January 17, 2012 • 34 mins
The Magic Eight Ball of Your Existence: Imagine a computer model of the entire world, one on which world leaders can test their decisions and gauge the ripple effect of their actions. Is such a simulation possible? In this episode, Robert and Julie discuss plans for a Living Earth Simulator.
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Episode Transcript
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Speaker 1 (00:03):
Welcome to Stuff to Blow your Mind from how Stuff
Works dot com. Hey, welcome to Stuff to Blow your Mind.
My name is Robert Lamb and Julie Douglas. Julie, you know,
making decisions in this world can be really taxing. We've
discussed that before. Even the smallest decisions in life are
(00:24):
often difficult to make. But put yourself in the in
the boots in the gold studied jewel encrusted boots of
a king or or an Elvis, somebody who's whose decisions
are are are sweeping that change the escape of international
politics and economics. We're talking about huge ripple effect globally, globally,
(00:48):
huge political leaders, leaders of multinational companies, policymakers, The decisions
that they make UH can have catastrophic effects. They can
they can change the world for the better for the worst.
So in UH, in ancient times, you know, you would
have the emperor and he would have like a sourcerer
or a diviner there too. I was gonna say, an
(01:08):
oracle or an oracle, you know, there would be some
sort of magical go to man to bounce these ideas
off of and be like, hey, I'm trying to figure
out what to do about this. I don't know this
protest situation in the streets, um, but I'm not really
sure what to do. Can you look into your magic
pool of water and see what the future is going
to be, um, and tell me what I should do? Now?
(01:32):
Of course, there's no such thing as magic. There is,
so I'm sorry atually to tell me that my fortune
cookies are full of bunk, except the ones where the
fortune is general advice. But but we we love the
idea of being able to do that. Mainly we want
to we want to test our assumptions about what should
be done versus the outcome of those assumptions in the
(01:53):
real world. So what you're saying is that if leaders
had some sort of magic ball, right that they could
ask a question of and it could it actually spit
out an answer that was valid, we could uh really
manage our lives on a global scale in the much cleaner,
better way. That's the idea. But of course, to power
(02:15):
that magic eight ball, you would need some pretty intense
computer technology, and you would you would basically have to
have a computer model of everything under there. Uh. And
in the same day, in our attempts to understand global
climate UH, and just not even global climate, just local
weather to find out whether whether we should have a
picnic tomorrow. Can I plan on mo in my yard?
(02:35):
Should I would bring a raincoat with me to the
to the train station, that kind of thing. We depend
on these these climate models, which UHL is we've discussed
in the past. Creating an an accurate climate model is
very difficult. There's so many factors involved. It's a it's
largely chaotic system, and it's it's difficult to judge. Like
every every day that you're into the future that you look,
(02:57):
the more flawed the model becomes. But but still we
we depend on the community computer models for for our
understanding of what the weather is going to be. And
if conceivably, if we created a complex enough computer model,
could we not have a a kind of simulation of
the world in which to test our ideas. So you
(03:19):
would have this politician or this policymaker somewhere in a
position of power, gold stilettos, and she's thinking to herself,
what should I do? Should I enact this policy or
this policy? Well, bring me the magic eight ball and
I will ask it in the magic eight ball will
then run two scenarios in the in its simulation of
the world, one in which policy A is enacted and
(03:40):
one in which policy B is enacted. Okay, but this
magic eight ball would have to aggregate data of our
entire existence, right, so we're talking about the economic existence,
are social um existence, the geographical existence um, you know,
the physics of our existence. All of this, uh, would
have to be something that we could get our arms around,
(04:02):
all this data, right, and and and then we have
to have a name for this, all this data. We
call it big data. Big data name for it. And
it's kind of like imagine, like the way I was
kind of thinking, because I'm writing about some related issues
here for work, so I've been been researching, and the
way I tend to think of it is imagine, imagine
like this this field, all right, this flat plane, right,
(04:25):
what's not completely flat. There's some slight bumps in it
enough to where you have numerous puddles of water, and
then it starts raining, right, those puddles get bigger and
bigger until those puddles all meet and then you have
like a giant lake. And so that's the kind of Uh,
that's how I like I end up imagining big data
because every day we create an estimated two point five
(04:47):
quin trillion bytes of data. So to the point of
the data in the world today has been created in
the last two years alone. And when I say big data,
like this is all these little puddles of data that
form this giant lake of big day. We're talking about
everything we'll climate sensors, to your to everyone's Facebook and
Twitter updates, to digital text, digital video and picture upload.
(05:10):
Stuff you're putting on Flicker, stuff you're putting on YouTube
to just to show visions of the world, ideas about
what the world is doing, online transaction records, cell phone
GPS signals, all of it is coming together into this
big picture of big data, right and right now it's
chaos to us, right, I mean, this is not something
that we've tried to manage before to get a picture
(05:30):
of what our lives look like using all of this
big data, although some people, some institutions have tried to
do it at a smaller scale, like NASA. Right, it's
kind of like imagine the dude or a lady who
starts just picking up buying a book every day and
doesn't doesn't have any kind of accurate library system going
in their house. They just bring a book or to home.
They maybe they read a little bit of one, they
(05:51):
throw on here, throw on here. Eventually they have an
entire house just filled with books. But they have no
system of organization to understand how many books they have,
how their selection in one category stacks up against another,
or even kind of like just a general idea of
what kind of books they like. Um. So we were
in this household of big data where data is just everywhere,
(06:11):
on everything, but we we tend to lack a complete
picture of what that data is telling us. What we're
getting to is that there is actually in the works
a a proposal and an enactment of this idea. It's
a billion a half dollar idea computing system to actually
try to wrangle all of this data. Right. It all
(06:34):
falls under the this project known as UH Future I
C T, which is really three parts. There's a planetary
nervous system and the idea here is you would um,
it's like a global sensor network throwing in all sorts
of socio economic, environmental, technological data from around the world. Again,
like the big day of the big data in the
world is from the last two years. Although there it's
(06:56):
the the timiness of this data as it's rolling in.
So if you put up enough, put up enough sensors,
you you hooked into enough existing data networks, you would
have like a real time picture of what is happening
in the world and all these different spheres. Okay, and
the guy who is heading it all up is dirt helping.
He's the Scientific Coordinator of the Future i c T.
(07:16):
Which is that what you're talking about, this large scale
European research program to explore and manage our future. And
he's talking about the necessity to understand complex global, socially
interactive systems. He's saying that we live in a global
world and this requires new tools. Yeah, and uh, if
i'm engine the first tool the planetary nervous system. Another tool,
(07:37):
which we'll get into later, is the Global Participatory Platform,
which you can think of in a way sort of
like this the the interactive aspect of this project. But
then the really core thing, the thing that we're going
to talk in detail about here is the Living Earth simulator.
And this is exactly what we were talking about, the
engine that would drive this imaginary eight ball magic eight ball.
(07:59):
I love this idea because to me it seems like
a souped up second life. Yeah, where it's or it's
you can't help. But even though it's it's probably not
kosher to really talk about the matrix anymore after the
last two films, but it sounds very matrix like the
idea that here is here, there's a simulated world where
we would we would bring in all this data to
create a model of the world on which we can
(08:19):
test possible choices. Well, and have you ever seen Google's
Liquid Earth. I don't think I have. It's really cool.
