Episode Transcript
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Speaker 1 (00:00):
Brought to you by Toyota. Let's go places. Welcome to
Forward Thinking. Hey there, and welcome to Forward Thinking, the
podcast that looks at the future and says we don't
need no education. Yes we do. We just used a
(00:21):
double negative. I'm Jonathan Strickland, I'm Lauren Vocal, I'm Joe McCormick.
That was a good one, actually, thank you. Yeah. Once
once in a while I pick one that's actually si
appropriate for the podcast. Today we're gonna tell me appropriate
at all for the podcast for anyway. So today we're
gonna talk about science fiction and education, the future of
what education might be. Uh. And the reason for this
(00:45):
is because obviously we just did a video about what
the future of education is all about, and uh, if
you look to science fiction, there's some interesting concepts of
what we could see as part of our educational uh
experience in the future. The one that we often think of,
at least here in the office, because uh, it made
(01:06):
such a big splash when it first debuted, is the matrix, right, right,
So in the concept of the matrix, you've got characters
who have these these computer jacks that are built into
them huge hole in the back of your head. Right
right right at the top of your spine base of
your skull, and you can plug in what looks to
be a an inconveniently large plug into the back of
(01:30):
your skull, and then that allows you to do a
couple of things. One, it allows you to enter the matrix.
This this virtual environment we plug into the the program. Yeah. See,
it's so far in the future. I don't understand why
they don't have wireless access to the matrix. Yeah, well,
I mean clearly looks cooler. Yeah, I don't understand why
they're using humans as opposed to cow I thought about it. Now.
(01:52):
If you remember in the movie, they can kill you
just by unplugging you while you're plugged in. If you
had wireless access and then suddenly you had interference in
the signal, I guess that would kill you. What's interfering though,
it's just them, I don't know. Suddenly somebody moves a
big lead sheet between you and the and the router
and then you die, right right, Okay, you know what
(02:14):
We're getting far away from what I'm trying to get
at at this conversation already, and we haven't even gotten
into it. The point being that in the context of
the matrix. Uh. While you get plugged into this virtual environment,
one of the other things that can happen is that
using this connection to computers, this physical connection between the
person and the computer, you can download information from a
(02:38):
computer or have a computer upload information into you, and
then use that information in a meaningful way within the
context of the matrix, like piloting a ship or kung fu, yes,
I know kung fu, or becoming an expert at at
weapons systems, all this sort of stuff. And uh, at
least within the context of the matrix, as far as
(02:59):
I tell now, granted I have to in full disclosure,
I only watched the first film, and then I tried
to get through the second film twice. Second film. Yeah,
that's pretty much how I am. Wouldn't it be nice
if they made sequels? Yeah? At any rate, The point
being that that it seemed to me that the knowledge
you gained through that computer link up into your brain
(03:21):
really was only um uh, something you could put to
use within the matrix itself, right right for for most
human beings. The way that it worked in the films
was that you most people could could learn this thing
that they would know within the confines of the matrix
computer program, and then once you got back into reality, um,
which was a sucky place to be, you wouldn't know
(03:42):
it anymore, right, except they would occasionally the raves. That
was the that was the one part that wasn't too sucky.
That's actually not all that implausible when you think about it,
because apart from the sort of like the instantaneous downloading part,
it's possible to learn a virtual skill that has no
correlation in the real world. Like you can be the
(04:03):
best shot in the world at Halo, but that doesn't
mean you can actually do combat and operate an assault
rifle in real life. Well sure, I mean it's two
different sets of skills in that case. It is just
that it's at one set is mimicking something that happens
in our real space, but it's not using the exact
same approach. There there are correlations, though, I mean, for example,
surgeons use video games these days to help train themselves
(04:26):
to be better surgeons. Using that kind of a fine
eye hand coordination training is very helpful. I guess what
would be crucial in designing those kind of systems is
making them as map as closely to real life as possible. Well,
that and to make whatever the whatever your goal is,
something that actually helps you refine whatever your skill set is.
