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TED2015

Donald Hoffman: Do we see reality as it is?

March 18, 2015

Cognitive scientist Donald Hoffman is trying to answer a big question: Do we experience the world as it really is ... or as we need it to be? In this ever so slightly mind-blowing talk, he ponders how our minds construct reality for us.

Donald Hoffman - Cognitive scientist
Donald Hoffman studies how our visual perception, guided by millions of years of natural selection, authors every aspect of our everyday reality. Full bio

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Double-click the English subtitles below to play the video.
I love a great mystery,
00:12
and I'm fascinated by the greatest
unsolved mystery in science,
00:14
perhaps because it's personal.
00:19
It's about who we are,
00:21
and I can't help but be curious.
00:23
The mystery is this:
00:26
What is the relationship
between your brain
00:28
and your conscious experiences,
00:31
such as your experience
of the taste of chocolate
00:33
or the feeling of velvet?
00:35
Now, this mystery is not new.
00:38
In 1868, Thomas Huxley wrote,
00:40
"How it is that anything so remarkable
as a state of consciousness comes about
00:44
as the result of irritating nervous tissue
00:49
is just as unaccountable
00:53
as the appearance of the genie
when Aladdin rubbed his lamp."
00:55
Now, Huxley knew that brain activity
01:01
and conscious experiences are correlated,
01:03
but he didn't know why.
01:06
To the science of his day,
it was a mystery.
01:08
In the years since Huxley,
01:12
science has learned a lot
about brain activity,
01:14
but the relationship
between brain activity
01:17
and conscious experiences
is still a mystery.
01:19
Why? Why have we made so little progress?
01:22
Well, some experts think
that we can't solve this problem
01:26
because we lack the necessary
concepts and intelligence.
01:31
We don't expect monkeys to solve
problems in quantum mechanics,
01:35
and as it happens, we can't expect
our species to solve this problem either.
01:39
Well, I disagree. I'm more optimistic.
01:44
I think we've simply
made a false assumption.
01:47
Once we fix it, we just
might solve this problem.
01:50
Today, I'd like tell you
what that assumption is,
01:54
why it's false, and how to fix it.
01:56
Let's begin with a question:
01:59
Do we see reality as it is?
02:01
I open my eyes
02:04
and I have an experience that I describe
as a red tomato a meter away.
02:06
As a result, I come to believe
that in reality,
02:12
there's a red tomato a meter away.
02:15
I then close my eyes, and my experience
changes to a gray field,
02:18
but is it still the case that in reality,
there's a red tomato a meter away?
02:24
I think so, but could I be wrong?
02:30
Could I be misinterpreting
the nature of my perceptions?
02:33
We have misinterpreted
our perceptions before.
02:39
We used to think the Earth is flat,
because it looks that way.
02:42
Pythagorus discovered that we were wrong.
02:46
Then we thought that the Earth
is the unmoving center of the Universe,
02:49
again because it looks that way.
02:53
Copernicus and Galileo discovered,
again, that we were wrong.
02:56
Galileo then wondered if we might
be misinterpreting our experiences
03:01
in other ways.
03:05
He wrote: "I think that tastes,
odors, colors, and so on
03:06
reside in consciousness.
03:11
Hence if the living creature were removed,
all these qualities would be annihilated."
03:14
Now, that's a stunning claim.
03:20
Could Galileo be right?
03:23
Could we really be misinterpreting
our experiences that badly?
03:24
What does modern science
have to say about this?
03:29
Well, neuroscientists tell us
that about a third of the brain's cortex
03:32
is engaged in vision.
03:37
When you simply open your eyes
and look about this room,
03:39
billions of neurons
and trillions of synapses are engaged.
03:43
Now, this is a bit surprising,
03:47
because to the extent that
we think about vision at all,
03:48
we think of it as like a camera.
03:51
It just takes a picture
of objective reality as it is.
03:54
Now, there is a part of vision
that's like a camera:
03:58
the eye has a lens that focuses
an image on the back of the eye
04:02
where there are 130 million
photoreceptors,
04:06
so the eye is like a 130-megapixel camera.
04:10
But that doesn't explain
the billions of neurons