It's a it's actually created as like someone's project over
at Google. So the Skuy's time, he decided to dedicate
to the Google Earth model that they have, you know
that consuming on the cities, and he created this highly
immersive program has eight panels surrounding you. She almost feel
(08:42):
like you're in a video game. And the idea I
think is that you know, you can zoom in and
out and you can see the taj Mahal and you
can see all the details. Um So when I think
about this Earth simulator, this Living Earth simulator, I think
about this sort of immersive situation and where you can
be on a city street, you can zoom in and
(09:03):
you'll have all of this data overlaid on top of
it real time, right, And again, real time is key
when we're talking about all this data. Um so Dr
Dirk Um, Dr Dirk, Dr Dirk he Um. He's very
expressive about all of this. He makes the point that
in the past, we we didn't really have the data
to come up with a systemic science of how our
(09:25):
society works. But now we have this data, right, and
of course who could have conceived of it right? Right? Right?
Who could have conceived of it in the past. And
he's saying it's it's necessary to keep up with globalization,
technological change. You have all these systems like smashing into
each other. In fact, he often refers to the living
or simulator is a knowledge collider. The idea that you
would take all this data and in the same way
(09:45):
that the the large hypn collider is is slamming particles
together to try to understand how the universe works. This
is about like slamming all this information together and seeing
what happens. Which I like this idea because although I
will say that it doesn't sound like it's going to
be quite that dynamic, because this is this is predictive
modeling that we're talking about, and as and as we
(10:06):
discussed in the weather example, predictive modeling is uh imperfect
at best. Uh. There there are various arguments about what
can be done with computer modeling of of complex systems.
There are plenty of arguments that state that you cannot
form a perfect model of a complex system that you're
you're never gonna be able to to really get down
(10:27):
into the exact minusha of it. Uh. It's kind of
like with our our ability to understand whether you can
look at data telling you what the weather has been
like at a particular place, particular times of the year,
and you can use that and you can create a
general idea of what the weather is going to be
in the future. You know, I can see, like say
March third, We can take March third for Atlanta, Georgia,
(10:49):
run it all the way through the past as far
as the recorded data goes, and we can get a
general idea of what March thirds in the future are
going to be because it's the their their seasonal aspects
to all of this. There is currents, but it's not
that far away from Richard's Almanac, right, or Richard's Almanac,
which is what two hundred years old or something that
they've been, um, you know, recording all the weather systems
(11:11):
to try to predict the best time to plant crops
and some one and so forth. So yeah, there's it's different.
Um you know, technologies of course to have are in
play now that inform us, but it's you know, the
unpredictability factor is still there. But before we talk about that,
I just wanted to talk about the impetus for this
whole creation. This the the future I see because because
(11:35):
it's we can agree that it's a wonderful idea, but
what potentially gets the money behind this idea? And uh
and that's what Yeah, billion and a half dollars. The
European Commission selected the Living Earth Simulator, which is part
of this project right as a way to help predict
economic conditions. And this was brought up by the Greek
financial crisis because as we know now, it's severely undermine
(11:58):
the European Union and a lot of people are saying, well, perhaps, uh,
you know, grease should pull out of the euro Zone.
And if they were to do that, what would be
the ramifications? You know, you would have a highly devalued
currency for Greece. But what does this mean on a
practical level, for for a global economy. Does this mean
(12:18):
that trade routes would alter? Would there be less disease? Actually,
because it would be a less tourist, less people traveling
to Greece. Um, they're saying, I wish we had to
magic eight ball to ask about this. Dr Dirk says,
I have one. I can build one for you. Will
only cost a billion and a half. There you go. Yeah.
(12:38):
So they have all these different questions about what would
happen if this were the scenario, because of course they
don't want Grease necessarily to pull out and you know
for the EU to crumble, right, I mean these are
big stakes. It's like a big economic ginga game. Um, yeah,
it is. It is um. And And then also you
know you can use this for for other huge situations
(13:00):
or high impact and situations. I should say, like for
instance of volcano eruption. UM could tell you what the
short term economic growth is going to be, as well
as the effect it may have on everything from education
to the distribution of vaccines, political unrest. UM. Disease epidemics
was another one. How disease is spread across the world,
(13:21):
how we should be prepared for the spread, and that
was actually modeled on how the dollar bills are circulated
in the United States, which is really interesting that they
use this as a model. And again we'll talk about
the limitations of using these types of models for other
instances such as disease epidemics. One of the real world
(13:43):
systems that this is based on is UH as actually
the urban traffic the idea of typically congested traffic and
urban area and how do you how do you figure
out what's going wrong, how do you combat it? How
do you deal with the little pockets of unrest and
change that eventually cascade into just complete gridlock, right, and
(14:05):
and Dirk helping this is really his knowledge center, you know,
this is something he's been concentrating on in his career.
Um in this case it's human and machine traffic patterns.
Helving actually consulted on a project that model the movement
of pedestrians during the Hajj in Mecca, resulting in a
billion dollars of street and bridge rejiggering to prevent deaths
from trampling. So this is yeah, this is of course
(14:27):
one of the pillars of Islam. Uh and the the
idea that if you were able, you take this pilgrimage
to Mecca to see the holy sites. So it creates
a lot of challenges just for the infrastructure in Saudi
Arabia to how do you deal with all these these
visitors coming to the country to to see these sites
and do so in a way that doesn't, like you said,
(14:47):
result in trampling, result in starvation. I'm not starvation, but
the hydration. I watched an interesting video here just back.
It was actually put up by the Saudi government that
it was kind of their their video of saying, hey,
we got it under control, don't worry when you come
on the hodge. It's like a public service and yeah, yeah,
and uh, you know, so it was definitely coming from
(15:07):
from the said of government, but it but it was
really interesting because they did go into all these various
things that they are doing and or have done in
the past to try and and limit the congestion or
or or things like the hydration making sure there's plenty
of water. Yeah, and this is a really cool model.
But of course there are limitations to this type of model,
and in particular, if you look at the Hajje or highways,
(15:29):
everyone is moving in the same direction. Right, This is
highly predictable, which underlies one of the main criticisms of
trying to predict the future based on these types of models. Um,
what we know and can predict is actually far less
than what we don't actually know, because in real life
there's not just a northbound lane and a southbound lane
(15:49):
and turn lane there. It's commendously more complex and every
every layer of complexity, Um, I mean it just makes
the overall model that much more are difficult to create. Right.
And there's actually a term for this. Yes, yes, they're
called black Swan events. And when we return, we shall
reveal what the black Swan is. The black Swan we're back.
(16:17):
The black Swan is, uh, is not a crazy ballerina
who turns into a bird. It's true, Yeah, just to
get that out there. Uh, but it is actually an
incredible theory about not only the auliers who change the world,
but the way that we try, the way the way
that we don't understand, um, the importance of those outliers
(16:39):
in retrospect, and the reason why we we it's called
the black Swan event for black Swan events is because
for I don't know, decades hundreds of years. Actually people
thought that there were no black swans because all that
had been documented were white swans. Right, so people thought
really like that there are no black swans, um, there
(17:00):
are only white swans. And in fact they were so
confident of this information that black swan became sort of
this this uh code word for for you know, something
not existing, right, just be something of medical fantasy. Really, yeah,
there's there's actually a Latin term that talks about this,
but low and the whole. Some dude in the eighteen
hundreds visits Australia documents a black swan, and all of
(17:22):
a sudden, this this uh certainty, this this absolute idea
that there were no black swans on the white swans
was turned on its head. Yeah. It reminds me a
lot of two events in the last several years, one
being the maybe half hour or so that it seemed
possible that we had found Bigfoot and Bigfoot's body was
in a cooler in the in the middle Georgia. Uh.
