Ep148 "How can we improve political dialog?" with Saul Perlmutter

How can we improve political dialogue, and what does this have to do with the discovery that the universe behaves differently than expected? Why do we cling to beliefs even when evidence pushes against them? What if the biggest problem facing humanity could be solved with practice? Join Eagleman today with Saul Perlmutter, a Nobel-prize winning astrophysicist, but instead of the cosmos we talk about the inner cosmos: why polarization happens and how we might address it with a different kind of thinking.

Episode Transcript

Speaker 1 (00:05):
How can we improve political dialogue? And what does this
have to do with discovering that the universe is behaving
completely differently than expected. Why do we all cling to
beliefs even when evidence pushes against them, What does this
have to do with polarization? And what if the biggest
problem facing humanity could be solved with practice. Today we're

(00:28):
going to talk with Saul Pearl Mutter, a Nobel Prize
winning astrophysicist. But instead of the cosmos, we're going to
talk about the inner cosmos. We're going to talk about
polarization in society and how we might be able to
address that with a different kind of thinking. Welcome to

(00:48):
Inner Cosmos with me David Eagelman. I'm a neuroscientist and
author at Stanford and in these episodes we sail deeply
into our three pound universe to understand why and how
our lives look the way they do, and specifically today,
why we think the way we do, and whether we
can improve our thinking. Okay, so imagine you've spent years

(01:20):
as an astrophysicist, as space scientist working to understand the
universe out there. You've got a bunch of measurements, you
have your instruments calibrated to exquisite precision. You've pulled in
data from stars that exploded billions of years ago, these
little pinpricks of light you can't even see with the

(01:40):
naked eye, and you and your team have worked to
stitch all of that together into a single picture. And
finally you pull all this into one place and you
plot the data, and you look at the curve and
something is off. Let's say it's not dramatically off, but
the data just isn't land in a place that it should. Now,

(02:02):
this is the key moment in science, and it's maybe
not what you expect, because in this situation, you don't
jump up and shout eureka and call a press conference.
What happens instead is that you assume your graph is wrong.
Because what we all learn in science is that if
something looks really surprising, the most likely explanation is that

(02:27):
you screwed something up. So you go back, you check
the instruments, you look at all your assumptions, you tweak
the calibration, you dig really deep to see whether there's
some bias in how you collected the data or some
stupid explanation hiding in the machinery. And you do this

(02:48):
for days, and then for weeks and months, you keep
rebuilding this graph, and it keeps landing in that strange place.
So you refine the measurements and the graph stays. You
improve the calibration, and the graph just sharpens. And then
very very slowly you begin to entertain the possibility that

(03:11):
maybe the graph is right. What if the universe itself
is doing something unexpected, Because you know that ever since
the Big Bang, the universe has been expanding outward. Everything
is rushing away from everything. But the pull of gravity
should be slowing down that expansion over time. Like when

(03:33):
you throw a ball up in the air, it goes
up and then it slows because of gravity, and eventually
it falls back down. So the universe should be slowing
down under the influence of gravity and eventually coming back together.
Except your graph says it's not doing this. Your graph
says the expansion of the universe is accelerating. In other words,

(03:58):
something is pushing everything apart, something we don't understand, something
we now call dark energy. Now, one of the key
figures in this discovery, and who we're going to talk
to today is Saul pearl Mutter at the Lawrence Berkeley National Labs.
And that discovery that the expansion of the universe is

(04:20):
accelerating completely reshaped our understanding of cosmology. And in twenty
eleven Saul was awarded the Nobel Prize in Physics. But
here's the point I want to make right now. His
big discovery came about as a long, uncomfortable process of
eliminating every possible way that he could be wrong. And

(04:43):
that's what scientific thinking is. It's not like what they
teach you in high school science, where they tend to
give science as a collection of facts. Instead, science is
a way of thinking. It's a way of navigating uncertainty.
It's a way way of asking, over and over, how
might I be fooling myself? Now, this is deeply counterintuitive

(05:08):
to how our brains usually operate, because our brains are
evolved to lock onto patterns and construct stories. A whole
bunch of my episodes touch on this point that brains
are always seeking explanations that feel coherent, and once we
have a model of the world, we tend to protect it.

(05:29):
We look for confirming evidence, and we tend to filter
out contradictions. But a scientific mindset asks for something different.
It asks for a kind of intellectual humility. What it
asked for is a willingness to say, look, I might
be wrong. In fact, I'm probably wrong about a bunch
of things, and the only way forward is to keep

(05:53):
testing and keep updating. Now, when we look at the
political world around us, that might mindset of being willing
to be wrong is starting to feel more relevant than ever,
because we are living in a moment saturated with information,
but we struggle to process it. All of us take

(06:13):
really complex issues and smush them down into binaries like
us and them, or good and evil. We all form teams,
we defend our positions, and we treat uncertainty as weakness.
But what if the ability to live with uncertainty is
one of the most powerful tools we have for solving

(06:36):
the mess that we're in. What if thinking in probabilities
and revising our beliefs and engaging with disagreement. What if
this is our way out of the whole. So today's guest,
Saul Pearlmutter, has spent his whole career grappling with uncertainty
at the largest possible scale, but in recent years he's

(06:56):
turned his attention to something closer to home. He has
zoomed in on this issue that scientists every day rely
on a set of thinking tools that aren't always taught explicitly.
In other words, scientists have ways of reasoning about uncertainty
and evidence and disagreement. And Saul asked himself, what if

(07:18):
everyone learned these tools? What if we taught everyone not
just the content of science, but the process of thinking scientifically.
Because the stakes are about how we all make decisions
in a society, how we communicate, how we navigate a
very complex, very interconnected world. So I started this episode

(07:43):
with a conversation about a graph that didn't make sense.
But today's show is really a conversation about how we
come to believe something that overturns our expectations. And ultimately,
it's a conversation about how a species standing on a
small planet under and expanding universe might learn to think

(08:03):
just clearly enough to build an excellent future. Here's my
conversation with Saul Pearl Mutter. Okay, so, Saul, let's start
when you discovered that the expansion of the universe is accelerating,
When you first got this idea about dark energy, What

(08:25):
did that moment feel like intellectually? Was it excitement, skepticism,
disbelief because of other things that you'd thought previously.

