Hello and welcome to the Behavioral Design Podcast.
This season we're diving into the intersection of behavioral
science and AI. We want to make sense of the
state of AI, from understanding how humans interact with
intelligent systems to using AI to do behavioral design itself.
I'm Aline Holsworth, a health tech advisor specializing in AI
and product design. Over the past 15 years, I've
been crafting human centered products with behavioral science
at the core. At Apple, I LED Behavioral
Science for Health AI, designing and launching AI powered
features to help users reach their health goals.
And I'm Samuel Sultzer, your second Co host.
I'm a behavioral strategist specializing in hybrid formation
and designing products that drive long term baby change.
I work with leading tech organizations integrating AI to
scale behavioral design for good.
And I'm also the founder of Baby Bites, a dedicated community on
behavioral science and AI. Quick word on Nuance Behavior
where we help organizations build impactful digital products
using behavioral design. We only take on a few clients at
a time to ensure the highest level of quality for our
tailored evidence based solutions.
If you'd like to become one of our special projects, e-mail us
at hello@nuancebehavior.com or we could call directly on our
website, nuancebehavior.com. Hey, I don't see a voting
sticker. Have you voted?
Well, yes, actually I have already voted.
I voted early. We have this wonderful thing in
Durham called early voting. There are, there are many, many
advantages to it. You can go at any time of day.
And like one of many, many places, it's flexible.
It's, it's like really the ideal way to vote.
There's no lines. Whereas if you if you vote on
actual Election Day, you can only go to a very specific place
with all the like very specific things and often have to wait
for a very long time time to vote.
So highly recommend early voting.
Nice. That's awesome.
And I had a voting experience this year with voting for the EU
elections. And I feel like for me, every
time I vote, I feel like good about democracy, like I feel.
Like. It's like positive reinforcement
because you know you go to place, people are friendly.
So friendly, yeah. Everyone is friendly and you
kind of feel like you leave there feeling like you've done
something good as well, and you've done your part and you,
yeah, you feel thankful. Yeah, that you, you get that,
that voter's high after. No, I agree.
I mean, there are really very few situations in life nowadays
where you can go and do something, you know, fairly
simple and get like 6 thank you's and like smiles the whole
time and just all of this positive reinforcement.
It's wonderful. And then you even get a sticker
at the end. Yeah, I didn't get a sticker.
I got, I think a cookie maybe or something.
I I got something, but I didn't get a sticker.
But. But I'm glad you did and I'm
glad you voted. And that sets us up for
obviously this episode and also next episode, we're going to
cover a lot of thoughts on how behavioral science can help us
think better about misinformation, elections and
everything in between. Also with kind of AI as a big
influence as well, potentially. Yeah.
And, and overall, we obviously have this big theme of
misinformation, especially looking from this side of the
Atlantic observing the American election, there seems to be this
cloud and worry around misinformation and, and what are
things we can trust and what can we trust when it comes to the
news leading up to the election? And we've heard about cats and
dogs being consumed in some places where I've heard a lot of
different things. But I don't know from my
perspective, I obviously see it from a different angle than you.
So what has been your experience so far when it comes to
encountering misinformation? In this election.
Yeah. Well, so first, I think the
Haitians eating cats and dogs is maybe one of the more comical
form of misinformation. But a lot of the misinformation
that's proliferating increasingly in advance of the
election is less innocuous than that.
And it's really what I would categorize as disinformation,
which is intentional. It's misinformation, but really
intentionally trying to deceive people from mail in ballots
being destroyed in Pennsylvania and then encouraging or
facilitating non citizens to vote in California.
These are all examples of disinformation that's already
spreading that has been very clearly and unilaterally
debunked. But because it's sensational and
because it casts doubt on the election results, it's juicy
enough that people are extremely motivated to spread it.
And the big fear is that this disinformation will not only
have an impact on the election itself, but on whatever happens
after the election. Right.
And yeah, maybe Eileen, do you want to introduce our fantastic
guest at this important time? Yes, I would love to.
We were so lucky to have Gordon Pennycook on the show.
He is a psych professor at Cornell, and he studies where we
go wrong in reasoning. And these reasoning errors show
up in all sorts of domains, from climate change to health issues
to politics, like we'll talk about today.