04:14
and trillions of synapses
that are engaged in vision.
04:17
What are these neurons up to?
04:21
Well, neuroscientists tell us
that they are creating, in real time,
04:23
all the shapes, objects, colors,
and motions that we see.
04:27
It feels like we're just taking a snapshot
of this room the way it is,
04:31
but in fact, we're constructing
everything that we see.
04:35
We don't construct
the whole world at once.
04:39
We construct what we need in the moment.
04:42
Now, there are many demonstrations
that are quite compelling
04:45
that we construct what we see.
04:48
I'll just show you two.
04:50
In this example, you see some red discs
with bits cut out of them,
04:52
but if I just rotate
the disks a little bit,
04:58
suddenly, you see a 3D cube
pop out of the screen.
05:01
Now, the screen of course is flat,
05:06
so the three-dimensional cube
that you're experiencing
05:08
must be your construction.
05:11
In this next example,
05:15
you see glowing blue bars
with pretty sharp edges
05:17
moving across a field of dots.
05:21
In fact, no dots move.
05:25
All I'm doing from frame to frame
is changing the colors of dots
05:28
from blue to black or black to blue.
05:33
But when I do this quickly,
05:35
your visual system creates
the glowing blue bars
05:37
with the sharp edges and the motion.
05:41
There are many more examples,
but these are just two
05:43
that you construct what you see.
05:46
But neuroscientists go further.
05:49
They say that we reconstruct reality.
05:53
So, when I have an experience
that I describe as a red tomato,
05:58
that experience is actually
an accurate reconstruction
06:02
of the properties of a real red tomato
06:06
that would exist
even if I weren't looking.
06:08
Now, why would neuroscientists
say that we don't just construct,
06:13
we reconstruct?
06:16
Well, the standard argument given
06:18
is usually an evolutionary one.
06:21
Those of our ancestors
who saw more accurately
06:24
had a competitive advantage compared
to those who saw less accurately,
06:27
and therefore they were more likely
to pass on their genes.
06:32
We are the offspring of those
who saw more accurately,
06:34
and so we can be confident that,
in the normal case,
06:38
our perceptions are accurate.
06:40
You see this in the standard textbooks.
06:43
One textbook says, for example,
06:47
"Evolutionarily speaking,
06:49
vision is useful precisely
because it is so accurate."
06:51
So the idea is that accurate perceptions
are fitter perceptions.
06:55
They give you a survival advantage.
07:00
Now, is this correct?
07:02
Is this the right interpretation
of evolutionary theory?
07:04
Well, let's first look at a couple
of examples in nature.
07:06
The Australian jewel beetle
07:10
is dimpled, glossy and brown.
07:13
The female is flightless.
07:16
The male flies, looking,
of course, for a hot female.
07:18
When he finds one, he alights and mates.
07:22
There's another species in the outback,
07:26
Homo sapiens.
07:28
The male of this species
has a massive brain
07:30
that he uses to hunt for cold beer.
07:33
(Laughter)
07:37
And when he finds one, he drains it,
07:38
and sometimes throws the bottle
into the outback.
07:41
Now, as it happens, these bottles
are dimpled, glossy,
07:44
and just the right shade of brown
to tickle the fancy of these beetles.
07:49
The males swarm all over
the bottles trying to mate.
07:54
They lose all interest
in the real females.
07:59
Classic case of the male
leaving the female for the bottle.
08:02
(Laughter) (Applause)
08:06
The species almost went extinct.
08:11
Australia had to change its bottles
to save its beetles.
08:14
(Laughter)
08:18
Now, the males had successfully
found females for thousands,
08:21
perhaps millions of years.
08:25
It looked like they saw reality
as it is, but apparently not.
08:28
Evolution had given them a hack.
08:32
A female is anything dimpled,
glossy and brown,
08:35
the bigger the better.
08:40
(Laughter)
08:42
Even when crawling all over the bottle,
the male couldn't discover his mistake.
08:44
Now, you might say, beetles, sure,
they're very simple creatures,
08:49
but surely not mammals.
08:53
Mammals don't rely on tricks.
08:55
Well, I won't dwell on this,
but you get the idea. (Laughter)
08:57
So this raises an important
technical question:
09:03
Does natural selection really favor
seeing reality as it is?