Speaker 2 (08:33):
I think what people may not realize about the life
of a research scientist is that most of the time
you're trying to figure out what's broken. That most of
the time you're trying to figure out, you know, okay,
what's wrong with my current setup, what's wrong with the
data that I just brought in? If you're really lucky,
you're trying to figure out what's wrong with the fundamental understanding.

Speaker 3 (08:52):
Of the universe.

Speaker 2 (08:54):
But that's that's really lucky, you know, if you get
to that point. And so when we first started data
that suggested this kind of unusual result, the first assumption is, Okay,
we're lucky that we've managed to piece all the parts
together and we got a graph at all. Now we
have to figure out, you know what, what parts of

(09:14):
the graph to trust, what things we still have to recalibrate.
And you just don't take it at all seriously when
you when you first see it, you're just happy you
got a graph. It's you know, there's so many different
elements of the story that you had to pull together,
and so much data had to be collected, and you were,
and you're so many calaborations that you had to do.
Then the hard work starts that you're starting to work
on the next you know, part of the hard work

(09:36):
of trying to figure out what do you believe? And
finally what happened after months and months is that the
data kept sharpening up, looking stronger and stronger as we
understood and calibrate everything, and it was starting to stay
in this rather odd place that suggested the universe was
not doing what we expected. It wasn't slowing down as

(09:57):
expansion as you would expect gravity would slow it, but
it seemed to be speeding up. And this is saying
that finally, after months and months, we start to believe Okay.

Speaker 3 (10:08):
That's probably the answer. We're going to have to go
public with this.

Speaker 2 (10:12):
But so the moment of AHA is a little bit
hard to describe, right because it's not a AHA moment,
you know, that instant, It's AHA spread out over seven
eight months and so but by the time you finally
believe it, it's no longer a big surprise.

Speaker 1 (10:29):
So the most interesting discoveries in science are often the
ones that contradict our expectations. And so how does the
scientific process train people, and you, in particular in this case,
to embrace having been wrong and having a new model
of something.

Speaker 2 (10:46):
Once you having in your mind that you're that most
of what you're doing is trying to figure out what's
broken and trying to build up confidence in different pieces.
In some sense, the idea that something is wrong with
the big watching theory is is a part of the game.
It's it's it's kind of what you're trying to do.
You're trying to figure out can we sharpen up our

(11:07):
understanding of the world and can we figure out, okay,
which part have we not quite got right yet? And
for the community as a whole, the huge excitements are
whenever you figure out something that we all had thought
was the case and now we figured out something new
about it.

Speaker 3 (11:23):
But your career is.

Speaker 2 (11:24):
Based on as a sciences it's based on really doing trustworthy,
very careful work so that people trust that the results
that you're doing aren't just what you hope they would be,
they're actually what you find and that you are checking
for everything you could that could be a mistake.

Speaker 3 (11:41):
And so that's where all this comes from.

Speaker 2 (11:43):
That that that that ability to convince people that you've
really looked for your own mistakes, and in some sense
probably it's the reason that science has had to learn
how to work with people you disagree with, because they're
the ones who are going to help you find your
mistakes most effectively. I mean, I can say in their
particular case we had, there was a rival team that

(12:07):
started working after we'd started this project. They started racing
with us, using the very very similar techniques to get
the result, and it was a very fierce competition. But
that actually is what helps you. The fact that you
have a group that's going to try to figure out
where you're making your mistakes and you're trying to figuret
where they're making their mistakes.

Speaker 3 (12:28):
It's one of the best.

Speaker 2 (12:29):
Ways to make that kind of guarantee that you've really
hunted for where the problems are.

Speaker 1 (12:36):
A lot of people when they hear about dark energy
and dark matter, they interpret that as ignorance, but scientists
interpret this as progress. So why if your goal.

Speaker 2 (12:46):
Is just to prove things you already know, then it
sounds like it's a big step backwards if you found that, oh,
what we thought was true is wrong. But that's so
much not the philosophy of what you're trying to do
in the sciences. In the big picture, you're trying to
you're assuming that there are things that we don't understand,
and you're trying to figure out what they are. And

(13:07):
so it's a huge success when you figure out that
there's something that we had misunderstood and that now we've
honed in our home di in on our understanding just
a little bit more.

Speaker 3 (13:19):
So.

Speaker 2 (13:19):
This is the kind of thing that just you know,
the scientists week up in the morning hoping they do
someday they figure out something that overturns a piece of
the puzzle, and that that's really where the excitement is.

Speaker 1 (13:31):
So you in your career sat in your lab and
in meetings and you realize that scientists seem to be
using a set of of course thinking tools that maybe
the rest of society could benefit from. And so you
about twelve years ago started a course at Berkeley tell

(13:53):
us about that.

Speaker 2 (13:55):
Yeah, So I was I think I was watching some
political debate. This is you know, even before all the
current uh you know, particularly strong polarization. But it's one
where I think they were trying to figure out what
was the right level to set the debt ceiling or
something in one of these earlier periods, and and it
wasn't a particularly uh you know, vociferous, uh you know,

(14:17):
a moment. But even so, it struck me that the
style of the conversation didn't look at all like the
style of conversations I saw at the lunch table of
a bunch of scientists talking about almost any topic, and
it included things like that probabilistic thinking that I just
you know that we just discussed. There are all these
different just parts of the vocabulary of how people talked

(14:38):
that were I felt very good at helping think through
a problem rationally and be able to handle just the
the logic of the question in a way that I
thought was missing. Uh, when you saw our society asking
just a cold question about what is the right level
to set a debt in a in the debt ceiling
in a society, that's not a it's not an emotional question.