And one fun fact about Gordon. He won the very humorous and
highly esteemed IG Nobel Peace Prize for his work on pseudo
profound bullshit. This is one of my favorite
prizes in all of social science. It's actually, it's not just
social science, but many social scientists have been awarded the
IG Nobel. And it's also one of my favorite
papers that has won the IG Nobel.
So if you're not familiar, the the IG Nobel is this celebration
of research that quote UN quote first makes people laugh and
then makes them think. And he has some very interesting
research on pseudo profound bullshit, which is what he calls
seemingly impressive assertions that are presented as true and
meaningful but are actually vacuous.
And you can see this in many of the quotes that come from Deepak
Chopra. But it's some examples are
something like hidden meaning transforms unparalleled abstract
beauty, which like has the the syntax of being a statement that
could be true and makes sense, but actually is complete
nonsense, even though it's it like comes off as something that
could be real. Gordon has also done a great
deal of research on misinformation, which is exactly
why we invited him here today. And, you know, given that it's
election week and the first thing that comes to mind when
you think of elections, at least in the US, is misinformation and
disinformation. I'm not sure what that says
exactly about the state of society, but these two do seem
to come hand in hand. And so as a result, who would we
be if we weren't tackling this head on?
Yeah. And like, to be fair, I think
it's not only true for the US, but I think in every election
that happened this year, there's been a lot of elections in the
world. And even last year, it's
definitely always, always a part of the conversation.
And yeah, as I said, we had AI think a really important and
valuable discussion when it comes to understanding
misinformation from kind of behavioral science perspective,
but in a very fun way. I will say we had a really good
conversation and Gordon shared with us a way for us to break
down misinformation. It's a big topic, but I think he
did a great job of helping us make sense of it in a way.
What we know about misinformation, how to think
about it, and how we can kind of also think about the causes and
ways to measure it and many things.
That is interesting. From a behavioral science
perspective, so we cover. That given the system as well,
we naturally also cover quite a bit on.
A is part. To what degree AI play a role in
amplifying and creating misinformation and how to think
about that as well? But yeah, so if you're
interested to learn what makes misinformation so enticing and
spread worthy, and also AI's. Role in all of this Listen to
this episode with Gordon pennycook happens to.
Murgatroyd. Wow.
Perhaps, say, welcome Gordon to the Behavioral, the same
podcast. Thank you, happy to be here.
Yeah, you don't sound very happy.
Sound very happy to be here. Well, it's 9:30 in the morning,
I mean. That is not that early.
Because that is, that's true. My kids go to school at 8:00 and
I, I'm, they say goodbye to me when I'm in bed still.
So I yeah. Yeah.
Well, we're very happy, yeah.
We are excited to have you here. I'm so excited.
This is great, Oh my God. That's better.
And yeah, we obviously wanted to talk to you because it's been a
lot of elections already this year, but then the Big 1 is
coming up. And leading up to this has been
increasingly, I think, questions about how well we understand the
role of misinformation, especially in this day and age
where AI is having a big role. And so we really want to get
your help to make sense of all of this.
And I guess to start, it would be really interesting to maybe
set the scene a little bit. Yeah, that's good.
No, maybe I can give it like a an even broader kind of like
historical thing. Like I started doing research on
misinformation in the 2016 election because fake news was
this big thing and that and that was a particular case where
people, it was like there was a bunch of stories about
Macedonian teenagers and like just people trying to make a
buck. They'd just make a website that
looks like a news website, make up a bunch of stuff.
And then that would be like make go viral on Facebook and they'd
make a few bucks off that. And so that was the kind of
initial sort of thing that we were investigating.
And misinformation has kind of evolved since then.
You know, I mean, misinformation has been around since
information has been around, like it's just false things.
But there's this, like, unique class of Internet stuff, social
media falsehoods and so on. And then as the kind of like
bots on social media we got became more advanced, I mean,
most of they were pushing misinformation that people are
making. It wasn't like, yeah, it was
magnifying it. They were just like, a lot of
the, it was inauthentic kind of engagement on social media that
was helping things go viral. But I mean, a lot of the time it
was purely just people. People were getting their
attention grabbed by some insane headline, and then it was just
kind of getting spread. But then we like when Trump was
the president, it became kind of apparent that there might be
bigger problems. And that's misinformation coming
directly from political elites in some cases.