(17:44):
And of course that turned out to be complete bunk bunk.
But but for a for a very brief time, I
was like, oh my goodness, what if they what if
this is it? What if if the the world in
which Bigfoot is an unproven mythical creature is about to end,
and I am entering into a new world in which
Bigfoot is a reality, proven reality, what would that be like?
Another example would be in the last year. And the
(18:04):
jury is still out on exactly what these findings means.
But the findings out of cern regarding faster than light particles.
The idea, I mean the speed of light is is
based on our understanding of physics, uh a universal speed limit.
Nothing can go faster than that, um, because I mean
it would break the universe, to break our understanding of
the universe, it would be a black swan. And then
(18:25):
suddenly we have this finding saying, yeah, we we clocked
some uh some phimotomic particles going fast in the speed
of light. And everybody's like, whoa, I doubt it. Uh,
you know, let's let's do some let's study this, let's uh,
let's find out if if you're if your findings are
actually accurate here. But if they are, it changes everything.
It's it just forces us to complete to enter this
new world where the rules are are different than we
(18:48):
originally perceived them to be. Right, there's a book by
Nacineing Nicholas Talub And he's a distinguished professor of Risk
Engineering at the Polytechnic Institute that n y u UM.
He has this book black Swan, and he talks about
these black Swan events is having three attributes, and the
attributes are rarity, extreme impact in retrospective and what he
(19:09):
means by that is the first, for for for it
to be a black Swan event, it has to be
an outlier. Right, it's outside of our realm of expectations
because nothing in the past would have predicted that it existed. Right. Second,
it carries an extreme impact. The ripples of its existence
are far reaching. Right, and like the photon, I mean
the subatomic particle example here definitely lines up with those
(19:32):
two right if true? If true? Right, that's that's the
key there. For that third, in spite of its outlier status,
human nature makes us concoct explanations for its occurrence after
the after the fact, making it explainable to us and
seemingly predictable. Okay, So he says that there are examples
of this all around us, like the two thousand and
(19:54):
four tsunami, the Rise of Hitler nine eleven, UH, the
advent of the Internet. He says, there all all black
Swan events that we didn't expect were outliers, changed our culture,
um forever right, Uh, changed society, changed world events and uh.
And also the things that we we scrambled afterwards to
(20:18):
try to explain their existence, to to try to make
them feel not so much like these voids of knowledge
to us, because a lot of people would say, oh, well,
if we could just only have done this, we would
have you know, avoided the tsunami or voted nine eleven.
So he actually says, and this is a quote from
his book, Um, this is from the intro. He says,
(20:39):
what did people learn from the nine eleven episode? They
did they learn that some events, owing to their dynamics,
stand largely outside the realm of the predictable. No, did
they learn the built in defect of conventional wisdom? No?
What they what did they figure out? They learned precise
rules for avoiding Islamic proto terrorists and tall bill links.
(21:00):
And this, he says, is a real problem because we
learned so specifically that we try to apply this model again.
You know, we're talking about model systems over and over again.
So he's saying Okay, we learned some sort of lesson
from there, but it's so specific it deals with strong
predators and tall buildings, that it doesn't necessarily say that
(21:21):
we learned a lesson there that helps us to avoid
terrorism altogether. Right, I mean, and that comes down to
just to wear of our minds work. And we were
talking about this before the podcast. Inevitably, when we're talking
about the way we think about the world, we end
up falling back on on examples and involve our ancestors,
and like savor tooth tigers, like the sabre tooth tiger
(21:41):
attacks you, you learn a lesson, but it's gonna be
a very specific lesson in these cases, how to avoid
being eaten? How did you avoid being eaten on this
particular this particular encounter, right we we He would argue
that um Talent would argue that our brains really aren't
built for thinking per se, because if our ancestors had
stopped to think, you know, that probably would have been
(22:04):
torn apart by the sabre tooth tiger. Right, Um that
we are so much more invested in pattern recognition and
UH predictability models than unpredictability. So he's saying that now
we live in this entirely complex world, and we can't
really conceive of all the black swans around us. You know,
we think about eighteen hundreds. Probably it is a lot
(22:25):
more simple, Right, you were going to turn some butter milk,
some cows, um things were you have far less choices. Um,
it was a far lex complex world. So he's saying, really,
our brains haven't caught up to it, and that's why
we are actually blind to all of the black swans
around us. Well, you know, just think back, you know,
I'm speaking to everyone, to you the listener, Just think
(22:46):
back on your own life and and just how how
little of it you could have possibly predicted you could
you know, all the all the little things that have
that have led you to this place in your life,
that the decisions, the the the bits of of just
fate and blind luck and uh and here you are.
But you look back on it and you see it,
uh the way our perspective on it works. Um, you
(23:10):
don't see those black swans even in our own personal history. Right.
But but if you really look closely and you see
that there probably are a series of random events. Right.
We we plan to the best of our ability, and
things happen, and life takes us down different roads, right,
and you know, in retrospect we can probably explain some
of those away and apply some sort of pattern to them.
(23:31):
But Talib would say that it's complete randomness. Um. And
he says, actually, the world is dominated by black swans
and that they are the norm. And so this is
interesting when he says this, because if you if you
take this up face value, it means that this, uh,
this Earth simulator is probably not going to work in
the way that that the European Commission actually wants it to. Yeah,
(23:54):
it's it wouldn't be a situation where, oh, just occasionally
you have a black swan that throws the monkey wrench
into the into our our understanding the world. It's not
like occasionally, oh occasionally, there's been a lot. Occasionally there'sn't
there's a Hitler or Einstein that kind of changes the
way it works. You know, he's saying they're everywhere. That
that that that the world continues to change at a
at a at a steady rate based on the actions
(24:15):
of these various black swans, both individuals and just random
events in the world around us and these very spheres
of activity. Right, So it's great to have these predictive models,
but if you can't build in some sort of system
for ferreting out black swans, or you don't have a
system in there, and that says, okay, well, we think
this is going to happen based on what's you know,
(24:36):
historically the data stream that's coming in. But if you
can't run that up against something that says, you know,
forget it, this might actually not happen, or you have
five other variables, uh, then sort of it sort of
discounts the system as a whole. And even if you
did have the black swan effect or events built in,
(24:57):
you're still not going to get that one answer that
they so desperately want. This says this is the right answer,
because you're gonna get four variables, five variables, ten variables
spit out at you and you're back at square one.
And and then this is something that really blew my mind.
Um when you when you think, imagine you did build
this just enormously complex, uh model of the world, this
(25:18):
living Earth simulator. What gets me is the feedback loop
loops you eventually fall into because because because you're building,
you're building a model of the world that has access
to a model of the world, that has access to
a model of the world, that has access to a
model of the world, and it just like it just
it blows my mind to think of that. How would
(25:38):
that pan out? It just would the complexity would just
would spiral out forever. Well, and there's another point here
that even if you did have a couple of answers
spit out in a in a scenario, right, that seemed like, Okay,
this is the best course of action. Because you have
such a complex system and you can't even understand how
(25:58):
that data came to that conclusion, then you're probably less
likely to trust it in the first place. Yeah. Yeah,
And in fact, it lines up interestingly with climate change
Man Maine climate change and our our attempts to understand it. Uh,
the scientific findings that have come out arguing, uh, the
point that hey, humans are are altering global climate and
here are some things we should do to stop it.