(04:49):
If you're talking about hand eye coordination, then it has
to have lots of stuff that you can react to
quickly and respond to in a in a way that
makes sense within the context of the game. Now, the
question is, could we get to a point where we
could get that kind of skill uh through a connection
direct connection to a computer automatic learning. It's called right right,
(05:11):
this this concept of just beaming that information from a
digital source into our brains and have it translate in
a meaningful way. And to really understand how difficult this
would be, we have to kind of look at how
we learn and how we retain information within our own brains. Yeah,
because in the matrix there's this it's just kind of
(05:35):
glossed over. There's some easy transition between digital and and
you know, the wet stuff in your head. They've got
a hole you just plug the thing in and that
that's taking care of. But in the real world, I
have to imagine that our brains don't use binary data.
No they do not. Yeah, No, our brains are not
they don't. This is one of those things I think
(05:57):
some futurists have trouble with and that I think some
futurists believe that the human brain and computers share way
more in common than they actually do. Now, there are commonalities,
I mean, they're The computer is sort of our attempt
to create a machine that can, in at least some contexts,
reason its way through things. It has to have a
(06:18):
very specific set of rules that has to follow in
order to do that. But um, you know, it's kind
of trying to mimic what we do when we're thinking
about stuff using rules that we have created. But when
you get down to the actual biology of the brain,
it is really complex, so complex in fact, that we
still don't fully understand how it works. We've got some
(06:40):
theories or maybe we should say, some hypotheses about what
is going on, but we're still learning a mystery to us. Yeah, yeah,
we we can. Even with the sophisticated tools and the
information that we have available to us today, we still
don't fully understand the process. But I let me talk
a little it about what we think is going on. Uh.
(07:03):
And of course some of this we may find out
later on is not completely correct or that it's it's right,
but it's missing some key component. That's you know, that's
part of the joy of discovering stuff. Really, it's something
that I find exciting about all areas of science. So. Um, Really,
there's three steps in the way that we store information.
(07:26):
There's uh or the way we deal with information in
our brains. There's encoding, there's storage, and there's retrieval. Now
so far, that sounds a lot like computers. You know,
you encode the information, you store it, and then you
can retrieve it whenever you need to. Um. There are
three different types basic types of memory. There's sensory memory.
This is something that lasts maybe two seconds at most.
(07:49):
This is what your brain is doing to to help
you interpret the information that you're bringing in through your senses.
Is it's sort of what we describe as the moment
to moment ex perience of consciousness. Um. It's it's almost
like when you first feel that blast of cold air
and you think of it as cold. It's really the
memory of cold that you're associate. It's kind of you
(08:12):
get a little metaphysical when you can start talking. There's
such a thing as the present, you know, right right, Yeah,
that thing as cold and whether or not, Yeah, just
just based on you know, the the idea that my
green is different than your green because we've both experienced
the color differently. Yeah. Uh. And then there's the lady
who can experience millions of colors. You guys read about her, right,
(08:33):
Yeah you haven't. This this is a sidebar, but it
is an exciting thing. Uh. Some scientists have have identified
a woman, I want to say, she's a doctor in
the UK who they've identified as as being able to
perceive something like one dred million different shades of color.
So she's got supersensory ability when it comes to color differentiation.
(08:54):
She cannot see outside the visible range. It's not like
she suddenly has the ability to see infrared or ultra violet,
but she can see incredibly subtle differences in color. Uh.
The average person, it's more like one million shades. So
she has one hundred times the sensitivity, which means that
she must go bunkers when she's trying to pick out
an outfit that matches, because things that to us would
(09:17):
look like they match perfectly, she'd say, well, no, that's white,
totally not white. That that's not the right color at all.