09:07
Fortunately, we don't have
to wave our hands and guess;
09:13
evolution is a mathematically
precise theory.
09:17
We can use the equations of evolution
to check this out.
09:20
We can have various organisms
in artificial worlds compete
09:23
and see which survive and which thrive,
09:28
which sensory systems are more fit.
09:30
A key notion in those
equations is fitness.
09:33
Consider this steak:
09:37
What does this steak do
for the fitness of an animal?
09:41
Well, for a hungry lion looking to eat,
it enhances fitness.
09:45
For a well-fed lion looking to mate,
it doesn't enhance fitness.
09:51
And for a rabbit in any state,
it doesn't enhance fitness,
09:57
so fitness does depend
on reality as it is, yes,
10:01
but also on the organism,
its state and its action.
10:05
Fitness is not the same thing
as reality as it is,
10:10
and it's fitness,
and not reality as it is,
10:13
that figures centrally
in the equations of evolution.
10:17
So, in my lab,
10:21
we have run hundreds of thousands
of evolutionary game simulations
10:24
with lots of different
randomly chosen worlds
10:28
and organisms that compete
for resources in those worlds.
10:31
Some of the organisms
see all of the reality,
10:35
others see just part of the reality,
10:39
and some see none of the reality,
10:41
only fitness.
10:43
Who wins?
10:46
Well, I hate to break it to you,
but perception of reality goes extinct.
10:48
In almost every simulation,
10:54
organisms that see none of reality
10:55
but are just tuned to fitness
10:58
drive to extinction all the organisms
that perceive reality as it is.
11:00
So the bottom line is, evolution
does not favor vertical,
11:05
or accurate perceptions.
11:10
Those perceptions of reality go extinct.
11:11
Now, this is a bit stunning.
11:15
How can it be that not seeing
the world accurately
11:17
gives us a survival advantage?
11:21
That is a bit counterintuitive.
11:23
But remember the jewel beetle.
11:25
The jewel beetle survived
for thousands, perhaps millions of years,
11:26
using simple tricks and hacks.
11:30
What the equations
of evolution are telling us
11:33
is that all organisms, including us,
are in the same boat as the jewel beetle.
11:36
We do not see reality as it is.
11:42
We're shaped with tricks
and hacks that keep us alive.
11:44
Still,
11:48
we need some help with our intuitions.
11:50
How can not perceiving
reality as it is be useful?
11:52
Well, fortunately, we have
a very helpful metaphor:
11:57
the desktop interface on your computer.
12:00
Consider that blue icon
for a TED Talk that you're writing.
12:03
Now, the icon is blue and rectangular
12:07
and in the lower right corner
of the desktop.
12:11
Does that mean that the text file itself
in the computer is blue,
12:15
rectangular, and in the lower
right-hand corner of the computer?
12:20
Of course not.
12:23
Anyone who thought that misinterprets
the purpose of the interface.
12:25
It's not there to show you
the reality of the computer.
12:29
In fact, it's there to hide that reality.
12:32
You don't want to know about the diodes
12:35
and resistors and all
the megabytes of software.
12:37
If you had to deal with that,
you could never write your text file
12:39
or edit your photo.
12:42
So the idea is that evolution
has given us an interface
12:44
that hides reality and guides
adaptive behavior.
12:48
Space and time, as you
perceive them right now,
12:53
are your desktop.
12:56
Physical objects are simply icons
in that desktop.
12:58
There's an obvious objection.
13:04
Hoffman, if you think that train
coming down the track at 200 MPH
13:06
is just an icon of your desktop,
13:10
why don't you step in front of it?
13:12
And after you're gone,
and your theory with you,
13:14
we'll know that there's more
to that train than just an icon.
13:17
Well, I wouldn't step
in front of that train
13:20
for the same reason
13:22
that I wouldn't carelessly drag
that icon to the trash can:
13:23
not because I take the icon literally --
13:28
the file is not literally blue
or rectangular --
13:31
but I do take it seriously.
13:34
I could lose weeks of work.
13:37
Similarly, evolution has shaped us
13:39
with perceptual symbols
that are designed to keep us alive.
13:41
We'd better take them seriously.
13:46
If you see a snake, don't pick it up.
13:49
If you see a cliff, don't jump off.
13:52
They're designed to keep us safe,