(15:02):
It's just a question of what works best. And yet
you're not hearing any of that kind of thoughtful discussion
that you would see around any bunch of scientists, just
using the terminology that they would use. So I found
myself asking, well, where is it that these that this
terminology comes in. I mean, it's not like we're taught
it in any physics, biology and chemistry course that I

(15:24):
know of, and uh, and I realized that it was
taught sort of by osmosis. By as people go through
a training as a research scientist, working with other scientists,
they start to learn this vocabulary of ideas, and it
just seemed to me that it would be really useful
for everybody to know about it much much earlier, even
if they were going to be scientists, they should learn it,
learn it like directly, not just you know, little by

(15:46):
little through what people say. And then people are not
going to become scientists, they should be using this all
the time. It's it's just a very useful way to
have an approach that helps you think through problems in a.

Speaker 3 (15:58):
In a very effective way.

Speaker 2 (16:00):
Hey, for almost anything you do day to day, and
for any business decision, any medical decision, any you know,
personal decision, this could all be useful.

Speaker 3 (16:10):
So that's what picked off this this idea for the course.

Speaker 1 (16:12):
And so you hooked up with a couple of your
colleagues and you started thinking about what are the scientific
tools that could be useful for public conversation and as
the starting set. You came up with twenty three of them,
so give us a flavor of what sort of ideas
would be useful.

Speaker 2 (16:29):
Absolutely, and I should mention that my colleagues John Campbell,
philosopher and Rob mccoonn, a social psychologist in the Public
Policy School, that I thought it was really important to
bring people from other parts of the university together because
as a physicist, you know, it's not like we have
a monopoly on all these thinking tools, and that you
want to try to bring the best of you know,

(16:50):
what everybody's been coming up with. And we actually put
a sign up asking people come work on the on
the on this developing the course, saying signing, you know,
are you embarrassed watching our society make decisions? Come help
invent the course and come help save the world. And
about thirty people started showing up, like every week at
the end of Fridays we would hangk We would be

(17:11):
there for a few hours before dinner, trying to come
up with you know, what would a set of concepts
look like that would be helpful for everybody to have.
So in answer to your question, I mean, these some
of the concepts where things like propositions are probabilistic. We
we know them, just as we were saying before, you
know some that we know for real strong certainly ninety

(17:31):
nine point nine nine percent, some sixty percent. Other concepts
were ideas like, when you look to understand patterns in
the world and signals in the world of of what's
going on, it's very easy for our brains to see
patterns that are just random noise, that things that will
randomly to us appear like there's ah, we've suddenly just

(17:55):
detected you know, a A this relationship, this is causing
this a huge fraction of the time, and it's easy
to see that humans will just see a pattern that
is not really there. It's just the random events look
like a pattern to us because our brains are such
good pattern finders. So that concept led to the idea

(18:18):
of you know, what are the elements that we've learned
about how do you differentiate those kinds of mistakes? And
these are the issues of false positives and false negatives.
You know, when is it dangerous to think you seeing
a pattern that's not there? But when is it dangerous
to miss a pattern that really is there? And how
do you balance those and what's the right order of
techniques that people have developed to handle those. So these

(18:40):
are three concepts you have to start with. Many of
the concepts are very much these cautionary ones, how to
avoid fooling yourself, because so much of science is built
around the idea that we tend to fool ourselves, and
so we're constantly having to develop these techniques to avoid
doing it again. But there are other unbalancing concepts that
we each which are techniques for keeping going and for

(19:03):
some sense of optimism and forward motion despite all that
cynical uh you need to avoid to avoid another chance
to you fool yourself. And so some of the concepts
include things like the idea that scientists have really as
a culture, developed a capability to have some confidence that

(19:25):
you can solve a problem, and therefore you stick to
it long enough to actually solve it, because most people
give up way too soon or in a difficult problem,
and that this is just a trick of the trade,
is to have a little bit of an arrogance just
long enough to be able to get you to the
point of actually being able to take on big problems.

Speaker 1 (19:57):
So let's step back to the first issue you mentioned
about probabilities. So how did this come up at the
beginning of the pandemic? What happened in terms of public
communication of scientists to the public. That's where the issue
of probability started. Really the interface had a lot of
friction there.

Speaker 3 (20:15):
Now now here.

Speaker 2 (20:15):
I feel like there was a real missed opportunity because
and I should say before I say anything else, I
should say, if you are a public official and you're
in a position that you suddenly faced the pandemic, it's
really difficult, right, I mean, I can and so people
making mistakes. I feel absolutely no you know, sense of
you know, smugness. Though I would have done better. I'm

(20:38):
sure that I would have done worse because it's really
difficult to figure this out, But in armchair quarterbacking watching.

Speaker 3 (20:44):
It, you know, from the outside, I would say that,
you know, there was a moment where you had a
choice of being absolutely.

Speaker 2 (20:55):
Confident about what it was you were going to tell
the public to do, and I think that ended up
being a trap. That you should not claim a confidence
that you don't actually have, and that you should put
up with the fact that some people may be a
little less willing to follow you in exchange for a
really strong sense of honesty about here is what we

(21:19):
know and here's what we don't know, and we are
going to play the odds. And when I said I'm
chair quarterbacking, I realized that actually the metaphor of football
plays could have been really useful that I think it
would have been a moment to leveled with the public,
and I think that people could have listened if you said,
we are about we're in a football game with the virus.