And and just and just how how little of that
(26:21):
has been has resonated with the decision makers and with
the general public in some cases. Right, Right, So they
have a bunch of information there and they still can't act. Yeah,
we ask our our our biggest reasoning machine that we
have available to a science what we should do about
a given situation, we get an answer for it, and
not not everyone's gonna listen. So is there gonna be
any better if we have a a complex simulation of
(26:43):
of existence that we can turn to our people are
gonna trust that? And indeed, are people are going to
trust this supercomputer that has that is using reasoning that
we can't even fathom, uh, to tell us of what
we should do? And what if what indeed if if
it's a suggestion is something that seems nonsensical? Well, and
there's this whole idea too, that all of this is
predicated on us even understanding our existence in the first place,
(27:06):
and how our existence is the fact that you and
I are sitting here and everybody you guys are listening.
This is a black Swan event in and of itself.
And what I mean about that is the odds of
our existence. Um. There's a Harvard professor Dr Ali Benazzar
who says, so, what's the probability of you existing? This
(27:27):
is a quote. It says, it's the probability of two
million people getting together about the population of San Diego,
each to play a game of dice with trillion sided dice.
They each roll the dice and they all come up
with the exact same number. Say, five hundred and fifty trillion,
three hundred forty three million, two hundred seventy nine thousand
(27:48):
and one. That's the number. So, you know, we've talked
about this before to just in terms of the rare
Earth theory, about how the fact that life on Earth
came about in and how there's circumstances were just right.
But this is a rarity as far as we know, right, Yeah,
so it's you know, we have a whole podcast devoted
(28:08):
to this. But but the arguments often come down to, um,
it's such a rare event that this Earth exists, Does
that mean that we're special or you know? But but
we can't think scientifically, we can't view ourselves as special.
So how do we how do we wrap our heads
around that one? So yeah, yeah, there you go, There
you go. And then if this if this simulator, if
this future set, if it actually it works right, if
(28:32):
it comes to fruition and it's useful in naturally predicting
uh black swans really, because that's what the end result
of that should be. Uh, then What does that mean
about science? What does that mean about thought experiments? You know,
if everything is answerable and predictable, is at the end
of science? I don't know. And and then likewise it
(28:53):
also brings to mind any kind of corporate situation where
you have a problem. What's the first thing people do?
Meeting about it? Committee about it. Let's form a task
force to to talk about this, uh, this situation and
come up with some recommendations to what extent would this
simulation this uh, this Living Earth simulator be a version
of that where we're like, oh, we have a problem. Um,
(29:13):
you know, there's a there's a there suffering in the
world somewhere. What should we do about it? Throw into
the simulator and then we get the results, and then
the simulator gives us a list of recommendations and we
end up following none of them. Right, we don't have
the budget for that, right because we've we've talked about it.
We we put the the info into the machine. It
uh it does spit us out some numbers, so we're good. Right, Well,
(29:36):
at least we can finally uh let the cat out
of Shreddinger's box, right, yeah, all right, Well, let's have
the Robot bring us something to read reading Donald, Thank you.
There we go. All right, Well, we heard from a
listener by the name of Dustin. Dustin Wright sentences Hi, Robert,
(29:56):
Julie and the rest of the STB y M staff.
I wanted to say thanks for your episode on mesophonium.
My whole life has been driven nuts by chewing, swallowing
and smacking. I always thought that my reaction wasn't normal,
but now I realized that I'm not alone out there.
It was really fascinating to hear about others triggers. At
least I know when I expect my triggers and can
take steps to cope with the overwhelming anxiety. If a
(30:19):
person's trigger was the crunching of leaves, then that must
be hell. I really hope that the more research that
develops on this topic. Thanks for all of your hard
work and the wonderful show. Yeah, that was really great.
We've had so many people right in about mesophonia. It's
really interesting. It seems to be just anecdotally, uh more
widespread than we saw. Yeah. I mean, I find myself
(30:41):
thinking about it all the time too. Whenever I let
petty things sounds annoy me, and I sort of have
to step back and I'm like, maybe have a touch
of messophonia. And then I'm like, well be conscious of it,
don't let it irk you in. And luckily I don't
have severe enough reactions that that doesn't work. Yeah. Yeah,
you know what, Chris, this was hard for me because
I've got a three year old and there was a
(31:02):
lot of start from around and I was constantly stop.
All right, here's another one just from listener Neil. Neil
writes and it says, Hi, Robert and Julie's super podcast again,
didn't know about Terry Pratchett's sword made out of meteor?
Do they call him sky swords? He's a responding tore
away of the Sword podcast. Just a note on kindo.
The foot stomp happens at the time of the strike
(31:23):
or cut, not before, or at least not as a warning.
The stomp uh fumi komi is part of the cut. Typically,
for a cut to be counted, you need to stomp,
call out what you were cutting, and of course land
the cut in the place that you have called out.
This is all to demonstrate what kN Doka call key
kin ta ichi, the oneness of the spirit key with
(31:46):
the sword. Can and the body tie. You can, of
course foot stomp before a cut, but typically this is
a thing to get a reaction, either a flinch or
start from the other kim dooka, which might reveal a
hesitate to exploit immediately or just put them on edge,
or an attack which you might counterattack or otherwise blunt.
(32:06):
I am not sure I would call it a warning,
since the intention is usually not that charitable. That said,
kendo is a great martial art, no disrespect to other
sword arts, and well worth the effort. Fun to boot
and the gear is cool too. Anyway, thanks for the
super podcast series, Cheers and Neil Cool. Yeah, I was
so glad to hear the information. I saw some of
the kendo in the documentary Reclaiming the Blade, and it
(32:29):
seemed as though they were stomping as a warning. But
it's great to share that information. It makes it even
that much more intriguing of muscial art. Yeah, it's kind
of it sounds a lot like it's kind of like
a like a lunch like you see. I mean, I
not that I've ever been in a fight, but you know,
you see people in like in a fighting situation, and
one will sort of like Yeah, but I like this idea,
(32:50):
this one oneness of the spirit and the sword and um,
and that's why they did a little foot stomping. I
also I was thinking that the little foot stoping because
they have tiny little feet with Kendem Marshall artists have
tiny little fie. Okay, I'm kidding, um, but but I
mean it made me think of playing pool, like if
you were to call out a pocket, but you would
do it at the same time that you were to
(33:11):
hit the ball, or kind of like Babe Ruth like
pointing the field is going to hit the ball. Yeah,
thank you, sucker. Try just try to get it. Well. Hey,
we would love to hear what anyone has to say
about the the idea of a living Earth simulator. Um,
what do you think about it? Depending do you do?
You do you think it's a great idea, do you
(33:32):
think it's at all feasible? And how do you imagine
a future in which we have access to one? Would
you want an app on your phone? Yeah, because that
was one of the things that they talk about, is
the idea that if we had this simulator in place,
you would basically be able to get apps where you
could see like and I imagine someone would be kind
of fun like. Someone will probably be like, what would
a zombie apocalypse actually look like? Let's load that in.
(33:54):
What would it be like? If you know, just any
kind of crazy scenario you could think of, you could
conceivably have an app for it to to to load
in to check. And you can just imagine everyone from
any like every business in the world would have some
sort of access to this model so they could test
their various uh, promotional materials, etcetera. But let us know
(34:15):
what you think. You can find us on Facebook and Twitter.
We are blow the Mind on Twitter, and you can
find us on Facebook just by searching for stuff to
blow the mind. And you can drop us a line
at blow the Mind at how stuff works dot com.
