker 1: different sets of skills in that case. It is just
Speaker 1: that it's at one set is mimicking something that happens
Speaker 1: in our real space, but it's not using the exact
Speaker 1: same approach. There there are correlations, though, I mean, for example,
Speaker 1: surgeons use video games these days to help train themselves
Speaker 1: to be better surgeons. Using that kind of a fine
Speaker 1: eye hand coordination training is very helpful. I guess what
Speaker 1: would be crucial in designing those kind of systems is
Speaker 1: making them as map as closely to real life as possible. Well,
Speaker 1: that and to make whatever the whatever your goal is,
Speaker 1: something that actually helps you refine whatever your skill set is.
Speaker 1: If you're talking about hand eye coordination, then it has
Speaker 1: to have lots of stuff that you can react to
Speaker 1: quickly and respond to in a in a way that
Speaker 1: makes sense within the context of the game. Now, the
Speaker 1: question is, could we get to a point where we
Speaker 1: could get that kind of skill uh through a connection
Speaker 1: direct connection to a computer automatic learning. It's called right right,
Speaker 1: this this concept of just beaming that information from a
Speaker 1: digital source into our brains and have it translate in
Speaker 1: a meaningful way. And to really understand how difficult this
Speaker 1: would be, we have to kind of look at how
Speaker 1: we learn and how we retain information within our own brains. Yeah,
Speaker 1: because in the matrix there's this it's just kind of
Speaker 1: glossed over. There's some easy transition between digital and and
Speaker 1: you know, the wet stuff in your head. They've got
Speaker 1: a hole you just plug the thing in and that
Speaker 1: that's taking care of. But in the real world, I
Speaker 1: have to imagine that our brains don't use binary data.
Speaker 1: No they do not. Yeah, No, our brains are not
Speaker 1: they don't. This is one of those things I think
Speaker 1: some futurists have trouble with and that I think some
Speaker 1: futurists believe that the human brain and computers share way
Speaker 1: more in common than they actually do. Now, there are commonalities,
Speaker 1: I mean, they're The computer is sort of our attempt
Speaker 1: to create a machine that can, in at least some contexts,
Speaker 1: reason its way through things. It has to have a
Speaker 1: very specific set of rules that has to follow in
Speaker 1: order to do that. But um, you know, it's kind
Speaker 1: of trying to mimic what we do when we're thinking
Speaker 1: about stuff using rules that we have created. But when
Speaker 1: you get down to the actual biology of the brain,
Speaker 1: it is really complex, so complex in fact, that we
Speaker 1: still don't fully understand how it works. We've got some
Speaker 1: theories or maybe we should say, some hypotheses about what
Speaker 1: is going on, but we're still learning a mystery to us. Yeah, yeah,
Speaker 1: we we can. Even with the sophisticated tools and the
Speaker 1: information that we have available to us today, we still
Speaker 1: don't fully understand the process. But I let me talk
Speaker 1: a little it about what we think is going on. Uh.
Speaker 1: And of course some of this we may find out
Speaker 1: later on is not completely correct or that it's it's right,
Speaker 1: but it's missing some key component. That's you know, that's
Speaker 1: part of the joy of discovering stuff. Really, it's something
Speaker 1: that I find exciting about all areas of science. So. Um, Really,
Speaker 1: there's three steps in the way that we store information.
Speaker 1: There's uh or the way we deal with information in
Speaker 1: our brains. There's encoding, there's storage, and there's retrieval. Now
Speaker 1: so far, that sounds a lot like computers. You know,
Speaker 1: you encode the information, you store it, and then you
Speaker 1: can retrieve it whenever you need to. Um. There are
Speaker 1: three different types basic types of memory. There's sensory memory.
Speaker 1: This is something that lasts maybe two seconds at most.
Speaker 1: This is what your brain is doing to to help
Speaker 1: you interpret the information that you're bringing in through your senses.
Speaker 1: Is it's sort of what we describe as the moment
Speaker 1: to moment ex perience of consciousness. Um. It's it's almost
Speaker 1: like when you first feel that blast of cold air
Speaker 1: and you think of it as cold. It's really the
Speaker 1: memory of cold that you're associate. It's kind of you
Speaker 1: get a little metaphysical when you can start talking. There's
Speaker 1: such a thing as the present, you know, right right, Yeah,
Speaker 1: that thing as cold and whether or not, Yeah, just
Speaker 1: just based on you know, the the idea that my
Speaker 1: green is different than your green because we've both experienced
Speaker 1: the color differently. Yeah. Uh. And then there's the lady
Speaker 1: who can experience millions of colors. You guys read about her, right,
Speaker 1: Yeah you haven't. This this is a sidebar, but it
Speaker 1: is an exciting thing. Uh. Some scientists have have identified
Speaker 1: a woman, I want to say, she's a doctor in
Speaker 1: the UK who they've identified as as being able to
Speaker 1: perceive something like one dred million different shades of color.