Like these things work together because I mean, it's just we
happened again in the in the debate with Kamala Harris, which
was like eating the cats and the dogs.
That was a kind of misinformation that came into
Trump's sphere and then he tells everyone, millions of people
about this thing, and not that many people would have seen it
if it was just a fake news headline.
But then it became a gigantic thing.
And then it has a certain level of credibility to people who are
following Donald Trump that that maybe they would have dismissed
otherwise. Yeah.
Yeah, exactly. And I mean, one is just like
getting in front of as many people as you can, if you have
that size of a platform, but then also adding credibility and
people kind of accept what he says and so on.
So there's and there's more dynamic, there's different
dynamics to that. And so it became a more
difficult problem. And then you enter in AI as a
way to kind of like make things easier for the creator side,
like, you know, building misinformation kind of that
scale. Now, at the same time, I should
say, though, it's not difficult to make up crap.
It's not, it's not, it's actually pretty trivial for
people to just make up stories. And a lot of time it's not even
like that. It's like some kernel of
something becomes it's like a rumors.
I'll give one explicit example. The people have heard the story
about like in schools, teens are identifying as cats and there's
litter boxes in bathrooms or whatever.
And like the furries, are these the furries?
Yeah, well, I mean, but they I mean it's because it's like it's
like anti trans kind of trope. People think it's furries, but
people think furries are trans people.
But it has nothing to do with one or the other, of course.
And so they just think so they think that they're identifying
as cats because you could you could identify as anything now
and blah, blah, blah, blah, blah.
But that rumor came out of like, I think there was actually was
Kitty litter in a school, but it was because of shooter scenario.
But there was no one obviously like pretending to be a cat and
using the Kitty litter in the bathroom.
I'm sorry that is lost. I mean what?
Why do you need Kitty litter for an active shooter situation?
Well, you might be stuck in the room for a long time.
Oh, my uncle who is a literal a teacher in Canada told her he's
like, I heard a story about their kind of kid leaders.
And I'm like Shane, there's no who's.
And by the way, I was, there's a here's a little story.
I was my parents were janitors in addition to other things, but
I so after school, my after school's chores were to clean
the high school. And if a kid, you know, use the
Kitty litter box, there's like they're not going to clean it.
Like that's just not, you know what I mean?
That's it's not in the cards. So anyways, that's but so like
you don't really need AI to make up stuff like that, but it does.
But you can. It does help scale things, and
then it's. Easier.
To scale things. Yeah, exactly.
It's not difficult, but it but it does make it easier to make
much much more of it. Yeah, exactly.
Yeah. And I'm interested in that
sense, like, do you in your research or how you think about
this, is that a way that this is in some way separate in terms
like we have some things, as mentioned, there's been, you
know, various types of falsehoods and gossip and
propaganda in various ways where the objective has been to kind
of shape a narrative in some ways.
And and we've recently seen some like popular kind of more maybe
right wing pundits that has come out that they've been sponsored
by Russian television to to push certain things.
And so that it is kind of like this type of misinformation that
in some ways maybe has been around, but still obviously
still amplified with, you know, Internet existing today.
But then you have this maybe in some ways new wave of
misinformation that is purely used, accelerated and spewed by
used artificial means, like some form of bots or some form of LLM
models that are kind of used for for some of this.
Is that something that's actively separated or how would
you categorize misinformation in this way?
It's. Not separated by us.
I don't know, maybe some people are trying to do that.
I think it would be very hard to know which was which.
And we actually don't generally because I'm a psychologist, we
don't spend a lot of time speculating about the source of
it because it could who knows really.
And ultimately, and I think actually the, the funding of the
influencers by Russian, like by, by Russian interests is a great
example because they didn't tell them to do anything.
They're just funding them. They're like, they're already
saying what we want them to say. So they don't need AI.
They don't need they just, we're just giving them money to keep
doing what they're doing because they've already adopted the
narrative. And so like, I mean, so it's a
case study in the sense that if you think about there's enough
stuff out there already to drop on if you want to push false
narratives. And then, you know, you can see
how AI would help with it, but it's certainly not necessary.
And like we had the same. So I don't think that the scope
of the problem has really changed that much since AI has
come around. It's probably made the lives of
people who are trying to actively disinform people a
little bit easier perhaps. But like, I don't think it's
really improving the falsehoods or like making them more more
catchy or whatever. I think it's just that was
already there, people already pretty good at that.