It's like the color equivalent of how people don't like
forty eight frames per second. It's just there's too much
detail everything. The idea being that you could you could
show someone like like me, I have terrible color recognition
(09:38):
skills that I've taken those courses, those those those little
those little tests where you're supposed to arrange the different
shades from uh, you know, different the Roy G. BIV
type stuff and uh, and I don't score very well
at them at all. So you could show two colors
to me that I might think look identical, and to her,
she'd say, no, there's a world difference between them. All right,
(09:59):
that's getting beyond the scope of this conversation, but it's cool,
so I had to talk about it. So you've got
sensory memory that last two seconds max. Then you have
short term memory, This is more like something that lasts
about thirty seconds. This is when you are trying to
retain some information for just a brief moment, like someone's
just told you their phone number and you're trying to
put it into your phone or write it down if
(10:19):
you still do that, and and so you just have
to remember it long enough to be able to do that,
and then you offload that need to remember, so your
your mind doesn't have to retain that information. Um, then
you have long term memory. A long term memory, of course,
is when this is what we think of as when
we say actual memories, like you're remembering something that happened
to in your past. That's a long term memory. And
(10:42):
the interesting thing I found was that short term memory
what happens is when you encounter this new information that
you're trying to remember. What is going on is that
you have you have neurons in your brain, right, the
neural cells, and then you have connections synapsis between the neurons. Uh.
You've got about one billion neurons in your average brain,
(11:03):
all right. Each of those neurons has about one thousand
connections to other neurons, so that means that you have
more than a trillion connections total in your brain. Now,
a memory is actually the collection of connections between specific
neurons in your brain at any given time. So, if Joe,
(11:25):
you were to present to me some information that I
was supposed to remember, uh, that first short term memory
would form a connection between certain neurons and that would
represent that memory, that specific uh combination of connections. If
I were to make that a long term memory, it
would actually be reconfiguring the those cells and those connections
(11:46):
so that they were made a more permanent connection, and
then every time I thought back on it, it would
be essentially recreating what happened in that short term memory.
It would it would like fire an electrical signal on
a certain pattern across soup, if you could kind of
it in a weird analogy. Let's say that we get
a big group of people together to take a group
photo and I tell everyone assume a silly pose and
(12:09):
they all just do something spontaneous for a second, and
I take a picture, and then every single day for
the next month, I get everyone together, I'm like, all right,
assume the same silly pose that you did before. They
are trying to recreate that moment that they had before,
and the more it's recreated, the stronger that memory becomes. However,
just like in that analogy, you can make mistakes, right
(12:32):
I You know, I might think, oh, yeah, I raised
my left eyebrow really high in the scoofy photo, but
really I raised my right eyebrow, and you're not allowed
to look at the photo for reference, so you're just
trying to remember this. Uh, your memory can actually be faulty,
which we see all the time. Right, memory is not
a completely reliable source. We think our memories are better
than they are. Yeah, yeah, I mean I'm certainly that
(12:54):
way of the conversations I have with my wife, our
disagreements with who said what when, and uh, and clearly
one of us has to be wrong. And I hope
it's not always me, but it very well might be
because my memories is not it's it's not infallible. So uh,
I wish it were all right. So beyond that, we've
(13:17):
got the these this information stored within these connections of neurons,
and uh, we don't fully understand the mechanism that's going
on here. We can get some we've got some general ideas.
We also can't measure how big a memory is, like
how much is being stored there. So for example, with
(13:37):
with computers, you can see just by the file size, right, So,
and it's it's based on you know, a number of
letters of a number of characters that can be specifically
break broken down into a number of ones and serious
yeah yeah, essentially if you're talking about like a text file,
that's exactly true. So you look at that and you say,
all right, well that I know exactly how much space
(13:58):
this is going to take in whatever recording medium I'm
going to use, if it's going to be optical or
magnetic or whatever. That's we can't say that with human memories. Uh.
Memories are very very interesting and different things, and they
change over time. Like I said, you might forget little
details which could actually change quote unquote the file size
of your memory. Uh. And then beyond that, you have
(14:19):
things like association, where you can make associations between memories
that don't have a direct connection with one another. So
I might remember an instance I had with Lauren in
an instance I had with Joe and draw connections between
them even though they were too completely separate uh moments,
perhaps both in time and space. So I might have
run into Joe, uh, you know, in downtown Atlanta, and
(14:42):
it might have been something that happened with me and
Lauren in the office. And yet I'm able to associate things,
you know, because my That's one of the cool ways
that our brains work. Now, beyond all that, there's been
a recent study that was was published in Nature Neuroscience
where we discovered that rapid incoming data stuff that's happening
(15:03):
very very quickly. Little second long moments of information that
you're being confronted with can be stored in our brains
in single neurons. Like a single neuron can actually hold
a memory, but it's like a second long. And they think,
the scientists think that perhaps the reason for this is
so that it gives your brain a little bit of
(15:25):
a little extra time to incorporate this and start to
make a short term memory out of this blast of
short information. Which is why if someone comes up and
just gives you a quick list of of facts or figures,
you might be able to recall a few, but you're
not able to recall all of them. And some of
that is because those little neurons are able to hold
(15:46):
onto enough information for it to become meaningful to you. UH.