and we should take them seriously.
13:54
That does not mean that we
should take them literally.
13:58
That's a logical error.
14:01
Another objection: There's
nothing really new here.
14:03
Physicists have told us for a long time
that the metal of that train looks solid
14:06
but really it's mostly empty space
with microscopic particles zipping around.
14:10
There's nothing new here.
14:15
Well, not exactly.
14:16
It's like saying, I know that
that blue icon on the desktop
14:18
is not the reality of the computer,
14:22
but if I pull out my trusty
magnifying glass and look really closely,
14:25
I see little pixels,
14:28
and that's the reality of the computer.
14:30
Well, not really -- you're still
on the desktop, and that's the point.
14:32
Those microscopic particles
are still in space and time:
14:36
they're still in the user interface.
14:39
So I'm saying something far more radical
than those physicists.
14:41
Finally, you might object,
14:46
look, we all see the train,
14:48
therefore none of us constructs the train.
14:50
But remember this example.
14:53
In this example, we all see a cube,
14:55
but the screen is flat,
14:59
so the cube that you see
is the cube that you construct.
15:01
We all see a cube
15:05
because we all, each one of us,
constructs the cube that we see.
15:07
The same is true of the train.
15:12
We all see a train because
we each see the train that we construct,
15:14
and the same is true
of all physical objects.
15:19
We're inclined to think that perception
is like a window on reality as it is.
15:24
The theory of evolution is telling us
that this is an incorrect interpretation
15:29
of our perceptions.
15:34
Instead, reality is more like a 3D desktop
15:36
that's designed to hide
the complexity of the real world
15:40
and guide adaptive behavior.
15:43
Space as you perceive it is your desktop.
15:46
Physical objects are just
the icons in that desktop.
15:49
We used to think that the Earth is flat
because it looks that way.
15:53
Then we thought that the Earth
is the unmoving center of reality
15:57
because it looks that way.
16:00
We were wrong.
16:02
We had misinterpreted our perceptions.
16:03
Now we believe that spacetime and objects
16:06
are the nature of reality as it is.
16:10
The theory of evolution is telling us
that once again, we're wrong.
16:13
We're misinterpreting the content
of our perceptual experiences.
16:17
There's something that exists
when you don't look,
16:22
but it's not spacetime
and physical objects.
16:24
It's as hard for us to let go
of spacetime and objects
16:28
as it is for the jewel beetle
to let go of its bottle.
16:31
Why? Because we're blind
to our own blindnesses.
16:34
But we have an advantage
over the jewel beetle:
16:40
our science and technology.
16:42
By peering through the lens of a telescope
16:44
we discovered that the Earth
is not the unmoving center of reality,
16:46
and by peering through the lens
of the theory of evolution
16:51
we discovered that spacetime and objects
16:54
are not the nature of reality.
16:56
When I have a perceptual experience
that I describe as a red tomato,
16:58
I am interacting with reality,
17:03
but that reality is not a red tomato
and is nothing like a red tomato.
17:06
Similarly, when I have an experience
that I describe as a lion or a steak,
17:11
I'm interacting with reality,
17:16
but that reality is not a lion or a steak.
17:18
And here's the kicker:
17:21
When I have a perceptual experience
that I describe as a brain, or neurons,
17:23
I am interacting with reality,
17:28
but that reality is not a brain or neurons
17:30
and is nothing like a brain or neurons.
17:34
And that reality, whatever it is,
17:37
is the real source of cause and effect
17:42
in the world -- not brains, not neurons.
17:46
Brains and neurons
have no causal powers.
17:50
They cause none of our
perceptual experiences,
17:52
and none of our behavior.
17:55
Brains and neurons are a species-specific
set of symbols, a hack.
17:57
What does this mean
for the mystery of consciousness?
18:02
Well, it opens up new possibilities.
18:05
For instance,
18:09
perhaps reality is some vast machine
that causes our conscious experiences.
18:11
I doubt this, but it's worth exploring.
18:18
Perhaps reality is some vast,
interacting network of conscious agents,
18:22
simple and complex, that cause
each other's conscious experiences.