(21:41):
We don't know its plays, it doesn't know our plays,
but it will try to adapt to our plays. We're
going to try to get ahead of it and go
with a better play depending on what we see it doing.

Speaker 3 (21:53):
And so every week, every two weeks.

Speaker 2 (21:55):
Every month, we're going to tell you what our latest
play is, and then we're going to play it as
best we can and we're going to win this football game,
you know. Whereas if instead you say we're going to
come up with, you know, here's the rule. This is
what you guys should do from that on, and then
a month later you have to change it because now
we known something different. People say, well, you keep changing
your mind, how do I know what to follow? But

(22:16):
if you tell people this isn't a you know, a
one off thing. You know, either we're right or wrong.
This is a constant update that we're going to figure
out its plays and then we're going to do our plays.
People would get it, I think, and I think they
would follow you as you updated the recommendations as we
learn more.

Speaker 1 (22:35):
And part of the idea here is that generally the
world doesn't think too much in probabilities, but in sports
they do, right, That's that's your point here, naturally, Yeah, exactly.

Speaker 2 (22:46):
And you know this is those things where you know,
we often feel like, oh, well, how could the public
probably possibly follow something so complex. The answer is they
do it all the time in certain situations, and so
all we need to do is have them recognize that, oh,
this is another situation in which we have to use
that muscle that we that we have, that that thinking tool,
and you know, we we understand it, you know, in

(23:08):
a sports context. Now we have to use it in
this medical context. It's a little bit unusual, but it's
really the right it's the right answer.

Speaker 1 (23:15):
That's right. And and people, all of us often treat
complex problems as binary. Why do you suppose we're so
attracted to yes or no answers?

Speaker 2 (23:25):
I mean I've been trying to think about that a lot,
you know, as we've been discussing these topics, and to
some extent, I think we have all of us have
a little bit of the child in us where we
sort of remember those days in which our parents knew
the answers and where, you know, if we weren't sure
about something, our parents would say.

Speaker 3 (23:43):
Something and we feel we'd feel safe.

Speaker 2 (23:45):
And I think we're all looking for that sense of Okay, well,
let's just go find the person that the authority. They'll
tell us it's right or it's wrong. They'll tell us
what to do, and and that's it.

Speaker 3 (23:55):
But you know, the world isn't isn't that way.

Speaker 2 (23:57):
We grow up and we realize that actually many things
are balancing acts, and many things we have to figure
out how to play the numbers and play it and
play it as best we can. And that's where our
success comes from, that sense of being able to go
with what we learned. I mean, the other metaphor that
I've been thinking about was, you know, you wouldn't want
to try skiing down a hill by just locking your knees,

(24:22):
putting your weight in one position and then just going
you actually shift your weight. You move things depending on
what the bumps and terrain are doing. And nobody would
expect to make it down alive if you just were rigid.
You know, all the way down a hill, you're reacting
to it. And that's what we're very good at. I mean,

(24:42):
humans are quite good at that if they know that's
what their job is.

Speaker 1 (24:45):
By the way, this thing you said about parents and
being able to give you answer, you know, Sigmund Freud
famously argued that this is why we have religion, because
when you're a baby, you've got these two giant creatures
that care for you when you're in pain, they feed
you when you're hunger, and eventually you grow up and
that goes away and you need a replacement. I'm not
saying this as an indictment of religion, but I think

(25:07):
that's interesting to think about this issue of what we
lose as we age and how we yearn for that
kind of simplicity. Let me come back to this issue
about our imposition of a model on random noise. One
thing that's interesting is what we're doing is we're each
taking our internal model and imposing it onto the random noise.

(25:30):
Let's say in the political world we're talking about. We
see some new stories, some headline, and depending on our
neighborhood and culture and politics and whatever, we see that
story and we say, ah, this one case is an
example of this much larger thing. So how could we,
given that we're all yoked with our internal models that

(25:50):
we've developed over our whole lifetime, how might we be
able to see a little further beyond the fence lines
of that.

Speaker 2 (25:57):
So this is a among the different conceptual ideas that
we've been talking about that we that we all need
to use as our tools. One of them, of course,
is that real understanding of the fact that we have
a tendency to fall into confirmation by us right, that
we will tend to look for information that will back
up our position that we already have and supposed to

(26:18):
look for information that will disconfirm it, and once somebody
happens to give us information, will be much more skeptical
of the information that goes against something that we believe
than information that is just backing up some that we
that we believe. And that knowledge that that's what we do,
I think is a really important element of scientific thinking

(26:39):
of this, of the kind of describing because, among other things,
that it's one of the reasons why we've learned in
this culture of science to go work with people that
we disagree with, that we go to conferences, we send
our papers in for review, and people give us.

Speaker 3 (26:55):
A hard time, and that's their job.

Speaker 2 (26:57):
There's supposed to be not our best friends for this purpose,
they're supposed to be our best enemies, right, you know,
I mean to put it in a strong terminology. Their
job is to figure out where the weaknesses are of
what we're saying. And it actually is something that we
learned from and in the science is nobody enjoys when
they get criticized, but they take it in and they

(27:18):
actually try to improve their thinking by In the political context,
it seems to me that the analogy that we've been
really losing track of is that there's a reason that
we would have a loyal opposition. There's a reason that
we want to have people who are disagreeing with us
in the room when we're making policy. And it's because

(27:39):
there's no way that we're not making mistakes. We must
be making mistakes. It's inherent in how complex the world
is and how much we're trying to figure out and
to think that we will have a policy that must
be right is bound to be leading us into danger
zones of one kind or another. And one of the
best ways to get at that is to have people

(27:59):
who are going to disagree with the policy in the
room giving you a hard time. And I think that
we've lost that. One thing that our current society has
perhaps really not taken advantage of is the possiblity of
having good conversations with people who disagree with you and
try to work through. Okay, if I were born twenty
five miles away from where I was born, I would

(28:21):
probably believe everything you believe. Right, It's pretty clear when
you just look at the maps of where people live
and what they believe that you know, it can't be
the case that I'm amazingly right about everything I believe.
And if I happen to move twenty five miles away
and that's where I lived, I would be right, you know,
with some other point of view.