And then there there was a team led by Professor
John Gabrielli and UH he discovered that activity in a
specific of the brain called the para hippocampal cortex or PHC,
predicts how well people will remember a visual scene. So
(16:10):
if using fm R I machines to to take a
look at someone, um, if the activity were low, they
were more likely to remember a visual scenes, so they
could actually predict when people would remember more about the
stuff they were going to be shown based upon their
neural activity. Now, we can't do anything with that information
yet other than know that this we can tell when
(16:32):
someone is ready to learn, but we can't induce that right.
So it's just one of those things where you take
a look at the person's brain and you think now
is when they would be most us most have to
remember something visually. Now, beyond that, if we're talking about
the type parts of the brain that are involved in memory, again,
we don't know for sure all the different mechanisms here,
(16:57):
but we suspect that the hippocampus and frontal cortex X
work together to determine which sensory input is important to
go into memory formation, so which bits of info are
are vital and which are extraneous. So it may discard
that you could be you could be bringing in way
(17:17):
more information than you remember because you're parts of your
brain are saying, well, that's not important, let's not record that.
So you could be forgetting very important details because they
just were never recorded within your memory. Um and these
memories tend to be of spatial or declarative uh, types
of memories. No, spatial memory is of course how things
(17:39):
fit within a given space. Declarative are the type of
memories where you can actually talk about it. You could
express what you were thinking, such as, you know, when
I was young, I had to walk to school uphill
both ways and five ft of snow. That would be
a declarative memory, as also be a lie. Uh. And
then the amygdal plays a role in encoding emotionally stressful memories.
(18:04):
And then anything that's procedural, which is learning a basic
physical task or a set of steps, is probably governed
by basil ganglia and the cerebellum. It's that motor memory. Uh,
not just motor memory. Let's say that. Uh, let's say
that Joe, you are are traveling from your home to
(18:25):
the office. It's you learning that route to the point
where you no longer really thinking about the route anymore
as you drive from your home to the office. So
it's it's that kind of procedure. You know, Now I
take a right, Now I go two point three miles.
Now I take a left. That kind of thing become
(18:46):
so automatic people think they can do it while they're
composing a long text message. Yeah, that don't do that. Uh,
but anyway, that's that's the basic rundown of what we
know about the human brain, and clearly there's a lot
we still don't know. But when you think about that way,
when you think that memories, which is really what we
have to work on when we start talking about thinking
(19:08):
and putting stuff together, um, thinking about them being not
just neurons but connections makes it so much more complex
that you can see. To to be able to induce
information in someone is going to be challenging because it's
not like you could just target a specific neuron and
say it is your job to remember this fact. In fact,
(19:31):
i'd have to imagine that most memories, um and feel
free to correct me, But it seems like most would
involve multiple types of memory formation at the same time.
Like if I'm having a memory later today about us
recording this podcast, first of all, I'm sorry, isn't it
going to be composed of both? It's it's going to
be images. I'm going to remember auditory cues. I'm going
(19:54):
to remember what, you know, the paper felt like in
my hands, about it? Remember how so the brain, how
warm it is in this studio? Yeah, I could remember
my simmering resentment of our fearless leader here. That's that's fair, Joe,
I've earned that. Um yeah, you know, first of all, guys,
we all really do like each other. I don't want
(20:16):
I don't want to. I don't want that to actually
be taken seriously. We would I would suspect. I would
suspect that indeed, it would be several different memories all
combining into one, and not just one uh over, like
not just one mega memory that somehow engages all these things.