Be sure to check out our new video podcast, Stuff
from the Future. Join how Stuff Work staff as we
(34:37):
explore the most promising and perplexing possibilities of tomorrow.
Welcome to Stuff to Blow your Mind from how Stuff
Works dot com. Hey, welcome to Stuff to Blow your Mind.
My name is Robert Lamb and Julie Douglas. Julie, you know,
making decisions in this world can be really taxing. We've
discussed that before. Even the smallest decisions in life are
(00:24):
often difficult to make. But put yourself in the in
the boots in the gold studied jewel encrusted boots of
a king or or an Elvis, somebody who's whose decisions
are are are sweeping that change the escape of international
politics and economics. We're talking about huge ripple effect globally, globally,
(00:48):
huge political leaders, leaders of multinational companies, policymakers, The decisions
that they make UH can have catastrophic effects. They can
they can change the world for the better for the worst.
So in UH, in ancient times, you know, you would
have the emperor and he would have like a sourcerer
or a diviner there too. I was gonna say, an
(01:08):
oracle or an oracle, you know, there would be some
sort of magical go to man to bounce these ideas
off of and be like, hey, I'm trying to figure
out what to do about this. I don't know this
protest situation in the streets, um, but I'm not really
sure what to do. Can you look into your magic
pool of water and see what the future is going
to be, um, and tell me what I should do? Now?
(01:32):
Of course, there's no such thing as magic. There is,
so I'm sorry atually to tell me that my fortune
cookies are full of bunk, except the ones where the
fortune is general advice. But but we we love the
idea of being able to do that. Mainly we want
to we want to test our assumptions about what should
be done versus the outcome of those assumptions in the
(01:53):
real world. So what you're saying is that if leaders
had some sort of magic ball, right that they could
ask a question of and it could it actually spit
out an answer that was valid, we could uh really
manage our lives on a global scale in the much cleaner,
better way. That's the idea. But of course, to power
(02:15):
that magic eight ball, you would need some pretty intense
computer technology, and you would you would basically have to
have a computer model of everything under there. Uh. And
in the same day, in our attempts to understand global
climate UH, and just not even global climate, just local
weather to find out whether whether we should have a
picnic tomorrow. Can I plan on mo in my yard?
(02:35):
Should I would bring a raincoat with me to the
to the train station, that kind of thing. We depend
on these these climate models, which UHL is we've discussed
in the past. Creating an an accurate climate model is
very difficult. There's so many factors involved. It's a it's
largely chaotic system, and it's it's difficult to judge. Like
every every day that you're into the future that you look,
(02:57):
the more flawed the model becomes. But but still we
we depend on the community computer models for for our
understanding of what the weather is going to be. And
if conceivably, if we created a complex enough computer model,
could we not have a a kind of simulation of
the world in which to test our ideas. So you
(03:19):
would have this politician or this policymaker somewhere in a
position of power, gold stilettos, and she's thinking to herself,
what should I do? Should I enact this policy or
this policy? Well, bring me the magic eight ball and
I will ask it in the magic eight ball will
then run two scenarios in the in its simulation of
the world, one in which policy A is enacted and
(03:40):
one in which policy B is enacted. Okay, but this
magic eight ball would have to aggregate data of our
entire existence, right, so we're talking about the economic existence,
are social um existence, the geographical existence um, you know,
the physics of our existence. All of this, uh, would
have to be something that we could get our arms around,
(04:02):
all this data, right, and and and then we have
to have a name for this, all this data. We
call it big data. Big data name for it. And
it's kind of like imagine, like the way I was
kind of thinking, because I'm writing about some related issues
here for work, so I've been been researching, and the
way I tend to think of it is imagine, imagine
like this this field, all right, this flat plane, right,
(04:25):
what's not completely flat. There's some slight bumps in it
enough to where you have numerous puddles of water, and
then it starts raining, right, those puddles get bigger and
bigger until those puddles all meet and then you have
like a giant lake. And so that's the kind of Uh,
that's how I like I end up imagining big data
because every day we create an estimated two point five
(04:47):
quin trillion bytes of data. So to the point of
the data in the world today has been created in
the last two years alone. And when I say big data,
like this is all these little puddles of data that
form this giant lake of big day. We're talking about
everything we'll climate sensors, to your to everyone's Facebook and
Twitter updates, to digital text, digital video and picture upload.
(05:10):
Stuff you're putting on Flicker, stuff you're putting on YouTube
to just to show visions of the world, ideas about
what the world is doing, online transaction records, cell phone
GPS signals, all of it is coming together into this
big picture of big data, right and right now it's
chaos to us, right, I mean, this is not something
that we've tried to manage before to get a picture
(05:30):
of what our lives look like using all of this
big data, although some people, some institutions have tried to
do it at a smaller scale, like NASA. Right, it's
kind of like imagine the dude or a lady who
starts just picking up buying a book every day and
doesn't doesn't have any kind of accurate library system going
in their house. They just bring a book or to home.
They maybe they read a little bit of one, they
(05:51):
throw on here, throw on here. Eventually they have an
entire house just filled with books. But they have no
system of organization to understand how many books they have,
how their selection in one category stacks up against another,
or even kind of like just a general idea of
what kind of books they like. Um. So we were
in this household of big data where data is just everywhere,
(06:11):
on everything, but we we tend to lack a complete
picture of what that data is telling us. What we're
getting to is that there is actually in the works
a a proposal and an enactment of this idea. It's
a billion a half dollar idea computing system to actually
try to wrangle all of this data. Right. It all
(06:34):
falls under the this project known as UH Future I
C T, which is really three parts. There's a planetary
nervous system and the idea here is you would um,
it's like a global sensor network throwing in all sorts
of socio economic, environmental, technological data from around the world. Again,
like the big day of the big data in the
world is from the last two years. Although there it's
(06:56):
the the timiness of this data as it's rolling in.
So if you put up enough, put up enough sensors,
you you hooked into enough existing data networks, you would
have like a real time picture of what is happening
in the world and all these different spheres. Okay, and
the guy who is heading it all up is dirt helping.
He's the Scientific Coordinator of the Future i c T.
(07:16):
Which is that what you're talking about, this large scale
European research program to explore and manage our future. And
he's talking about the necessity to understand complex global, socially
interactive systems. He's saying that we live in a global
world and this requires new tools. Yeah, and uh, if
i'm engine the first tool the planetary nervous system. Another tool,
(07:37):
which we'll get into later, is the Global Participatory Platform,
which you can think of in a way sort of
like this the the interactive aspect of this project. But
then the really core thing, the thing that we're going
to talk in detail about here is the Living Earth simulator.
And this is exactly what we were talking about, the
engine that would drive this imaginary eight ball magic eight ball.
(07:59):
I love this idea because to me it seems like
a souped up second life. Yeah, where it's or it's
you can't help. But even though it's it's probably not
kosher to really talk about the matrix anymore after the
last two films, but it sounds very matrix like the
idea that here is here, there's a simulated world where
we would we would bring in all this data to
create a model of the world on which we can
(08:19):
test possible choices. Well, and have you ever seen Google's
Liquid Earth. I don't think I have. It's really cool.