Speaker 3 (28:41):
That can't be you know, the.

Speaker 2 (28:42):
Whole story, and so we I think we absolutely need
to find ways again to become part of a single politics,
you know, where people consider it to be important type
of conversation and not scary that they actually enjoy trying
to figure out. Ah, you know, if I believe that
one little piece that you believe, I would switch sides.
I'd be on your side, and they ideally would say

(29:04):
the same thing. The would say, you know, if that
other thing you just said it was true, I would
I would be joining you. And you can't find that
out unless you have a conversation. And once you find
that out, you still have another job to do, which
is together try to figure out, Okay, which of those
facts is true, if that's the issue, or which of
these our priorities do I do want to lean into

(29:25):
if that's what's differentiating you.

Speaker 3 (29:27):
But it doesn't happen unless you have that conversation.

Speaker 1 (29:30):
Scientists really have to train themselves out of this instinct
because the fundamental intuition for all of us is that
when something contradicts our beliefs, we have to double down
on that. So how do scientists get themselves out of
that instinct?

Speaker 2 (29:48):
I think it's partly a question of where do you
put your pride, and that the ideally what you want
is to not have your pride in always being right
in everything that you currently believe. That your pride should
be in being very capable of understanding which are the
weak parts of what you currently believe, which parts are
more likely to need to be revised, and pride in

(30:10):
showing off the fact that you get a real kick
out of learning something new that you didn't know before,
and that that's really where your sense of ego lies.
And I think that's the funny shift that science helped
people do. And I should say it's all I'm describing
as aspirational. It's not that the scientists individually always do
this right. All of us fall into all these traps

(30:32):
of confirmation bias and doing it wrong all the time.
It's that the culture helps us not always do that.
It helps us be able to sometimes show off our
excitement about finding out that we were wrong on something
and that there's something else going on here that somebody
has shown us. And the best of all is times
when you find yourself that you're wrong, because that you

(30:53):
can show.

Speaker 3 (30:53):
Off you know how you did that.

Speaker 2 (30:55):
But I think it's something that you are taking advantage
of a culture helping you shift this natural human tendency.

Speaker 1 (31:04):
So let me ask you this. When we look at politicians,
if they change their mind, that usually loses points for them,
and people call them wishy washy. This you know, changing
your mind in science is a badge of honor. How
could that spread more widely outside the Ivory Tower.

Speaker 2 (31:23):
Well, this is the saying that you know, I've been
very much interested in asking, is it possible that if everybody,
you know, every in high school right is supposed to
be learning a little bit of you know, physics and
chemistry and biology. You know, people are supposed to have
just enough of that, whether or not they're going to
go onto the science, is just enough so they can

(31:43):
recognize what it is that we know about the world,
and they can understand a little bit what's happening when
scientists report what they're learning.

Speaker 3 (31:50):
For my money, I would rather trade in a little.

Speaker 2 (31:54):
Bit of the content of physics, biology and chemistry in
exchange for some of this scientific thinking how do we
think through problems? Because I think that would really help
us be able to build a society where people, you know,
when they see one politician who's saying to them, you know,
this is a place where we do not know the answer.

(32:16):
We're going to come up with an iterative way to
get the answer. We're going to try this policy if
it doesn't work, We're going to update it with this policy.
I want to build a society where people say, oh,
that sounds a lot like how you think through a
problem that I learned in high school, as opposed to
saying that, well, that person sounds wushy washy, you know,
And that's I think the long term goal.

Speaker 3 (32:37):
Now, short term obviously.

Speaker 2 (32:39):
You want to you want to have lots of people
watch your podcast and try to get this out into
the world, even now for those people who did not
get in high school, just as they're reminded that there's
something that's been very, very effective. I don't think we
would have airplanes and GPS, and we wouldn't be able
to go to the moon, and we wouldn't have all
these capabilities if we didn't have this culture. And if

(33:02):
people recognize how effective it is, I think they would
also feel, like, you know, if they're running a company,
the company should just should adopt this more actively as
a culture and as a society. Hopefully then people would
start looking for it in their politicians.

Speaker 1 (33:16):
Okay, I love that. One thing we see though in
society is that disagreement tends to be very tribal, and
it strikes me that the difference might be I don't
have time to really get the data about the debt
ceiling and this issue and that issue, and so it's
easier in a sense to say, look, my skin isn't
attached to you know, what happens in this war or

(33:40):
that thing over there on the other side of the planet,
and so I'm just going to go with my team here.
How do we move things away from that.

Speaker 2 (33:50):
I've been very impressed at the few places where people
have come up with techniques that seem to get beyond
that team playing. So there are these techniques of like
deliberate A polling is one term that people were using.
Citizen assemblies is another term of people I'm described where

(34:12):
if you structure it correctly, you bring together a truly
random set of the population, you know the way a
jury does, and you organize how they will start to
deliberate on some questions and topic where they are supposed
to collect all the places that they don't know the
answer as they're talking, and then they have a team

(34:33):
of a panel of experts available to them that represent
people who do know a lot about these topics.

Speaker 3 (34:40):
They may disagree with each other, but the jury.

Speaker 2 (34:44):
Of citizens can interview them and try to figure out
what they believe and then go back and continue deliberating.
And the experience that people have had when they've done
this is that people don't get locked into their tribal
associations the way they would ordinarily.