But honestly, I don't know the answer, Like I couldn't
(20:37):
tell you for sure. I would suspect it, But again
that's because of what I've read already. Of course. Then again,
maybe one way to think about it is that that
a full experiential memory is maybe something kind of like
a web page where you have like images, and you
have text, and you might have music playing, and it's
all different types of data, but it comes together for
(20:59):
one when it could be very well, it could very
well be when you remember something that you're leaving certain
details out entirely, which would again kind of lead you
to that thought of these are separate pieces to a puzzle,
but you don't necessarily need the full puzzle. Okay, so
what would it take to use technology to make knowledge
(21:25):
in the brain, Like, is is it really possible? And
and is there a role for technology to play in
the future of education? Obviously, I would always argue that
technology definitely has a role in an education. I don't
I'm not one of those people who thinks that education
that technology replaces the need for teachers. I'm the son
(21:46):
of two teachers. I value teachers. I value librarians very highly.
I think that they are incredibly important in the role
of education. I think that technology can make their jobs
easy year if it is used properly. And that's a
big if, because just throwing technology at the problem is
(22:06):
no guarantee that you're going to uh going to actually
help out right, right, or maybe maybe not easier, but
maybe I'm just different, more more enriched, but different. Well,
one example I think we can look at right now
of how technology is doing something in education that we
normally can't do is stuff like personalized learning adaptive tutor software,
(22:30):
where so imagine you have something like students are you know,
elementary school students are trying to learn math alight, now
they might have a really good math teacher. And I
don't think that I can see anyway that technology could
on the whole replace that teacher, but I can see
it providing a really important individual attention that one teacher
(22:55):
can't give a whole room of students. So you're saying like,
you've got twenty five students, and as twenty five students
all learn in slightly different ways and uh, and the
teacher's approach might work really well for the majority of
the class, but there might be other members of the
class who are It's not that they're not bright, or
not that they're not willing to learn, but they might
(23:15):
absorb information better when they read it to versus or
if they're watching a video about it, or they're listening
to something about it rather than whatever the teacher do.
You guys happen to. And there's the simple like human
power issue like that the teacher does not have enough
time to spend individually with each student. I can make
sure that they're getting every bit of it right. I mean,
(23:36):
if you have if you have one hour for math
class and you have twenty five students, then you know,
how how would you divide that up so that you
would be the most effective teacher. Yeah, so imagine you
have a program that that watches the students solve the problem.
Like the student has a tablet or something and they're
working out the problem on the tablet. This software is
smart and it follows their progress, so it can see
(23:58):
what kind of mistakes there make consistently, and it can
focus attention, so like the teacher can even get feedback
saying like, Okay, what you know little Johnny's having trouble
with is he's forgetting to carry the one when he
does an addition with multiple places or something like that.
That actually I actually had more problem remembering positive and
negative signs. That's actually true. Well, I mean, and it
(24:21):
could probably figure that out too, right in a way
that um that a teacher who has lots of students
to deal with just probably wouldn't have time. And then
the software, based on what it learns about the student,
would give the student different problems or or focus its
information in a different way in the future. Exactly. Yeah,
it could adapt to what the student is learning and
(24:42):
and a just expectations accordingly, which is a great idea.
And of course we've seen different approaches to trying to
to cater to different learning styles. You know, for example,
do you guys happen to have a preference of how
you learn stuff reading reading stuff? I'm definitely in the minority.
(25:03):
I'm not very visual. I'm very auditory, So a lot
of times I understand something a lot better if I
hear somebody explain it to me than if I were
to read the exact same words. Interesting, I'm very visual myself,
so we've kind of got an interesting mix here. Um. Yeah,
And and so the idea would be that this software
would start to pick up on which learning methods seem
(25:26):
to work the best with that particular student and and
be able to concentrate more on catering to that knowing
that these kind of learning approaches aren't always exactly the
same across every subject, or even across every single day.
So ideally the best kind of software would be dynamic,
(25:48):
and that it could very in very subtle ways pick
up on changes that the student is going through when
they're learning and being able to to uh anticipate them
and cater to those as well. Because you might learn
one concept really easily one way, but you might need
a different, slight different combination of ways for another concept.