So that is, is I think a really good way to frame it.
And so then looking on still technological side of how things
have evolved, we you kind of mentioned the 2016 election
where there was talk, I think there was Cambridge Analytica
was kind of like one of the main things that was talked around.
I want to stop on Cambridge Analytica because this, I think,
is fake news in itself. I don't know, Gordon, how how
familiar you are with what actually happened with Cambridge
Analytica. Sure, yeah.
People thought that they were really targeting people, but
they weren't. It was, you know, they thought
they thought that it was like they had some secret sauce that
was really doing persuasion. But it.
Yeah, and, and I think a lot of us bought into that as well.
I, I certainly did. I used this as a, as a case
study to, to test out your debunk bot, which we're going to
talk about in another episode. But you know, I, I was actually,
you know, fairly unsure, at least not 100% certain that what
happened around this was, you know, certainly a lot of
accounts on Facebook were mishandled and information was
stolen or whatever you want to call it without consent.
But in terms of what was done with that information, I think
there's this huge misconception, let's just say, about how what
actually happened and then how much that actually affected the
election. So you might ask someone, you
know, why? Why did the election tilt in
favor of Donald Trump? And someone could reasonably
say, oh, you know, that psychological targeting that
happened through through Cambridge Analytica's data
problem. Yeah, and it probably was.
I mean, people say the same thing with fake news as well.
I mean, they're, so they're did that did the fake news sway the
election? Was it Cambridge Political
people are looking for reasons. I mean, at the time, you can see
we were looking for reasons to explain this thing that we could
not explain as like, liberal intellectuals, I guess, you
know, or like this doesn't make sense.
It turns out people actually like Trump and they had
different political opinions, you know what I mean?
So. And the polling was wrong and
they weren't listening to the. They weren't answering the
polls. So that was basically what it
was. So you, all of our little
explanations that we developed immediately after the election
were. Yeah.
I guess this for me raises another question, which is how
do you quantify the impact of misinformation on something like
an election? Can we in any reasonable way
actually do that? Yeah, probably not.
I mean, it's, I don't know, You can't, I can't quantify it on
the like, what people actually believe, you know what I mean?
Like how do you know this? Behavior.
Yeah, we want to. We what we really want to
understand is what influences voting behavior.
What people believe maybe is one thing, not necessarily the same
as who they actually vote for. Sure, yeah.
But yeah, I guess what I was saying was that it's hard to
even pinned down a little of misinformation and what people's
beliefs are and like, whether it's, you know, identity or
cultural negatives or whatever. But it's like, yeah, but
definitely when it comes to the election, this is it's difficult
because and one, respect almost all of like the vast majority of
people who vote, you already know who they're going to vote
for. That's what it's going to be
anyways. And so you have this like weird
situation in the States where there's this.
Small minority in a particular few states who have a gigantic
influence and there's a lot of things that could that's a very
like hard to predict context. And so like small things could
have a big influence or not and I don't know.
And so when it comes to misinformation, it's just, it's
just one of these things where people, one thing that we can
say for sure is that people do are walking around with a huge
amount of like misunderstanding about how the world is.
And that comes from somewhere. And the thing where it comes
from is like misinformation. Now, to the extent with that
comes from the sort of thing that we mean when we say
misinformation, like the social media viral stuff that everyone
kind of worries about or just like simple mistakes or
conversations with neighbors or whatever, you know, it's hard to
really tease that apart. Yeah.
And maybe the way to tease it apart a little bit is if we then
move forward a few years, we have 2020 and we have a strange
year with, you know, COVID and many other things happening
around there as well. But talking about COVID and and
vaccine and misinformation, I know you've you've done research
around that specifically. Yeah.
I mean, I think it's a good example because, like, thinking
about people not getting vaccinated as a consequence of
misinformation. Now, there are lots of reasons
why people don't vaccinate. And they, you know, some of it
like institutional trusts, you know, how much you trust doctors
in the system and all that kind of stuff.
But, I mean, I think there's something to question that the
amount of misinformation spreading had some impact on
people not deciding not to vaccinate.
It's just kind of very obvious, yeah.
It's it's primarily attributed to Joe Rogan, right?