18:27
Actually, this isn't as crazy
an idea as it seems,
18:33
and I'm currently exploring it.
18:36
But here's the point:
18:38
Once we let go of our massively intuitive
18:40
but massively false assumption
about the nature of reality,
18:43
it opens up new ways to think
about life's greatest mystery.
18:47
I bet that reality will end up
turning out to be more fascinating
18:53
and unexpected than we've ever imagined.
18:57
The theory of evolution presents us
with the ultimate dare:
19:01
Dare to recognize that perception
is not about seeing truth,
19:06
it's about having kids.
19:11
And by the way, even this TED
is just in your head.
19:15
Thank you very much.
19:20
(Applause)
19:22
Chris Anderson: If that's
really you there, thank you.
19:32
So there's so much from this.
19:36
I mean, first of all, some people
may just be profoundly depressed
19:38
at the thought that,
if evolution does not favor reality,
19:42
I mean, doesn't that to some extent
undermine all our endeavors here,
19:47
all our ability to think
that we can think the truth,
19:51
possibly even including
your own theory, if you go there?
19:53
Donald Hoffman: Well, this does not
stop us from a successful science.
19:57
What we have is one theory
that turned out to be false,
20:01
that perception is like reality
and reality is like our perceptions.
20:04
That theory turns out to be false.
20:09
Okay, throw that theory away.
20:10
That doesn't stop us from now postulating
all sorts of other theories
20:12
about the nature of reality,
20:15
so it's actually progress to recognize
that one of our theories was false.
20:16
So science continues as normal.
There's no problem here.
20:20
CA: So you think it's possible
-- (Laughter) --
20:23
This is cool, but what you're saying
I think is it's possible that evolution
20:25
can still get you to reason.
20:29
DH: Yes. Now that's a very,
very good point.
20:32
The evolutionary game simulations that I
showed were specifically about perception,
20:34
and they do show that our perceptions
have been shaped
20:39
not to show us reality as it is,
20:41
but that does not mean the same thing
about our logic or mathematics.
20:43
We haven't done these simulations,
but my bet is that we'll find
20:47
that there are some selection pressures
for our logic and our mathematics
20:51
to be at least in the direction of truth.
20:55
I mean, if you're like me,
math and logic is not easy.
20:57
We don't get it all right, but at least
the selection pressures are not
21:00
uniformly away from true math and logic.
21:03
So I think that we'll find that we have
to look at each cognitive faculty
21:05
one at a time and see
what evolution does to it.
21:09
What's true about perception may not
be true about math and logic.
21:11
CA: I mean, really what you're proposing
is a kind of modern-day Bishop Berkeley
21:15
interpretation of the world:
21:19
consciousness causes matter,
not the other way around.
21:21
DH: Well, it's slightly
different than Berkeley.
21:24
Berkeley thought that, he was a deist,
and he thought that the ultimate
21:27
nature of reality is God
and so forth,
21:30
and I don't need to go
where Berkeley's going,
21:32
so it's quite a bit
different from Berkeley.
21:35
I call this conscious realism.
It's actually a very different approach.
21:39
CA: Don, I could literally talk with you
for hours, and I hope to do that.
21:43
Thanks so much for that.
DH: Thank you. (Applause)
21:46

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Donald Hoffman - Cognitive scientist
Donald Hoffman studies how our visual perception, guided by millions of years of natural selection, authors every aspect of our everyday reality.

Why you should listen

In his research to uncover the underlying secrets of human perception, Donald Hoffman has discovered important clues pointing to the subjective nature of reality.

Rather than as a set of absolute physical principles, reality is best understood as a set of phenomena our brain constructs to guide our behavior. To put it simply: we actively create everything we see, and there is no aspect of reality that does not depend on consciousness.

Hoffman is a faculty member at UC Irvine and a recipient of the Troland Award of the US National Academy of Sciences.

The original video is available on TED.com
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