(26:09):
And so in a way you're talking about and artificially intelligent,
uh proactive learning tool, which is still sort of science fictionary.
I mean, we don't we haven't reached that level of
sophistication with artificial intelligence, but it's within the realm of plausibility,
right because we certainly have this kind of tutoring software,
not exactly what Jonathan was just talking about, but we
(26:31):
do have adaptive tutoring software right now in the real world,
and it'll be interesting. I think it's early. It's still
early enough days where it's hard to get a real
grip on how effective it is. It's one of those
things where I've definitely seen some conflicting stuff about you know,
is there a measurable difference? Does it really help a
(26:53):
student that much more than it would just going to
class and paying attention to a teacher? But um, But
then two things. One again, it's very early on in
the technology, so we haven't had a lot of time
to really examine it at work. And to being early
on in the technology, it means it's not as sophisticated
as it may one day be, So that's something to
(27:15):
keep in mind. It's I think it's a promising approach
to help supplement a student's education. Thinking you know, again
the teachers really important here, and then this would be
a great tool to help individualized where the teacher doesn't
just doesn't have time right right, and allow the teacher
and and also I mean even give the teacher that
(27:35):
indication early on if a student is having problems, so
that the teacher can be proactive and work with the
student and say, all right, I can tell that you're
not that something's not clicking here, can you. Let's let's
talk about this and see if we can find a
way where this makes sense to you and for them,
where to help teachers refine their educational style and and
cater more to what works you know, in the real world,
(27:59):
in the real class for get that data back from
the programs about where students attention is and what's really
working for them and what's maybe not. Yeah, now we're
looking at this from a very idealized way. If we
have any teachers out there listening, first of all, we
love you, and we do really appreciate the incredible work
you do, especially considering that you know, some schools it
(28:19):
can be a real challenge. Uh, so you know, it's
definitely one of those things that we're thinking about as
a future technology, not something like not that teachers just
aren't doing their job. Nothing could be for them, absolutely not. UM,
So I thought we should maybe move on to talk
about what other possibilities technology could hold for the inception
(28:41):
of knowledge and the technological supplementation. Supplementation. Sure, I'm just
that word. I was just looking to make sure my
top is still spinning and it is go on, okay
of of knowledge and training. And I found this fascinating
study about something called decoded neurofeedback. Say what decoded neurofeedback?
(29:08):
So neurofeedback is um where data gathered about a person's
brain is displayed back to the person in a certain
way so the person can adapt in in some way
control brain activity. Um. The uh, what I'm referring to
actually is a study that is from two thousand eleven UM.
(29:30):
It was published in Science. It's called Perceptual Learning Incepted
by decoded fMRI I neurofeedback without stimulus presentation. Now, if
you read about this study in lots of popular science blogs,
blogs places like that, a lot of what the they
touted it as like, you know, this is the matrix, right,
(29:51):
This is where we're beaming information directly into someone's brain
and they don't have to have any connection to it whatsoever,
and then they're experts in it. Well, no, it's not
it's not that, but it is really cool. Okay, okay,
it's not beaming information into your brain. But it does
represent a step in the direction of something kind of
like automatic learning, like what you know, so that you
(30:14):
can learn and practice a skill through through subtle or
automatic means. And you're squinting, Did I just want to
know more? Okay, I'm trying to work this out in
my brain, but I need you to explain it to me. Okay,
Well it started. The study started as part of this
(30:34):
debate about um, the adult plasticity of the human brain. Sure,
what what is that? What would that mean? Adult plasticity. Well,
there's there's been a controversy about how certain regions of
the brain can change past a certain age, and for
a long time there was a belief that the visual
cortex of the brain after a certain age, say maybe
(30:54):
like a year old or something like that, just couldn't
change much. It was not very plastic. This is similar
to that idea that it's very easy for a child
to learn another language, but it gets increasingly difficult for
adults to do that. Yes, exactly, UM okay. So you've
got that going on, and these people in this study
(31:15):
decided to test, well, maybe we can cause changes in
early visual areas of the brain. The early visual area
is part of the visual cortex and it controls different
visual processes in the brain. So one thing that people
used to test this is what's called is visual perceptual
learning UM, and that means like learning how to do
(31:37):
a visual task better UM by repetition. So let's say
you want to uh be able to look at um,
something in a room at a fixed position and then
look away and then look back. That's the example I read, UM,
and be able to immediately move your eyes to where
that object should um. Said that I was the one
(32:00):
example I read. But yeah, it's stuff like that, UM okay.