Speaker 1: So she's got supersensory ability when it comes to color differentiation.
Speaker 1: She cannot see outside the visible range. It's not like
Speaker 1: she suddenly has the ability to see infrared or ultra violet,
Speaker 1: but she can see incredibly subtle differences in color. Uh.
Speaker 1: The average person, it's more like one million shades. So
Speaker 1: she has one hundred times the sensitivity, which means that
Speaker 1: she must go bunkers when she's trying to pick out
Speaker 1: an outfit that matches, because things that to us would
Speaker 1: look like they match perfectly, she'd say, well, no, that's white,
Speaker 1: totally not white. That that's not the right color at all.
Speaker 1: It's like the color equivalent of how people don't like
Speaker 1: forty eight frames per second. It's just there's too much
Speaker 1: detail everything. The idea being that you could you could
Speaker 1: show someone like like me, I have terrible color recognition
Speaker 1: skills that I've taken those courses, those those those little
Speaker 1: those little tests where you're supposed to arrange the different
Speaker 1: shades from uh, you know, different the Roy G. BIV
Speaker 1: type stuff and uh, and I don't score very well
Speaker 1: at them at all. So you could show two colors
Speaker 1: to me that I might think look identical, and to her,
Speaker 1: she'd say, no, there's a world difference between them. All right,
Speaker 1: that's getting beyond the scope of this conversation, but it's cool,
Speaker 1: so I had to talk about it. So you've got
Speaker 1: sensory memory that last two seconds max. Then you have
Speaker 1: short term memory, This is more like something that lasts
Speaker 1: about thirty seconds. This is when you are trying to
Speaker 1: retain some information for just a brief moment, like someone's
Speaker 1: just told you their phone number and you're trying to
Speaker 1: put it into your phone or write it down if
Speaker 1: you still do that, and and so you just have
Speaker 1: to remember it long enough to be able to do that,
Speaker 1: and then you offload that need to remember, so your
Speaker 1: your mind doesn't have to retain that information. Um, then
Speaker 1: you have long term memory. A long term memory, of course,
Speaker 1: is when this is what we think of as when
Speaker 1: we say actual memories, like you're remembering something that happened
Speaker 1: to in your past. That's a long term memory. And
Speaker 1: the interesting thing I found was that short term memory
Speaker 1: what happens is when you encounter this new information that
Speaker 1: you're trying to remember. What is going on is that
Speaker 1: you have you have neurons in your brain, right, the
Speaker 1: neural cells, and then you have connections synapsis between the neurons. Uh.
Speaker 1: You've got about one billion neurons in your average brain,
Speaker 1: all right. Each of those neurons has about one thousand
Speaker 1: connections to other neurons, so that means that you have
Speaker 1: more than a trillion connections total in your brain. Now,
Speaker 1: a memory is actually the collection of connections between specific
Speaker 1: neurons in your brain at any given time. So, if Joe,
Speaker 1: you were to present to me some information that I
Speaker 1: was supposed to remember, uh, that first short term memory
Speaker 1: would form a connection between certain neurons and that would
Speaker 1: represent that memory, that specific uh combination of connections. If
Speaker 1: I were to make that a long term memory, it
Speaker 1: would actually be reconfiguring the those cells and those connections
Speaker 1: so that they were made a more permanent connection, and
Speaker 1: then every time I thought back on it, it would
Speaker 1: be essentially recreating what happened in that short term memory.
Speaker 1: It would it would like fire an electrical signal on
Speaker 1: a certain pattern across soup, if you could kind of
Speaker 1: it in a weird analogy. Let's say that we get
Speaker 1: a big group of people together to take a group
Speaker 1: photo and I tell everyone assume a silly pose and
Speaker 1: they all just do something spontaneous for a second, and
Speaker 1: I take a picture, and then every single day for
Speaker 1: the next month, I get everyone together, I'm like, all right,
Speaker 1: assume the same silly pose that you did before. They
Speaker 1: are trying to recreate that moment that they had before,
Speaker 1: and the more it's recreated, the stronger that memory becomes. However,
Speaker 1: just like in that analogy, you can make mistakes, right
Speaker 1: I You know, I might think, oh, yeah, I raised
Speaker 1: my left eyebrow really high in the scoofy photo, but
Speaker 1: really I raised my right eyebrow, and you're not allowed
Speaker 1: to look at the photo for reference, so you're just
Speaker 1: trying to remember this. Uh, your memory can actually be faulty,
Speaker 1: which we see all the time. Right, memory is not
Speaker 1: a completely reliable source. We think our memories are better
Speaker 1: than they are. Yeah, yeah, I mean I'm certainly that
Speaker 1: way of the conversations I have with my wife, our
Speaker 1: disagreements with who said what when, and uh, and clearly
Speaker 1: one of us has to be wrong. And I hope
Speaker 1: it's not always me, but it very well might be
Speaker 1: because my memories is not it's it's not infallible. So uh,
Speaker 1: I wish it were all right. So beyond that, we've
Speaker 1: got the these this information stored within these connections of neurons,
Speaker 1: and uh, we don't fully understand the mechanism that's going
Speaker 1: on here. We can get some we've got some general ideas.