Speaker 3 (34:59):
Now they feel they're a.

Speaker 2 (35:02):
Group that's working together to get an answer, and their
job is to figure it out together. And apparently people
identify with each other much faster when they're in that
sort of situation and they try to figure out without
their badging and their their sense of you know what
team they're on getting in the way. Doesn't always work,
but it seems to be a very effective technique when

(35:23):
people have tried it.

Speaker 1 (35:25):
What other principles could we take from scientific practice to
reduce polarization?

Speaker 2 (35:30):
So there are a number of things that we do
know that that can be helpful in this. One is
that it clearly makes a difference if people have friendships
and activities that they're doing with other people and then
discover that they disagree on something, because then they feel
like they know each other, they know that they're not
bad people, they're not trying to hurt anybody, and they

(35:51):
want they want good and so then they're more able
to talk to each other.

Speaker 3 (35:55):
And so I think it does.

Speaker 2 (35:57):
Make a big difference if we have people societ where
people are finding lots of ways to tie to each
other music and sports and art, and you know, there
are many ways that people can you know, hiking here,
there are many things that people can do where they
start to feel like they have a tie and then
they're able to have a conversation.

Speaker 3 (36:13):
So that's that's an element of the story.

Speaker 2 (36:16):
I think there's another element of people really using the
scientific ability to be curious that you want people to
be thinking, not that their job is when they find
somebody to disagree with. Their job is never originally to
convince them that they're wrong. Their job is to talk
to them and try to figure out with this real curiosity,

(36:36):
what is it that is leading you to your position,
and how how could I be in your position?

Speaker 3 (36:42):
What would make me agree with you?

Speaker 2 (36:44):
And I think that's the kind of thing that is
a much more open starting point, and it makes it
much more possible for people to have a real interesting
conversation without getting angry at each other.

Speaker 1 (37:08):
Do you see ways that we could structure conversations or
institutions designed explicitly around this scientific style of having structured debate.

Speaker 3 (37:19):
Oh absolutely.

Speaker 2 (37:20):
I mean, you know, I'm always a little wried about
the fact that the only thing that people know about,
for a like, what do you do in school if
you want to get people to have a discussion about
some problem, is you have them do a classical debate
where they have to take a position and stick to
it no matter what. I would love to see basically

(37:41):
a deliberation society as opposed to debate society in out
in the world and in schools, where the goal is
to figure things out together and come to some common
understanding and figure out what would actually make everybody feel
good about the solution rather than to win. And I
think that would actually be very interesting experiment, just to

(38:03):
do that in the school so that people got used
to it as a different style to start with. I
think in real life, you know, I'm uh, you know,
if you don't count school, let's say adult life. You know,
I would be very interested in trying to set up
more activities that felt like they encouraged this kind of
thing and that people had models of it to watch.

Speaker 3 (38:24):
So I was imagining I was supposed to.

Speaker 2 (38:26):
Set up a like a reality game show where you
where you watched pairs of people who disagree with each
other together do a learning journey where they go and
interview people, they talk to people, they have to do
everything together until they come to some common conclusion about
what what they believe about something and see.

Speaker 3 (38:45):
What would happen.

Speaker 2 (38:45):
I bet it would be kind of fun to watch,
uh if, if, if it was you know, played right,
you know, But in general, I do think this is
one of the jobs of our society right now to
ask And the reason I'm bringing this up, you know,
as a focus, is that we're really good as a
society at solving problems once we identify the problem. And

(39:07):
you know, generally it's amazing the scale of.

Speaker 3 (39:10):
Problems that we can now handle.

Speaker 2 (39:12):
I mean, when when I was a kid, you know,
two thirds of the world was going to bed hungry,
and apparently that's now down below like eight or nine percent,
and the population has what tripled or more, you know
since that time, and we know, nobody thought we could
solve that problem of world hunger. And yet once you

(39:32):
understand the problem, people can take it on. Today's biggest problem,
I think is this problem of polarization and inability to
think through problems together. And I think once we've identified
that problem, now our job is to come up with
the techniques and the solutions that will get people into
conversation with each other so that they can solve problems.
I think if we do that, we're home free. I'm

(39:54):
not really afraid of, you know, pandemics. I'm not afraid of,
you know, even comments hitting the earth and wiping out
the population the way they know it wiped out the
dinosaurs or all that.

Speaker 3 (40:05):
I mean, we are amazingly capable.

Speaker 2 (40:07):
But the one last technology that we have to learn
and the last problem we have to solve is this one.
Developing these techniques for getting people into useful conversation with
each other. And we've seen great patterns, so I'm not
worried about it being impossible to do. It's just that
we have to take that on and do it, and
we have to take it on while we're developing new

(40:28):
technologies like communication capabilities of the Internet, like the conversational
capabilities with AI. All these things have to be used
now for answering this last question. And if we do
this one, then I think we're we're in great shape.

Speaker 3 (40:44):
Oh.

Speaker 1 (40:44):
I love that I couldn't agree more. I want to
come back, just for one second to this issue about
debate and how when kids learn debate in high school
it's all about winning. There are interestingly, for example, there's
a there's a Reddit channel where people debate each other,
but the goal is to change the other person's mind,
like any debate, but the person explicitly says, okay, I

(41:07):
give you a point for that. You changed my mind.
Here's a karma point for that. And so then people
try to rack up as many points as they can,
and that's kind of lovely because it ends with this
thing of hey, you changed my mind. Now. What happened
is a Swiss research team about a year ago released
some AI bots that ended up doing six times better
than humans on this front in terms of changing other

(41:29):
people's mind. And of course everyone lost their minds and said,
I can't believe there were ai bots that were doing this.
But the really interesting lesson that nobody talked about was
that the AI bots did not do anything in terms
of misinformation. They simply presented their arguments more empathically and
calmly and rationally, and it changed people's views on particular things.