So the study went like this. They took some people
and they put them in an fm R I machine
and they had them look at a visual pattern which
was it was a sort of a circle with a
series of diagonal lines had different degrees of orientation. And
(32:21):
all they did was they had the people lay in
the f M r I, and it scanned the fm
R I, of course scans the blood flow and your
brain in real time, so it can map brain activity.
And they scanned if our f m R I while
people looked at these visual patterns. And then they took
the people out of the machines and sent them home.
Then they turned that data from the fm R I
(32:45):
into a picture of brain activity. They said, okay, this
is what it looks like when the brain is looking
at these diagonal lines. All right. They brought the people
back to the lab, didn't show them anything else. They said,
here's a disk on a screen back in the fMRI machine.
Of course, look at this disk and make it get bigger.
(33:08):
In fact, I want to find the exact words. It's
funny the quote in here is. Uh. They told them
to quote somehow regulate activity in the posterior part of
the brain to make the solid green disk that was
presented six seconds later as large as possible. How would
you do that? So imagine you're sitting there staring at
(33:28):
a computer screen and they're telling you to look at
something on the screen and make it bigger. Uh, well
you have This is going to sound like that scene
in Ghostbusters couple of lines UM. So the people had
no idea how to do this well. It turned out
there was a secret way of doing it, and the
(33:49):
secret way was for them to reproduce the patterns in
the early visual area of the brain that had existed
when they were looking at the diagonal lines earlier. But
they had no knowledge of this um and they were
given incentives. They were given a monetary incentive too, is
the bigger you can make the disc, the more more
pay um. And it turned out over time training with
(34:13):
this FMR neurofeedback, people got better at making the disc bigger.
So they were essentially remembering they they were They were
learning something without knowing they were learning it interesting. Interesting.
The neurofeedback was teaching them to enlarge the disk by
having a thought that they didn't realize was connected to
(34:35):
the enlarging of the disk. And so one thing there
was a good right up of what happened in this
experiment and Discover magazine, and one thing that pointed out
was that UM, so all that happened here was some
diagonal lines. That was the queue, that was what generated
the brain patterns that would enlarge the disk. But you
(34:57):
could perform this same type of experiment with thing that
was a lot more meaningful than diagonal lines. To say,
what if the brain pattern you were looking for was
associated with a task that required practice in order to
like say, learning kung fu in the matrix, and you
could induce mental training just by having somebody play this
(35:21):
game with enlarging This are similar to wax on wax off.
You don't know what you're doing, but you're actually learning skill.
Instead of teaching muscle memory, you're teaching memory memory. Interesting.
So the question here I have, and obviously this is
this is very preliminary and it's not anything close to
the matrix style yet. Uh. And that's you know, we
(35:44):
don't even know that we'll ever get to a point
where the matrix style will ever be at all realistic.
But one other discussion I wanted to have was that
this idea of it, this is something I think that
that sometimes administrators and politicians kind of fallen to the
trap they think about technology being the answer automatically, and
(36:05):
they don't think about the actual application of that technology.
This is why I think teachers and librarians are indispensable, really,
because if you just throw assets at students, that doesn't
necessarily mean that they will be meaningful or useful at all.