Speaker 1: We also can't measure how big a memory is, like
Speaker 1: how much is being stored there. So for example, with
Speaker 1: with computers, you can see just by the file size, right, So,
Speaker 1: and it's it's based on you know, a number of
Speaker 1: letters of a number of characters that can be specifically
Speaker 1: break broken down into a number of ones and serious
Speaker 1: yeah yeah, essentially if you're talking about like a text file,
Speaker 1: that's exactly true. So you look at that and you say,
Speaker 1: all right, well that I know exactly how much space
Speaker 1: this is going to take in whatever recording medium I'm
Speaker 1: going to use, if it's going to be optical or
Speaker 1: magnetic or whatever. That's we can't say that with human memories. Uh.
Speaker 1: Memories are very very interesting and different things, and they
Speaker 1: change over time. Like I said, you might forget little
Speaker 1: details which could actually change quote unquote the file size
Speaker 1: of your memory. Uh. And then beyond that, you have
Speaker 1: things like association, where you can make associations between memories
Speaker 1: that don't have a direct connection with one another. So
Speaker 1: I might remember an instance I had with Lauren in
Speaker 1: an instance I had with Joe and draw connections between
Speaker 1: them even though they were too completely separate uh moments,
Speaker 1: perhaps both in time and space. So I might have
Speaker 1: run into Joe, uh, you know, in downtown Atlanta, and
Speaker 1: it might have been something that happened with me and
Speaker 1: Lauren in the office. And yet I'm able to associate things,
Speaker 1: you know, because my That's one of the cool ways
Speaker 1: that our brains work. Now, beyond all that, there's been
Speaker 1: a recent study that was was published in Nature Neuroscience
Speaker 1: where we discovered that rapid incoming data stuff that's happening
Speaker 1: very very quickly. Little second long moments of information that
Speaker 1: you're being confronted with can be stored in our brains
Speaker 1: in single neurons. Like a single neuron can actually hold
Speaker 1: a memory, but it's like a second long. And they think,
Speaker 1: the scientists think that perhaps the reason for this is
Speaker 1: so that it gives your brain a little bit of
Speaker 1: a little extra time to incorporate this and start to
Speaker 1: make a short term memory out of this blast of
Speaker 1: short information. Which is why if someone comes up and
Speaker 1: just gives you a quick list of of facts or figures,
Speaker 1: you might be able to recall a few, but you're
Speaker 1: not able to recall all of them. And some of
Speaker 1: that is because those little neurons are able to hold
Speaker 1: onto enough information for it to become meaningful to you. UH.
Speaker 1: And then there there was a team led by Professor
Speaker 1: John Gabrielli and UH he discovered that activity in a
Speaker 1: specific of the brain called the para hippocampal cortex or PHC,
Speaker 1: predicts how well people will remember a visual scene. So
Speaker 1: if using fm R I machines to to take a
Speaker 1: look at someone, um, if the activity were low, they
Speaker 1: were more likely to remember a visual scenes, so they
Speaker 1: could actually predict when people would remember more about the
Speaker 1: stuff they were going to be shown based upon their
Speaker 1: neural activity. Now, we can't do anything with that information
Speaker 1: yet other than know that this we can tell when
Speaker 1: someone is ready to learn, but we can't induce that right.
Speaker 1: So it's just one of those things where you take
Speaker 1: a look at the person's brain and you think now
Speaker 1: is when they would be most us most have to
Speaker 1: remember something visually. Now, beyond that, if we're talking about
Speaker 1: the type parts of the brain that are involved in memory, again,
Speaker 1: we don't know for sure all the different mechanisms here,
Speaker 1: but we suspect that the hippocampus and frontal cortex X
Speaker 1: work together to determine which sensory input is important to
Speaker 1: go into memory formation, so which bits of info are
Speaker 1: are vital and which are extraneous. So it may discard
Speaker 1: that you could be you could be bringing in way
Speaker 1: more information than you remember because you're parts of your
Speaker 1: brain are saying, well, that's not important, let's not record that.
Speaker 1: So you could be forgetting very important details because they
Speaker 1: just were never recorded within your memory. Um and these
Speaker 1: memories tend to be of spatial or declarative uh, types
Speaker 1: of memories. No, spatial memory is of course how things
Speaker 1: fit within a given space. Declarative are the type of
Speaker 1: memories where you can actually talk about it. You could
Speaker 1: express what you were thinking, such as, you know, when
Speaker 1: I was young, I had to walk to school uphill
Speaker 1: both ways and five ft of snow. That would be
Speaker 1: a declarative memory, as also be a lie. Uh. And
Speaker 1: then the amygdal plays a role in encoding emotionally stressful memories.