(41:54):
And I think there's a lovely lesson there about how
we might actually become better humans by looking at a
in analogy to how we've done that with chess and
go and other things, by learning how to present arguments
well and how to change our own minds, which I
totally take your point that that's missing in high school debate.

Speaker 2 (42:13):
Now, love, I love I love that example, and uh,
and I've really enjoyed that the fact that there is
that reddit, uh, both.

Speaker 3 (42:20):
The original one and the and this story.

Speaker 2 (42:22):
Now, it'd be fascinating to know something that I that
I don't know the answer to, which is if we
look at how the the bots were doing this, were
they bringing in a unfair sample of the facts and
managining to calmly change people's mind using a distorted subset

(42:43):
of facts?

Speaker 1 (42:44):
Apparently not?

Speaker 3 (42:45):
Were they winning?

Speaker 2 (42:46):
Okay, so they were winning because they were actually helping
people touch reality. And if that's the case, that's of
course what we would love to keep using.

Speaker 3 (42:54):
More and more of. And I and I. Another example that.

Speaker 2 (42:58):
You're described of what you're describing was this study that
was done where they tried to ask they had conspiracy
theorists talk to a bot and the conspiracies. These were
actually known to be false conspiracies, but they found that
the conspiracy theorists were much more open to possibly being

(43:18):
wrong after they'd had this conversation with the butt. For
the I think like only like four exchanges of a
few minutes each, and I thought that was a really
another good example where the fact that they it was
a calm situation where they didn't feel any ego involved
in the interaction help them just ask, well, but rationally,
what do we know about the world? Is it possible

(43:39):
this is right as possible is wrong? And I think
that that is something that we can learn from the
fact that we have other thinking tools to play with,
like the AI. Now, it could go wrong in many ways.
You could imagine it being used to make trouble, but
I think this is one of these places where we
really would like the AI researchers to be putting their hats,
their thing hats on. From the point of view, what

(44:01):
do we do to build something that will help everybody
deal with reality in a much more direct way?

Speaker 1 (44:07):
Yes, because a lot of conspiracy theories, I think a
piece that's often overlooked is the social aspect to conspiracy theory.
So if I tell you my big theory about the
moon or JFK or whatever, I get to be the
guy who knows something and I'm telling it to you,
even if you disagree with me. I get to be
smarter than the rest and so on. But if you're

(44:30):
talking to a bot, as you said about the ego,
all that stuff is gone. I'm not trying to prove
something to the bot. I'm not getting the social reward
for convincing the bot that I'm smarter than they are.
So I'm more open to listening. I think there's a
real opportunity there as you do.

Speaker 2 (44:46):
Absolutely and probably one of the reasons that you really
don't necessarily want the butts in the end to become
too human in these interactions. You want them to stay
just clearly not human enough, long enough so people can
have a thoughtful station with them without feeling there they're invested,
you know, in in being right, you know, in the

(45:07):
same way they would if it was a human.

Speaker 1 (45:08):
Yes, okay, so I want to zoom the camera back out.
Your physics work deals with the largest scales imaginable to
studying the universe. Change the way that you think about
human disagreements on Earth.

Speaker 2 (45:22):
I had a violin teacher who I stayed with for
you know, a big chuck of many people do with
with the music. Teachers stay with a big shock of
your life, and they're very you know, it's very influential
in terms of your philosophy of life. And I remember
her telling me a story once about the fact that
her father used to take her and her sister out
at I think it was like once a week out

(45:43):
to look at the stars and to and to talk
about astronomy.

Speaker 3 (45:46):
And she said that years later, when she grew up,
she asked her father, what was that all about.

Speaker 2 (45:50):
You know, you're not particularly a huge astronomy fan, and
and you know it's not in keeping with everything else
you do, and he said, oh, I thought it was
really really important for you to not have a narrow
view of of the world, to be able to see
see the larger context of things. And to some extent,
I think one of the real pleasures of doing things
like cosmology is it brings everybody together around something that

(46:13):
we enjoy thinking about. And but it sets a sense
of scale that you know, we are, you know, just
a part of a very rich world that we live in.
And uh, in some sense, you know, that we should
be thinking of ourselves as what is it that would
make make us special and and and and give us
an interesting role in in this uh cosmos, that that that.

Speaker 3 (46:37):
We would like to feel proud about.

Speaker 2 (46:38):
We'd like to feel like we're building a world that
we'd like to that we you know, that that we
would feel.

Speaker 3 (46:43):
Represented something important and meaningful.

Speaker 2 (46:45):
And it's kind of interesting to do that in the
face of the idea that we're such a small corner
of such a small uh you know, galaxy in such
a you know, small cluster galaxies and such a gigantic
universe that that you could feel like, where where is
the meaning at all? But for me, it actually feels
a little different. It feels like it gives us a

(47:08):
sense of that we're unusually able to look out to
this outer world. We're able to look into the inner
world of the fundamental particles. As physicists, that's then that
we care about a lot as well. And somewhere in
that nestled amidst all these different skills, we exist and
we have the possibility of building something that feels meaningful.

(47:28):
And so for me, it actually allows you to step
way back think of the big picture and yet also
feel like you're you have a responsibility out there to
do something, to do something good.

Speaker 1 (47:40):
So when you think about the future of humanity scientifically
and culturally and technologically, do you feel optimistic?

Speaker 2 (47:47):
Well, I should admit to start with, I tend to
be an optimist in these respects and maybe for no
for no fair reason, and you and I can easily
just you state that ahead of time. However, I will
also say that I think we have lots of good
reasons for optimism.

Speaker 3 (48:03):
I feel like we have.