It's a it's actually created as like someone's project over
at Google. So the Skuy's time, he decided to dedicate
to the Google Earth model that they have, you know
that consuming on the cities, and he created this highly
immersive program has eight panels surrounding you. She almost feel
(08:42):
like you're in a video game. And the idea I
think is that you know, you can zoom in and
out and you can see the taj Mahal and you
can see all the details. Um So when I think
about this Earth simulator, this Living Earth simulator, I think
about this sort of immersive situation and where you can
be on a city street, you can zoom in and
(09:03):
you'll have all of this data overlaid on top of
it real time, right, And again, real time is key
when we're talking about all this data. Um so Dr
Dirk Um, Dr Dirk, Dr Dirk he Um. He's very
expressive about all of this. He makes the point that
in the past, we we didn't really have the data
to come up with a systemic science of how our
(09:25):
society works. But now we have this data, right, and
of course who could have conceived of it right? Right? Right?
Who could have conceived of it in the past. And
he's saying it's it's necessary to keep up with globalization,
technological change. You have all these systems like smashing into
each other. In fact, he often refers to the living
or simulator is a knowledge collider. The idea that you
would take all this data and in the same way
(09:45):
that the the large hypn collider is is slamming particles
together to try to understand how the universe works. This
is about like slamming all this information together and seeing
what happens. Which I like this idea because although I
will say that it doesn't sound like it's going to
be quite that dynamic, because this is this is predictive
modeling that we're talking about, and as and as we
(10:06):
discussed in the weather example, predictive modeling is uh imperfect
at best. Uh. There there are various arguments about what
can be done with computer modeling of of complex systems.
There are plenty of arguments that state that you cannot
form a perfect model of a complex system that you're
you're never gonna be able to to really get down
(10:27):
into the exact minusha of it. Uh. It's kind of
like with our our ability to understand whether you can
look at data telling you what the weather has been
like at a particular place, particular times of the year,
and you can use that and you can create a
general idea of what the weather is going to be
in the future. You know, I can see, like say
March third, We can take March third for Atlanta, Georgia,
(10:49):
run it all the way through the past as far
as the recorded data goes, and we can get a
general idea of what March thirds in the future are
going to be because it's the their their seasonal aspects
to all of this. There is currents, but it's not
that far away from Richard's Almanac, right, or Richard's Almanac,
which is what two hundred years old or something that
they've been, um, you know, recording all the weather systems
(11:11):
to try to predict the best time to plant crops
and some one and so forth. So yeah, there's it's different.
Um you know, technologies of course to have are in
play now that inform us, but it's you know, the
unpredictability factor is still there. But before we talk about that,
I just wanted to talk about the impetus for this
whole creation. This the the future I see because because
(11:35):
it's we can agree that it's a wonderful idea, but
what potentially gets the money behind this idea? And uh
and that's what Yeah, billion and a half dollars. The
European Commission selected the Living Earth Simulator, which is part
of this project right as a way to help predict
economic conditions. And this was brought up by the Greek
financial crisis because as we know now, it's severely undermine
(11:58):
the European Union and a lot of people are saying, well, perhaps, uh,
you know, grease should pull out of the euro Zone.
And if they were to do that, what would be
the ramifications? You know, you would have a highly devalued
currency for Greece. But what does this mean on a
practical level, for for a global economy. Does this mean
(12:18):
that trade routes would alter? Would there be less disease? Actually,
because it would be a less tourist, less people traveling
to Greece. Um, they're saying, I wish we had to
magic eight ball to ask about this. Dr Dirk says,
I have one. I can build one for you. Will
only cost a billion and a half. There you go. Yeah.
(12:38):
So they have all these different questions about what would
happen if this were the scenario, because of course they
don't want Grease necessarily to pull out and you know
for the EU to crumble, right, I mean these are
big stakes. It's like a big economic ginga game. Um, yeah,
it is. It is um. And And then also you
know you can use this for for other huge situations
(13:00):
or high impact and situations. I should say, like for
instance of volcano eruption. UM could tell you what the
short term economic growth is going to be, as well
as the effect it may have on everything from education
to the distribution of vaccines, political unrest. UM. Disease epidemics
was another one. How disease is spread across the world,
(13:21):
how we should be prepared for the spread, and that
was actually modeled on how the dollar bills are circulated
in the United States, which is really interesting that they
use this as a model. And again we'll talk about
the limitations of using these types of models for other
instances such as disease epidemics. One of the real world
(13:43):
systems that this is based on is UH as actually
the urban traffic the idea of typically congested traffic and
urban area and how do you how do you figure
out what's going wrong, how do you combat it? How
do you deal with the little pockets of unrest and
change that eventually cascade into just complete gridlock, right, and
(14:05):
and Dirk helping this is really his knowledge center, you know,
this is something he's been concentrating on in his career.
Um in this case it's human and machine traffic patterns.
Helving actually consulted on a project that model the movement
of pedestrians during the Hajj in Mecca, resulting in a
billion dollars of street and bridge rejiggering to prevent deaths
from trampling. So this is yeah, this is of course
(14:27):
one of the pillars of Islam. Uh and the the
idea that if you were able, you take this pilgrimage
to Mecca to see the holy sites. So it creates
a lot of challenges just for the infrastructure in Saudi
Arabia to how do you deal with all these these
visitors coming to the country to to see these sites
and do so in a way that doesn't, like you said,
(14:47):
result in trampling, result in starvation. I'm not starvation, but
the hydration. I watched an interesting video here just back.
It was actually put up by the Saudi government that
it was kind of their their video of saying, hey,
we got it under control, don't worry when you come
on the hodge. It's like a public service and yeah, yeah,
and uh, you know, so it was definitely coming from
(15:07):
from the said of government, but it but it was
really interesting because they did go into all these various
things that they are doing and or have done in
the past to try and and limit the congestion or
or or things like the hydration making sure there's plenty
of water. Yeah, and this is a really cool model.
But of course there are limitations to this type of model,
and in particular, if you look at the Hajje or highways,
(15:29):
everyone is moving in the same direction. Right, This is
highly predictable, which underlies one of the main criticisms of
trying to predict the future based on these types of models. Um,
what we know and can predict is actually far less
than what we don't actually know, because in real life
there's not just a northbound lane and a southbound lane
(15:49):
and turn lane there. It's commendously more complex and every
every layer of complexity, Um, I mean it just makes
the overall model that much more are difficult to create. Right.
And there's actually a term for this. Yes, yes, they're
called black Swan events. And when we return, we shall
reveal what the black Swan is. The black Swan we're back.
(16:17):
The black Swan is, uh, is not a crazy ballerina
who turns into a bird. It's true, Yeah, just to
get that out there. Uh, but it is actually an
incredible theory about not only the auliers who change the world,
but the way that we try, the way the way
that we don't understand, um, the importance of those outliers
(16:39):
in retrospect, and the reason why we we it's called
the black Swan event for black Swan events is because
for I don't know, decades hundreds of years. Actually people
thought that there were no black swans because all that
had been documented were white swans. Right, so people thought
really like that there are no black swans, um, there
(17:00):
are only white swans. And in fact they were so
confident of this information that black swan became sort of
this this uh code word for for you know, something
not existing, right, just be something of medical fantasy. Really, yeah,
there's there's actually a Latin term that talks about this,
but low and the whole. Some dude in the eighteen
hundreds visits Australia documents a black swan, and all of
(17:22):
a sudden, this this uh certainty, this this absolute idea
that there were no black swans on the white swans
was turned on its head. Yeah. It reminds me a
lot of two events in the last several years, one
being the maybe half hour or so that it seemed
possible that we had found Bigfoot and Bigfoot's body was
in a cooler in the in the middle Georgia. Uh.
(17:44):
And of course that turned out to be complete bunk bunk.