Speaker 1: And then anything that's procedural, which is learning a basic
Speaker 1: physical task or a set of steps, is probably governed
Speaker 1: by basil ganglia and the cerebellum. It's that motor memory. Uh,
Speaker 1: not just motor memory. Let's say that. Uh, let's say
Speaker 1: that Joe, you are are traveling from your home to
Speaker 1: the office. It's you learning that route to the point
Speaker 1: where you no longer really thinking about the route anymore
Speaker 1: as you drive from your home to the office. So
Speaker 1: it's it's that kind of procedure. You know, Now I
Speaker 1: take a right, Now I go two point three miles.
Speaker 1: Now I take a left. That kind of thing become
Speaker 1: so automatic people think they can do it while they're
Speaker 1: composing a long text message. Yeah, that don't do that. Uh,
Speaker 1: but anyway, that's that's the basic rundown of what we
Speaker 1: know about the human brain, and clearly there's a lot
Speaker 1: we still don't know. But when you think about that way,
Speaker 1: when you think that memories, which is really what we
Speaker 1: have to work on when we start talking about thinking
Speaker 1: and putting stuff together, um, thinking about them being not
Speaker 1: just neurons but connections makes it so much more complex
Speaker 1: that you can see. To to be able to induce
Speaker 1: information in someone is going to be challenging because it's
Speaker 1: not like you could just target a specific neuron and
Speaker 1: say it is your job to remember this fact. In fact,
Speaker 1: i'd have to imagine that most memories, um and feel
Speaker 1: free to correct me, But it seems like most would
Speaker 1: involve multiple types of memory formation at the same time.
Speaker 1: Like if I'm having a memory later today about us
Speaker 1: recording this podcast, first of all, I'm sorry, isn't it
Speaker 1: going to be composed of both? It's it's going to
Speaker 1: be images. I'm going to remember auditory cues. I'm going
Speaker 1: to remember what, you know, the paper felt like in
Speaker 1: my hands, about it? Remember how so the brain, how
Speaker 1: warm it is in this studio? Yeah, I could remember
Speaker 1: my simmering resentment of our fearless leader here. That's that's fair, Joe,
Speaker 1: I've earned that. Um yeah, you know, first of all, guys,
Speaker 1: we all really do like each other. I don't want
Speaker 1: I don't want to. I don't want that to actually
Speaker 1: be taken seriously. We would I would suspect. I would
Speaker 1: suspect that indeed, it would be several different memories all
Speaker 1: combining into one, and not just one uh over, like
Speaker 1: not just one mega memory that somehow engages all these things.
Speaker 1: But honestly, I don't know the answer, Like I couldn't
Speaker 1: tell you for sure. I would suspect it, But again
Speaker 1: that's because of what I've read already. Of course. Then again,
Speaker 1: maybe one way to think about it is that that
Speaker 1: a full experiential memory is maybe something kind of like
Speaker 1: a web page where you have like images, and you
Speaker 1: have text, and you might have music playing, and it's
Speaker 1: all different types of data, but it comes together for
Speaker 1: one when it could be very well, it could very
Speaker 1: well be when you remember something that you're leaving certain
Speaker 1: details out entirely, which would again kind of lead you
Speaker 1: to that thought of these are separate pieces to a puzzle,
Speaker 1: but you don't necessarily need the full puzzle. Okay, so
Speaker 1: what would it take to use technology to make knowledge
Speaker 1: in the brain, Like, is is it really possible? And
Speaker 1: and is there a role for technology to play in
Speaker 1: the future of education? Obviously, I would always argue that
Speaker 1: technology definitely has a role in an education. I don't
Speaker 1: I'm not one of those people who thinks that education
Speaker 1: that technology replaces the need for teachers. I'm the son
Speaker 1: of two teachers. I value teachers. I value librarians very highly.
Speaker 1: I think that they are incredibly important in the role
Speaker 1: of education. I think that technology can make their jobs
Speaker 1: easy year if it is used properly. And that's a
Speaker 1: big if, because just throwing technology at the problem is
Speaker 1: no guarantee that you're going to uh going to actually
Speaker 1: help out right, right, or maybe maybe not easier, but
Speaker 1: maybe I'm just different, more more enriched, but different. Well,
Speaker 1: one example I think we can look at right now
Speaker 1: of how technology is doing something in education that we
Speaker 1: normally can't do is stuff like personalized learning adaptive tutor software,
Speaker 1: where so imagine you have something like students are you know,
Speaker 1: elementary school students are trying to learn math alight, now
Speaker 1: they might have a really good math teacher. And I
Speaker 1: don't think that I can see anyway that technology could
Speaker 1: on the whole replace that teacher, but I can see
Speaker 1: it providing a really important individual attention that one teacher
Speaker 1: can't give a whole room of students. So you're saying like,
Speaker 1: you've got twenty five students, and as twenty five students
Speaker 1: all learn in slightly different ways and uh, and the
Speaker 1: teacher's approach might work really well for the majority of
Speaker 1: the class, but there might be other members of the
Speaker 1: class who are It's not that they're not bright, or
Speaker 1: not that they're not willing to learn, but they might
Speaker 1: absorb information better when they read it to versus or
Speaker 1: if they're watching a video about it, or they're listening
Speaker 1: to something about it rather than whatever the teacher do.