So the example I gave was, let's say that we've
even reached the point where we can just download Internet. Yeah,
(36:27):
we can somehow impart information instantly from one source into
your brain. So does that mean that you would actually
quote unquote no stuff or would it just means that
you have access to information now and at least, I mean,
of course, without without this reality being around us. We
can't say for sure because we can't actually test it,
but I would suspect it would be very similar to
(36:49):
having access to the internet. You know, on a computer
or on a smartphone that I can look up the
answer to any given question. But it doesn't mean that
I know that answer right or you know, or being
able to the difference between being able to um perform
and intricate kung fu routine versus being able to say, well,
in order to do that, you combine this move with
(37:11):
this move, and this is what those moves look like. Yeah,
well that's part of the first part of this is
that I think knowledge is more complex than we give
it credit for. Uh. And the example I was thinking
about was, um, so imagine you are in the matrix
world and you can just beam data directly into your brain.
You could say, download a book into your brain. Say
(37:35):
you download a Russian to English dictionary. You're an English speaker,
Do you now speak Russian? I would say now. I
think a simplistic understanding would say like, oh, yeah, okay,
you can just download Russian to English dictionary. Bam, I
know Russian. But I don't think it's that simple because
(37:55):
I think to have fluency in Russian, there's also part
of the brain that needs to have the experience of
speaking it, not just to know what all the words
mean right right, Well, there's there there's an element of
knowing what the words mean, there's an element of knowing
the syntax that the grammar, the structure of how to
put those words into use, and then there's a yeah,
(38:16):
you know, is there another dimension to it? Is there
an actual practiceable thing that we could digitally reproduce or
or not. I mean, and you know, we were talking
about a little bit earlier, and I think that it's
probably similar to the difference between UM taking a course
in college, Like, for example, I took a couple of
semesters of Japanese and UM so I I you know,
(38:37):
learned the alphabets. I learned a bunch of vocabulary. I
technically learned the syntax. If you asked me to speak anything,
I I. The only thing I've retained from it is
how to apologize for my terrible Japanese. What does that
sound like? Go a nut that you don't touch my mustache?
(38:57):
So yeah, I mean the point being that that knowledge
is very complex, and then maybe if we ever do
reach that point, we will be able to actually create
those neural pathways, that that complex series of pathways that
would allow us to not just know something, but to
understand it, to comprehend it, and to be able to
(39:20):
associate different ideas together. That's one of the amazing things
I think there that we can say about the human
brain is the fact that we can associate things that
were not associated before and come up with new ideas
and new information and innovation, things that didn't exist until
we thought them up. And that you know, we can't
(39:40):
create matter or energy, we can't destroy it either, but
we can create ideas, which is kind of magical in
a way. And I say magical only because we don't
understand the form of science significantly advanced enough that it
seems like, yeah, it's just biological science and not technology
in this case, but it really is kind of amazing
(40:01):
when you think about it. And uh, and so whether
we'll ever be able to achieve the same thing technologically
is another question. I think that if it is something
we can do, it's pretty far off into the future
because we don't understand enough about ourselves to be able
to leverage it, even if the technology is sophisticate enough
(40:24):
to do it. Uh. Although that being said, there are
those who argue that if we ever reach a point
where we can uh completely simulate a brain on on
a meaningful scale at a meaningful time frame, it doesn't
matter if we don't understand everything yet, because that thing
may very well gain its own consciousness and self awareness.
(40:44):
And the fact that we don't understand everything that's going
on in our own heads doesn't mean that we won't
be able to create it in some other form, which
is an interesting point. But I think artificial intelligence is
something we can say for another show, well what about it?
Do you have anything else you want to add before
we sign off? That's about all I got the overwhelming
response from Joe as he just stares at me with
(41:06):
his dead eyes tells me that it's time to conclude
the episode. I was telepathically telling you that, oh got it,
got it. See that's the problem is that I just
was beaming the knowledge into your brain. See. The problem
is outside the matrix, someone was moving a lead shield
between us, and then it just bounced right off. Guys,
thank you so much for listening. If you have any comments, questions,
suggestions for future shows, please get in touch with us
(41:27):
our email address. That's the word I was looking for,
is FW thinking at Discovery dot com. We'll go to
fw thinking dot com. That's where we have all the blogs,
the podcasts, we've got the videos, and we have links
to our social media so you can get in touch
with us there. And until then, we say Sionara. For
(41:47):
more on this topic and the future of technology. Is
it forward thinking dot com brought to you by Toyota.
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