But but for a for a very brief time, I
was like, oh my goodness, what if they what if
this is it? What if if the the world in
which Bigfoot is an unproven mythical creature is about to end,
and I am entering into a new world in which
Bigfoot is a reality, proven reality, what would that be like?
Another example would be in the last year. And the
(18:04):
jury is still out on exactly what these findings means.
But the findings out of cern regarding faster than light particles.
The idea, I mean the speed of light is is
based on our understanding of physics, uh a universal speed limit.
Nothing can go faster than that, um, because I mean
it would break the universe, to break our understanding of
the universe, it would be a black swan. And then
(18:25):
suddenly we have this finding saying, yeah, we we clocked
some uh some phimotomic particles going fast in the speed
of light. And everybody's like, whoa, I doubt it. Uh,
you know, let's let's do some let's study this, let's uh,
let's find out if if you're if your findings are
actually accurate here. But if they are, it changes everything.
It's it just forces us to complete to enter this
new world where the rules are are different than we
(18:48):
originally perceived them to be. Right, there's a book by
Nacineing Nicholas Talub And he's a distinguished professor of Risk
Engineering at the Polytechnic Institute that n y u UM.
He has this book black Swan, and he talks about
these black Swan events is having three attributes, and the
attributes are rarity, extreme impact in retrospective and what he
(19:09):
means by that is the first, for for for it
to be a black Swan event, it has to be
an outlier. Right, it's outside of our realm of expectations
because nothing in the past would have predicted that it existed. Right. Second,
it carries an extreme impact. The ripples of its existence
are far reaching. Right, and like the photon, I mean
the subatomic particle example here definitely lines up with those
(19:32):
two right if true? If true? Right, that's that's the
key there. For that third, in spite of its outlier status,
human nature makes us concoct explanations for its occurrence after
the after the fact, making it explainable to us and
seemingly predictable. Okay, So he says that there are examples
of this all around us, like the two thousand and
(19:54):
four tsunami, the Rise of Hitler nine eleven, UH, the
advent of the Internet. He says, there all all black
Swan events that we didn't expect were outliers, changed our culture,
um forever right, Uh, changed society, changed world events and uh.
And also the things that we we scrambled afterwards to
(20:18):
try to explain their existence, to to try to make
them feel not so much like these voids of knowledge
to us, because a lot of people would say, oh, well,
if we could just only have done this, we would
have you know, avoided the tsunami or voted nine eleven.
So he actually says, and this is a quote from
his book, Um, this is from the intro. He says,
(20:39):
what did people learn from the nine eleven episode? They
did they learn that some events, owing to their dynamics,
stand largely outside the realm of the predictable. No, did
they learn the built in defect of conventional wisdom? No?
What they what did they figure out? They learned precise
rules for avoiding Islamic proto terrorists and tall bill links.
(21:00):
And this, he says, is a real problem because we
learned so specifically that we try to apply this model again.
You know, we're talking about model systems over and over again.
So he's saying Okay, we learned some sort of lesson
from there, but it's so specific it deals with strong
predators and tall buildings, that it doesn't necessarily say that
(21:21):
we learned a lesson there that helps us to avoid
terrorism altogether. Right, I mean, and that comes down to
just to wear of our minds work. And we were
talking about this before the podcast. Inevitably, when we're talking
about the way we think about the world, we end
up falling back on on examples and involve our ancestors,
and like savor tooth tigers, like the sabre tooth tiger
(21:41):
attacks you, you learn a lesson, but it's gonna be
a very specific lesson in these cases, how to avoid
being eaten? How did you avoid being eaten on this
particular this particular encounter, right we we He would argue
that um Talent would argue that our brains really aren't
built for thinking per se, because if our ancestors had
stopped to think, you know, that probably would have been
(22:04):
torn apart by the sabre tooth tiger. Right, Um that
we are so much more invested in pattern recognition and
UH predictability models than unpredictability. So he's saying that now
we live in this entirely complex world, and we can't
really conceive of all the black swans around us. You know,
we think about eighteen hundreds. Probably it is a lot
(22:25):
more simple, Right, you were going to turn some butter milk,
some cows, um things were you have far less choices. Um,
it was a far lex complex world. So he's saying, really,
our brains haven't caught up to it, and that's why
we are actually blind to all of the black swans
around us. Well, you know, just think back, you know,
I'm speaking to everyone, to you the listener, Just think
(22:46):
back on your own life and and just how how
little of it you could have possibly predicted you could
you know, all the all the little things that have
that have led you to this place in your life,
that the decisions, the the the bits of of just
fate and blind luck and uh and here you are.
But you look back on it and you see it,
uh the way our perspective on it works. Um, you
(23:10):
don't see those black swans even in our own personal history. Right.
But but if you really look closely and you see
that there probably are a series of random events. Right.
We we plan to the best of our ability, and
things happen, and life takes us down different roads, right,
and you know, in retrospect we can probably explain some
of those away and apply some sort of pattern to them.
(23:31):
But Talib would say that it's complete randomness. Um. And
he says, actually, the world is dominated by black swans
and that they are the norm. And so this is
interesting when he says this, because if you if you
take this up face value, it means that this, uh,
this Earth simulator is probably not going to work in
the way that that the European Commission actually wants it to. Yeah,
(23:54):
it's it wouldn't be a situation where, oh, just occasionally
you have a black swan that throws the monkey wrench
into the into our our understanding the world. It's not
like occasionally, oh occasionally, there's been a lot. Occasionally there'sn't
there's a Hitler or Einstein that kind of changes the
way it works. You know, he's saying they're everywhere. That
that that that the world continues to change at a
at a at a steady rate based on the actions
(24:15):
of these various black swans, both individuals and just random
events in the world around us and these very spheres
of activity. Right, So it's great to have these predictive models,
but if you can't build in some sort of system
for ferreting out black swans, or you don't have a
system in there, and that says, okay, well, we think
this is going to happen based on what's you know,
(24:36):
historically the data stream that's coming in. But if you
can't run that up against something that says, you know,
forget it, this might actually not happen, or you have
five other variables, uh, then sort of it sort of
discounts the system as a whole. And even if you
did have the black swan effect or events built in,
(24:57):
you're still not going to get that one answer that
they so desperately want. This says this is the right answer,
because you're gonna get four variables, five variables, ten variables
spit out at you and you're back at square one.
And and then this is something that really blew my mind.
Um when you when you think, imagine you did build
this just enormously complex, uh model of the world, this
(25:18):
living Earth simulator. What gets me is the feedback loop
loops you eventually fall into because because because you're building,
you're building a model of the world that has access
to a model of the world, that has access to
a model of the world, that has access to a
model of the world, and it just like it just
it blows my mind to think of that. How would
(25:38):
that pan out? It just would the complexity would just
would spiral out forever. Well, and there's another point here
that even if you did have a couple of answers
spit out in a in a scenario, right, that seemed like, Okay,
this is the best course of action. Because you have
such a complex system and you can't even understand how
(25:58):
that data came to that conclusion, then you're probably less
likely to trust it in the first place. Yeah. Yeah,
And in fact, it lines up interestingly with climate change
Man Maine climate change and our our attempts to understand it. Uh,
the scientific findings that have come out arguing, uh, the
point that hey, humans are are altering global climate and
here are some things we should do to stop it.