Speaker 1: You guys happen to. And there's the simple like human
Speaker 1: power issue like that the teacher does not have enough
Speaker 1: time to spend individually with each student. I can make
Speaker 1: sure that they're getting every bit of it right. I mean,
Speaker 1: if you have if you have one hour for math
Speaker 1: class and you have twenty five students, then you know,
Speaker 1: how how would you divide that up so that you
Speaker 1: would be the most effective teacher. Yeah, so imagine you
Speaker 1: have a program that that watches the students solve the problem.
Speaker 1: Like the student has a tablet or something and they're
Speaker 1: working out the problem on the tablet. This software is
Speaker 1: smart and it follows their progress, so it can see
Speaker 1: what kind of mistakes there make consistently, and it can
Speaker 1: focus attention, so like the teacher can even get feedback
Speaker 1: saying like, Okay, what you know little Johnny's having trouble
Speaker 1: with is he's forgetting to carry the one when he
Speaker 1: does an addition with multiple places or something like that.
Speaker 1: That actually I actually had more problem remembering positive and
Speaker 1: negative signs. That's actually true. Well, I mean, and it
Speaker 1: could probably figure that out too, right in a way
Speaker 1: that um that a teacher who has lots of students
Speaker 1: to deal with just probably wouldn't have time. And then
Speaker 1: the software, based on what it learns about the student,
Speaker 1: would give the student different problems or or focus its
Speaker 1: information in a different way in the future. Exactly. Yeah,
Speaker 1: it could adapt to what the student is learning and
Speaker 1: and a just expectations accordingly, which is a great idea.
Speaker 1: And of course we've seen different approaches to trying to
Speaker 1: to cater to different learning styles. You know, for example,
Speaker 1: do you guys happen to have a preference of how
Speaker 1: you learn stuff reading reading stuff? I'm definitely in the minority.
Speaker 1: I'm not very visual. I'm very auditory, So a lot
Speaker 1: of times I understand something a lot better if I
Speaker 1: hear somebody explain it to me than if I were
Speaker 1: to read the exact same words. Interesting, I'm very visual myself,
Speaker 1: so we've kind of got an interesting mix here. Um. Yeah,
Speaker 1: And and so the idea would be that this software
Speaker 1: would start to pick up on which learning methods seem
Speaker 1: to work the best with that particular student and and
Speaker 1: be able to concentrate more on catering to that knowing
Speaker 1: that these kind of learning approaches aren't always exactly the
Speaker 1: same across every subject, or even across every single day.
Speaker 1: So ideally the best kind of software would be dynamic,
Speaker 1: and that it could very in very subtle ways pick
Speaker 1: up on changes that the student is going through when
Speaker 1: they're learning and being able to to uh anticipate them
Speaker 1: and cater to those as well. Because you might learn
Speaker 1: one concept really easily one way, but you might need
Speaker 1: a different, slight different combination of ways for another concept.
Speaker 1: And so in a way you're talking about and artificially intelligent,
Speaker 1: uh proactive learning tool, which is still sort of science fictionary.