Speaker 2 (48:05):
Solved one problem after another that looked unsolvable. That once
we know about a problem, we are as a group
now individuals sometimes yes, sometimes no, but as a group
we are amazingly capable. And that when you put a
group of people together in a healthy, positive mode where
their job is to disagree and work together, but they're

(48:26):
going to solve a problem together, they I have not
seen problems that they have not been able to solve,
you know, and that you would never have imagined that
they could solve.

Speaker 3 (48:36):
So that's for me, the source of optimism.

Speaker 2 (48:39):
It's always a scary moment, right because you know, we're
aware of all the things that can go wrong, and
we're also aware that at the moment we're not very
good at getting on the same page, and we could
easily hurt ourselves hurt each other if we can't do
better than we are at this instant. But in the
big picture, stepping back, we've come together after many times

(49:01):
where we've fallen apart as societies, we've come back together
and we've managed to build things. And I think that's
we just have to do it again. And I think
that's why I'm optimistic, because I think that we've done
it before, we can certainly do it again, and we
have all the tools we need. That's not the problem.
I think we just need to get everybody able to

(49:21):
think together and not feel too married to everything they
believe being having to be right, but being able to,
you know, enjoy walking around the problem with some other people,
just long enough to solve it.

Speaker 1 (49:31):
So if you fast forward one hundred years from now,
what do you hope humanity has figured out that we
haven't yet.

Speaker 2 (49:38):
If we manage to pull this off, if we manage
to get ourselves into a mode where we're actually thinking,
even it doesn't have to be everybody, but even just
enough of a core of people who are trying to
solve problems together. I imagine that we'd be living on a
planet where we're what we're really worrying about is how

(49:59):
do we make sure that everybody on the planet is healthy,
is given the opportunity to be creative and to and
to work on things besides just bears since survival, that
they're actually being able to think about what kind of
questions would they'd like to ask, what kind of creative
projects would they'd like to work on. I think it's

(50:20):
perfectly possible of if we did this right, that one
hundred years from now, that would be the challenge that
we say, oh, look, we just found that, you know,
we've gotten the kind of right in these parts of
the of these countries.

Speaker 3 (50:33):
Now we just have to get you know, the the you.

Speaker 2 (50:35):
Help this group over here that hasn't quite figured out
how to do it, they have some good ideas how
they would like to do it.

Speaker 3 (50:41):
Let's give them a hand.

Speaker 1 (50:42):
You know.

Speaker 2 (50:42):
I feel like we could be in that position where
we were looking around and asking, you know, where are
the last pockets of unhappiness that we could possibly help
alleviate and you know, bring a society where the only
problems are the the fact that you know, humans are
human and we're going to always you know, we have
our ups and downs, but that we have a chance

(51:03):
that everybody has an opportunity to be doing something productive together.
I just imagined that it would feel like such a
pleasure for everybody at you know, at any uh current
uh position in our current world, that they would all
feel this pleasure if they felt like they could walk
down the streets and feel they were part of a
planet that was thriving in that way, was making it

(51:26):
possible for you know, the presumably our our ecosystem of
other animals to be doing well, and that we were
also now beginning to think more about where would we
like to explore, both intellectually but perhaps you know, visiting
other parts of the of the Solar system eventually more.
You know, there's a lot of room for us to
be feeling something very exciting at this moment, and I

(51:50):
and I wish that people had that sense that this
is their their opportunity to do something positive, not just
to be scared of all the things that go wrong.

Speaker 1 (52:03):
That was my conversation with Saul pearl Mutter. We started
with astrophysics, but we quickly got ourselves to how we
hold our beliefs. What Saul noticed a long time ago
is that science has developed, over many centuries a very
particular culture around belief It's a culture where you want
to be uncertain and where disagreement is not something to avoid,

(52:26):
it's something to seek out. Now that's really unusual because
in most areas of life, we build our identities around
what we believe. We attach ourselves to ideas and then
we defend them. We double down when our beliefs are challenged.
But in science the game is different. The goal is

(52:46):
not to be right, it's to get it right, and
getting it right requires the ability to step outside your
own perspective and to examine your own beliefs as though
they might be flawed. We invite criticism, which never feels good,
but we do it because it sharpens the picture. And

(53:07):
it's hard because it runs against deep instincts. As I
mentioned at the beginning, our brains are pattern finders. Our
brains build internal models of the world, and once those
models are in place, they tend to become self reinforcing.
We catch the evidence that fits, we discount the evidence
that doesn't. So what do we do about this? The

(53:30):
answer that Saul suggests is the scientific approach. You build
systems that help you wriggle free from your own biases.
You invite people who disagree with you. You create structures where
your ideas are challenged and refined. In other words, you
make disagreement part of the process. And when that works,

(53:53):
perhaps we get a future where humans can think together better.
We can collaborate, we can disagree productively, We can update
our beliefs as new information comes in. Saul's hope is
that if we can do that, then many of the big,
overwhelming problems we face become tractable. And history gives us

(54:14):
lots of examples of this. Problems that once seemed insurmountable,
like feeding a growing world population, or getting rid of smallpox,
or getting ourselves to the moon. All these problems yielded
when enough minds worked together in the right way. So
what I take from today's conversation is that the biggest

(54:36):
challenge we face probably isn't any particular problem out there
in the world. It may be the meta problem of
how we think about problems, how we talk to each
other about them, and how we navigate disagreement. Because if
we can get that part right, all the rest will
fall into place. Go to eagleman dot com slash podcast

(55:02):
for more information and to find further reading. Join the
weekly discussions on my substack, and check out and subscribe
to Inner Cosmos on YouTube for videos of each episode
and to leave comments. Until next time, I'm David Eagleman,
and this is Inner Cosmos