And and just and just how how little of that
(26:21):
has been has resonated with the decision makers and with
the general public in some cases. Right, Right, So they
have a bunch of information there and they still can't act. Yeah,
we ask our our our biggest reasoning machine that we
have available to a science what we should do about
a given situation, we get an answer for it, and
not not everyone's gonna listen. So is there gonna be
any better if we have a a complex simulation of
(26:43):
of existence that we can turn to our people are
gonna trust that? And indeed, are people are going to
trust this supercomputer that has that is using reasoning that
we can't even fathom, uh, to tell us of what
we should do? And what if what indeed if if
it's a suggestion is something that seems nonsensical? Well, and
there's this whole idea too, that all of this is
predicated on us even understanding our existence in the first place,
(27:06):
and how our existence is the fact that you and
I are sitting here and everybody you guys are listening.
This is a black Swan event in and of itself.
And what I mean about that is the odds of
our existence. Um. There's a Harvard professor Dr Ali Benazzar
who says, so, what's the probability of you existing? This
(27:27):
is a quote. It says, it's the probability of two
million people getting together about the population of San Diego,
each to play a game of dice with trillion sided dice.
They each roll the dice and they all come up
with the exact same number. Say, five hundred and fifty trillion,
three hundred forty three million, two hundred seventy nine thousand
(27:48):
and one. That's the number. So, you know, we've talked
about this before to just in terms of the rare
Earth theory, about how the fact that life on Earth
came about in and how there's circumstances were just right.
But this is a rarity as far as we know, right, Yeah,
so it's you know, we have a whole podcast devoted
(28:08):
to this. But but the arguments often come down to, um,
it's such a rare event that this Earth exists, Does
that mean that we're special or you know? But but
we can't think scientifically, we can't view ourselves as special.
So how do we how do we wrap our heads
around that one? So yeah, yeah, there you go, There
you go. And then if this if this simulator, if
this future set, if it actually it works right, if
(28:32):
it comes to fruition and it's useful in naturally predicting
uh black swans really, because that's what the end result
of that should be. Uh, then What does that mean
about science? What does that mean about thought experiments? You know,
if everything is answerable and predictable, is at the end
of science? I don't know. And and then likewise it
(28:53):
also brings to mind any kind of corporate situation where
you have a problem. What's the first thing people do?
Meeting about it? Committee about it. Let's form a task
force to to talk about this, uh, this situation and
come up with some recommendations to what extent would this
simulation this uh, this Living Earth simulator be a version
of that where we're like, oh, we have a problem. Um,
(29:13):
you know, there's a there's a there suffering in the
world somewhere. What should we do about it? Throw into
the simulator and then we get the results, and then
the simulator gives us a list of recommendations and we
end up following none of them. Right, we don't have
the budget for that, right because we've we've talked about it.
We we put the the info into the machine. It
uh it does spit us out some numbers, so we're good. Right, Well,
(29:36):
at least we can finally uh let the cat out
of Shreddinger's box, right, yeah, all right, Well, let's have
the Robot bring us something to read reading Donald, Thank you.
There we go. All right, Well, we heard from a
listener by the name of Dustin. Dustin Wright sentences Hi, Robert,
(29:56):
Julie and the rest of the STB y M staff.
I wanted to say thanks for your episode on mesophonium.
My whole life has been driven nuts by chewing, swallowing
and smacking. I always thought that my reaction wasn't normal,
but now I realized that I'm not alone out there.
It was really fascinating to hear about others triggers. At
least I know when I expect my triggers and can
take steps to cope with the overwhelming anxiety. If a
(30:19):
person's trigger was the crunching of leaves, then that must
be hell. I really hope that the more research that
develops on this topic. Thanks for all of your hard
work and the wonderful show. Yeah, that was really great.
We've had so many people right in about mesophonia. It's
really interesting. It seems to be just anecdotally, uh more
widespread than we saw. Yeah. I mean, I find myself
(30:41):
thinking about it all the time too. Whenever I let
petty things sounds annoy me, and I sort of have
to step back and I'm like, maybe have a touch
of messophonia. And then I'm like, well be conscious of it,
don't let it irk you in. And luckily I don't
have severe enough reactions that that doesn't work. Yeah. Yeah,
you know what, Chris, this was hard for me because
I've got a three year old and there was a
(31:02):
lot of start from around and I was constantly stop.
All right, here's another one just from listener Neil. Neil
writes and it says, Hi, Robert and Julie's super podcast again,
didn't know about Terry Pratchett's sword made out of meteor?
Do they call him sky swords? He's a responding tore
away of the Sword podcast. Just a note on kindo.
The foot stomp happens at the time of the strike
(31:23):
or cut, not before, or at least not as a warning.
The stomp uh fumi komi is part of the cut. Typically,
for a cut to be counted, you need to stomp,
call out what you were cutting, and of course land
the cut in the place that you have called out.
This is all to demonstrate what kN Doka call key
kin ta ichi, the oneness of the spirit key with
(31:46):
the sword. Can and the body tie. You can, of
course foot stomp before a cut, but typically this is
a thing to get a reaction, either a flinch or
start from the other kim dooka, which might reveal a
hesitate to exploit immediately or just put them on edge,
or an attack which you might counterattack or otherwise blunt.
(32:06):
I am not sure I would call it a warning,
since the intention is usually not that charitable. That said,
kendo is a great martial art, no disrespect to other
sword arts, and well worth the effort. Fun to boot
and the gear is cool too. Anyway, thanks for the
super podcast series, Cheers and Neil Cool. Yeah, I was
so glad to hear the information. I saw some of
the kendo in the documentary Reclaiming the Blade, and it
(32:29):
seemed as though they were stomping as a warning. But
it's great to share that information. It makes it even
that much more intriguing of muscial art. Yeah, it's kind
of it sounds a lot like it's kind of like
a like a lunch like you see. I mean, I
not that I've ever been in a fight, but you know,
you see people in like in a fighting situation, and
one will sort of like Yeah, but I like this idea,
(32:50):
this one oneness of the spirit and the sword and um,
and that's why they did a little foot stomping. I
also I was thinking that the little foot stoping because
they have tiny little feet with Kendem Marshall artists have
tiny little fie. Okay, I'm kidding, um, but but I
mean it made me think of playing pool, like if
you were to call out a pocket, but you would
do it at the same time that you were to
(33:11):
hit the ball, or kind of like Babe Ruth like
pointing the field is going to hit the ball. Yeah,
thank you, sucker. Try just try to get it. Well. Hey,
we would love to hear what anyone has to say
about the the idea of a living Earth simulator. Um,
what do you think about it? Depending do you do?
You do you think it's a great idea, do you
(33:32):
think it's at all feasible? And how do you imagine
a future in which we have access to one? Would
you want an app on your phone? Yeah, because that
was one of the things that they talk about, is
the idea that if we had this simulator in place,
you would basically be able to get apps where you
could see like and I imagine someone would be kind
of fun like. Someone will probably be like, what would
a zombie apocalypse actually look like? Let's load that in.
(33:54):
What would it be like? If you know, just any
kind of crazy scenario you could think of, you could
conceivably have an app for it to to to load
in to check. And you can just imagine everyone from
any like every business in the world would have some
sort of access to this model so they could test
their various uh, promotional materials, etcetera. But let us know
(34:15):
what you think. You can find us on Facebook and Twitter.
We are blow the Mind on Twitter, and you can
find us on Facebook just by searching for stuff to
blow the mind. And you can drop us a line
at blow the Mind at how stuff works dot com.
Be sure to check out our new video podcast, Stuff
from the Future. Join how Stuff Work staff as we
(34:37):
explore the most promising and perplexing possibilities of tomorrow.
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