Speaker 1: I mean, we don't we haven't reached that level of
Speaker 1: sophistication with artificial intelligence, but it's within the realm of plausibility,
Speaker 1: right because we certainly have this kind of tutoring software,
Speaker 1: not exactly what Jonathan was just talking about, but we
Speaker 1: do have adaptive tutoring software right now in the real world,
Speaker 1: and it'll be interesting. I think it's early. It's still
Speaker 1: early enough days where it's hard to get a real
Speaker 1: grip on how effective it is. It's one of those
Speaker 1: things where I've definitely seen some conflicting stuff about you know,
Speaker 1: is there a measurable difference? Does it really help a
Speaker 1: student that much more than it would just going to
Speaker 1: class and paying attention to a teacher? But um, But
Speaker 1: then two things. One again, it's very early on in
Speaker 1: the technology, so we haven't had a lot of time
Speaker 1: to really examine it at work. And to being early
Speaker 1: on in the technology, it means it's not as sophisticated
Speaker 1: as it may one day be, So that's something to
Speaker 1: keep in mind. It's I think it's a promising approach
Speaker 1: to help supplement a student's education. Thinking you know, again
Speaker 1: the teachers really important here, and then this would be
Speaker 1: a great tool to help individualized where the teacher doesn't
Speaker 1: just doesn't have time right right, and allow the teacher
Speaker 1: and and also I mean even give the teacher that
Speaker 1: indication early on if a student is having problems, so
Speaker 1: that the teacher can be proactive and work with the
Speaker 1: student and say, all right, I can tell that you're
Speaker 1: not that something's not clicking here, can you. Let's let's
Speaker 1: talk about this and see if we can find a
Speaker 1: way where this makes sense to you and for them,
Speaker 1: where to help teachers refine their educational style and and
Speaker 1: cater more to what works you know, in the real world,
Speaker 1: in the real class for get that data back from
Speaker 1: the programs about where students attention is and what's really
Speaker 1: working for them and what's maybe not. Yeah, now we're
Speaker 1: looking at this from a very idealized way. If we
Speaker 1: have any teachers out there listening, first of all, we
Speaker 1: love you, and we do really appreciate the incredible work
Speaker 1: you do, especially considering that you know, some schools it
Speaker 1: can be a real challenge. Uh, so you know, it's
Speaker 1: definitely one of those things that we're thinking about as
Speaker 1: a future technology, not something like not that teachers just
Speaker 1: aren't doing their job. Nothing could be for them, absolutely not. UM,
Speaker 1: So I thought we should maybe move on to talk
Speaker 1: about what other possibilities technology could hold for the inception
Speaker 1: of knowledge and the technological supplementation. Supplementation. Sure, I'm just
Speaker 1: that word. I was just looking to make sure my
Speaker 1: top is still spinning and it is go on, okay
Speaker 1: of of knowledge and training. And I found this fascinating
Speaker 1: study about something called decoded neurofeedback. Say what decoded neurofeedback?
Speaker 1: So neurofeedback is um where data gathered about a person's
Speaker 1: brain is displayed back to the person in a certain
Speaker 1: way so the person can adapt in in some way
Speaker 1: control brain activity. Um. The uh, what I'm referring to
Speaker 1: actually is a study that is from two thousand eleven UM.
Speaker 1: It was published in Science. It's called Perceptual Learning Incepted
Speaker 1: by decoded fMRI I neurofeedback without stimulus presentation. Now, if
Speaker 1: you read about this study in lots of popular science blogs,
Speaker 1: blogs places like that, a lot of what the they
Speaker 1: touted it as like, you know, this is the matrix, right,
Speaker 1: This is where we're beaming information directly into someone's brain
Speaker 1: and they don't have to have any connection to it whatsoever,
Speaker 1: and then they're experts in it. Well, no, it's not
Speaker 1: it's not that, but it is really cool. Okay, okay,
Speaker 1: it's not beaming information into your brain. But it does
Speaker 1: represent a step in the direction of something kind of
Speaker 1: like automatic learning, like what you know, so that you
Speaker 1: can learn and practice a skill through through subtle or
Speaker 1: automatic means. And you're squinting, Did I just want to
Speaker 1: know more? Okay, I'm trying to work this out in
Speaker 1: my brain, but I need you to explain it to me. Okay,
Speaker 1: Well it started. The study started as part of this
Speaker 1: debate about um, the adult plasticity of the human brain. Sure,
Speaker 1: what what is that? What would that mean? Adult plasticity. Well,
Speaker 1: there's there's been a controversy about how certain regions of
Speaker 1: the brain can change past a certain age, and for
Speaker 1: a long time there was a belief that the visual
Speaker 1: cortex of the brain after a certain age, say maybe
Speaker 1: like a year old or something like that, just couldn't
Speaker 1: change much. It was not very plastic. This is similar
Speaker 1: to that idea that it's very easy for a child
Speaker 1: to learn another language, but it gets increasingly difficult for
Speaker 1: adults to do that. Yes, exactly, UM okay. So you've
Speaker 1: got that going on, and these people in this study
Speaker 1: decided to test, well, maybe we can cause changes in
Speaker 1: early visual areas of the brain. The early visual area
Speaker 1: is part of the visual cortex and it controls different
Speaker 1: visual processes in the brain. So one thing that people
Speaker 1: used to test this is what's called is visual perceptual
Speaker 1: learning UM, and that means like learning how to do
Speaker 1: a visual task better UM by repetition. So let's say
Speaker 1: you want to uh be able to look at um,
Speaker 1: something in a room at a fixed position and then
Speaker 1: look away and then look back. That's the example I read, UM,
Speaker 1: and be able to immediately move your eyes to where
Speaker 1: that object should um. Said that I was the one
Speaker 1: example I read. But yeah, it's stuff like that, UM okay.
Speaker 1: So the study went like this. They took some people
Speaker 1: and they put them in an fm R I machine
Speaker 1: and they had them look at a visual pattern which
Speaker 1: was it was a sort of a circle with a
Speaker 1: series of diagonal lines had different degrees of orientation. And
Speaker 1: all they did was they had the people lay in
Speaker 1: the f M r I, and it scanned the fm
Speaker 1: R I, of course scans the blood flow and your
Speaker 1: brain in real time, so it can map brain activity.
Speaker 1: And they scanned if our f m R I while
Speaker 1: people looked at these visual patterns. And then they took
Speaker 1: the people out of the machines and sent them home.
Speaker 1: Then they turned that data from the fm R I
Speaker 1: into a picture of brain activity. They said, okay, this
Speaker 1: is what it looks like when the brain is looking
Speaker 1: at these diagonal lines. All right. They brought the people
Speaker 1: back to the lab, didn't show them anything else. They said,
Speaker 1: here's a disk on a screen back in the fMRI machine.
Speaker 1: Of course, look at this disk and make it get bigger.
Speaker 1: In fact, I want to find the exact words. It's
Speaker 1: funny the quote in here is. Uh. They told them
Speaker 1: to quote somehow regulate activity in the posterior part of
Speaker 1: the brain to make the solid green disk that was
Speaker 1: presented six seconds later as large as possible. How would
Speaker 1: you do that? So imagine you're sitting there staring at
Speaker 1: a computer screen and they're telling you to look at
Speaker 1: something on the screen and make it bigger. Uh, well
Speaker 1: you have This is going to sound like that scene
Speaker 1: in Ghostbusters couple of lines UM. So the people had
Speaker 1: no idea how to do this well. It turned out
Speaker 1: there was a secret way of doing it, and the
Speaker 1: secret way was for them to reproduce the patterns in
Speaker 1: the early visual area of the brain that had existed
Speaker 1: when they were looking at the diagonal lines earlier. But
Speaker 1: they had no knowledge of this um and they were
Speaker 1: given incentives. They were given a monetary incentive too, is
Speaker 1: the bigger you can make the disc, the more more
Speaker 1: pay um. And it turned out over time training with
Speaker 1: this FMR neurofeedback, people got better at making the disc bigger.
Speaker 1: So they were essentially remembering they they were They were
Speaker 1: learning something without knowing they were learning it interesting. Interesting.
Speaker 1: The neurofeedback was teaching them to enlarge the disk by
Speaker 1: having a thought that they didn't realize was connected to
Speaker 1: the enlarging of the disk. And so one thing there
Speaker 1: was a good right up of what happened in this
Speaker 1: experiment and Discover magazine, and one thing that pointed out
Speaker 1: was that UM, so all that happened here was some
Speaker 1: diagonal lines. That was the queue, that was what generated
Speaker 1: the brain patterns that would enlarge the disk. But you
Speaker 1: could perform this same type of experiment with thing that
Speaker 1: was a lot more meaningful than diagonal lines. To say,
Speaker 1: what if the brain pattern you were looking for was
Speaker 1: associated with a task that required practice in order to
Speaker 1: like say, learning kung fu in the matrix, and you
Speaker 1: could induce mental training just by having somebody play this
Speaker 1: game with enlarging This are similar to wax on wax off.
Speaker 1: You don't know what you're doing, but you're actually learning skill.
Speaker 1: Instead of teaching muscle memory, you're teaching memory memory. Interesting.
Speaker 1: So the question here I have, and obviously this is
Speaker 1: this is very preliminary and it's not anything close to
Speaker 1: the matrix style yet. Uh. And that's you know, we
Speaker 1: don't even know that we'll ever get to a point
Speaker 1: where the matrix style will ever be at all realistic.
Speaker 1: But one other discussion I wanted to have was that
Speaker 1: this idea of it, this is something I think that
Speaker 1: that sometimes administrators and politicians kind of fallen to the
Speaker 1: trap they think about technology being the answer automatically, and
Speaker 1: they don't think about the actual application of that technology.
Speaker 1: This is why I think teachers and librarians are indispensable, really,
Speaker 1: because if you just throw assets at students, that doesn't
Speaker 1: necessarily mean that they will be meaningful or useful at all.
Speaker 1: So the example I gave was, let's say that we've
Speaker 1: even reached the point where we can just download Internet. Yeah,
Speaker 1: we can somehow impart information instantly from one source into
Speaker 1: your brain. So does that mean that you would actually
Speaker 1: quote unquote no stuff or would it just means that
Speaker 1: you have access to information now and at least, I mean,
Speaker 1: of course, without without this reality being around us. We
Speaker 1: can't say for sure because we can't actually test it,
Speaker 1: but I would suspect it would be very similar to
Speaker 1: having access to the internet. You know, on a computer
Speaker 1: or on a smartphone that I can look up the
Speaker 1: answer to any given question. But it doesn't mean that
Speaker 1: I know that answer right or you know, or being
Speaker 1: able to the difference between being able to um perform
Speaker 1: and intricate kung fu routine versus being able to say, well,
Speaker 1: in order to do that, you combine this move with
Speaker 1: this move, and this is what those moves look like. Yeah,
Speaker 1: well that's part of the first part of this is
Speaker 1: that I think knowledge is more complex than we give
Speaker 1: it credit for. Uh. And the example I was thinking
Speaker 1: about was, um, so imagine you are in the matrix
Speaker 1: world and you can just beam data directly into your brain.
Speaker 1: You could say, download a book into your brain. Say
Speaker 1: you download a Russian to English dictionary. You're an English speaker,
Speaker 1: Do you now speak Russian? I would say now. I
Speaker 1: think a simplistic understanding would say like, oh, yeah, okay,
Speaker 1: you can just download Russian to English dictionary. Bam, I
Speaker 1: know Russian. But I don't think it's that simple because
Speaker 1: I think to have fluency in Russian, there's also part
Speaker 1: of the brain that needs to have the experience of
Speaker 1: speaking it, not just to know what all the words
Speaker 1: mean right right, Well, there's there there's an element of
Speaker 1: knowing what the words mean, there's an element of knowing
Speaker 1: the syntax that the grammar, the structure of how to
Speaker 1: put those words into use, and then there's a yeah,
Speaker 1: you know, is there another dimension to it? Is there
Speaker 1: an actual practiceable thing that we could digitally reproduce or
Speaker 1: or not. I mean, and you know, we were talking
Speaker 1: about a little bit earlier, and I think that it's
Speaker 1: probably similar to the difference between UM taking a course
Speaker 1: in college, Like, for example, I took a couple of
Speaker 1: semesters of Japanese and UM so I I you know,
Speaker 1: learned the alphabets. I learned a bunch of vocabulary. I
Speaker 1: technically learned the syntax. If you asked me to speak anything,
Speaker 1: I I. The only thing I've retained from it is
Speaker 1: how to apologize for my terrible Japanese. What does that
Speaker 1: sound like? Go a nut that you don't touch my mustache?
Speaker 1: So yeah, I mean the point being that that knowledge
Speaker 1: is very complex, and then maybe if we ever do
Speaker 1: reach that point, we will be able to actually create
Speaker 1: those neural pathways, that that complex series of pathways that
Speaker 1: would allow us to not just know something, but to
Speaker 1: understand it, to comprehend it, and to be able to
Speaker 1: associate different ideas together. That's one of the amazing things
Speaker 1: I think there that we can say about the human
Speaker 1: brain is the fact that we can associate things that
Speaker 1: were not associated before and come up with new ideas
Speaker 1: and new information and innovation, things that didn't exist until
Speaker 1: we thought them up. And that you know, we can't
Speaker 1: create matter or energy, we can't destroy it either, but
Speaker 1: we can create ideas, which is kind of magical in
Speaker 1: a way. And I say magical only because we don't
Speaker 1: understand the form of science significantly advanced enough that it
Speaker 1: seems like, yeah, it's just biological science and not technology
Speaker 1: in this case, but it really is kind of amazing
Speaker 1: when you think about it. And uh, and so whether
Speaker 1: we'll ever be able to achieve the same thing technologically
Speaker 1: is another question. I think that if it is something
Speaker 1: we can do, it's pretty far off into the future
Speaker 1: because we don't understand enough about ourselves to be able
Speaker 1: to leverage it, even if the technology is sophisticate enough
Speaker 1: to do it. Uh. Although that being said, there are
Speaker 1: those who argue that if we ever reach a point
Speaker 1: where we can uh completely simulate a brain on on
Speaker 1: a meaningful scale at a meaningful time frame, it doesn't
Speaker 1: matter if we don't understand everything yet, because that thing
Speaker 1: may very well gain its own consciousness and self awareness.
Speaker 1: And the fact that we don't understand everything that's going
Speaker 1: on in our own heads doesn't mean that we won't
Speaker 1: be able to create it in some other form, which
Speaker 1: is an interesting point. But I think artificial intelligence is
Speaker 1: something we can say for another show, well what about it?
Speaker 1: Do you have anything else you want to add before
Speaker 1: we sign off? That's about all I got the overwhelming
Speaker 1: response from Joe as he just stares at me with
Speaker 1: his dead eyes tells me that it's time to conclude
Speaker 1: the episode. I was telepathically telling you that, oh got it,
Speaker 1: got it. See that's the problem is that I just
Speaker 1: was beaming the knowledge into your brain. See. The problem
Speaker 1: is outside the matrix, someone was moving a lead shield
Speaker 1: between us, and then it just bounced right off. Guys,
Speaker 1: thank you so much for listening. If you have any comments, questions,
Speaker 1: suggestions for future shows, please get in touch with us
Speaker 1: our email address. That's the word I was looking for,
Speaker 1: is FW thinking at Discovery dot com. We'll go to
Speaker 1: fw thinking dot com. That's where we have all the blogs,
Speaker 1: the podcasts, we've got the videos, and we have links
Speaker 1: to our social media so you can get in touch
Speaker 1: with us there. And until then, we say Sionara. For
Speaker 1: more on this topic and the future of technology. Is
Speaker 1: it forward thinking dot com brought to you by Toyota.
Speaker 1: Let's go places.