Yeah, I'm not sure primarily, but like, I think what's it
called? Ivermectin?
I mean, we've got to be clear on the.
I don't want to be too politically biased.
You know, people were saying that Joe Rogan was promoting
horse tranquilizer or whatever, which is kind of may be true in
a strict sense, but not true. And like, it's not really like
what it's for for humans, you know what I mean?
So but anyways, so it it goes both ways.
But there's been this kind of growing thing in the research on
misinformation where people are kind of like denying its
importance and consequence. And I think that's kind of just
wrong. I mean, I think that is the
case. We can it's it probably is
overrated in many respects. Like people think it's the most
there was like some like kind of a thing as aun thing or
something where it's like misinformation is the most
important problem. And like, Oh yeah, it's easy to
like make it see it's but it's like proximally speaking, not,
you know, like misinformation flourishes because of the
structure of our fragmented information environment.
That's a much bigger problem. And there's other like but many
other big problems, you know, climate change.
But but it still ultimately is like we want people to have
accurate beliefs about the world and misinformation is just false
things. And so like, just in a strict
sense, like, yeah, that's a huge problem.
We don't, we want, that's the whole point of education.
This is why we have expertise and and This is why we make
podcasts where we teach people things.
It ultimately is all about trying to like, persuade people
to believe things that are on based on good evidence, and
misinformation counteracts that. It's interesting that you put it
next to climate change because, well, for example, if you don't
believe in climate change, then it doesn't like there's nothing
you can even start to do there for getting someone to act.
They're just, you know, it doesn't matter how big the
actual problem of climate change is.
If they don't believe it, they're not going to do
anything. That's that's true.
I think that's so perfect example.
So that is the case. And people often say in papers
about climate change, they'll be like, we really need to kind of
convince people that this is a problem because they're not
going to do anything. But like at the same time, what
are the most effective ways to combat climate change?
It's not the everyday behaviors of citizens.
It's governmental policy and, you know, so those are things
that cannot be influenced by changing an individual's belief.
Then, of course, what people say is, well, if you change what
people believe and then the governments will listen to them,
well, you know that there's there's nothing there that's not
completely wrong, but it's not exactly right either.
So yeah. Pretty difficult indirect route
for sure. Yeah, exactly.
Yeah. And so if I'm going to try to
summarize a little bit where we're come so far.
So we started in some ways where misinformation has been around
forever and it's kind of it's the twin to information.
Like it's kind of hard to avoid in human society.
We're always have to deal with that.
We spoke about how a lot of the current misinformation is
amplified by credibility through certain voices and like certain
people that are kind of spreading this and with help of
obviously technology today, like it's making it easier.
But at the same time, it's it's much of that still comes from
people doing it. Like a lot of people being
involved in, in sharing their maybe false beliefs that we just
use masses and then has some kind of consequences, but that
it's very hard to understand actually what the consequences
are still. Like it's kind of hard to even
with something like vaccine hesitancy or or not taking your
vaccine, it's still hard to really know, like to what degree
people were vaccinated or not because of misinformation on the
sources. Because it's like it's so mixed
in to the fragment of like human experience that we talked to
people on the like in our lives on online.
Like this is very hard to know. Like, OK, this source of
misinformation LED people to to not do this thing.
It's like good summary so far. Anything you would like
underline? That's a great summary.
I think that captures it. We could just use that we don't
need. We could just cut out the first
part. They've got the gist.
Well, that, that's good to hear that sometimes you get it wrong
into summarizing, but that's good.
And and then I do want to kind of build on kind of moving from
COVID in some ways. I would say I've noticed and I
think it's been big part of the discourse is that, you know, I
think in 2022 there was some research that was around X or
Twitter saying that like 2/3 or at least 1/3 of of all accounts
were some form of bots on Twitter.
We saw counties rising first, like more edge cases where
you're like, hey, you could use deepfakes.
Like deepfakes is kind of the thing you could kind of copy
someone's voice or or face and that can be used in various
ways. But it was kind of like little
edge cases and, and more like, hey, be wary as soon it's going
to happen. And then I think it was around
last year that was in Slovakia. They had some form of election
deep fake thing around, especially with audio I believe
where there was some basing up to the election, there was some
basically deep fake audio that was spread that had some form of
impact in terms of least fact checkers were scrambling to make
sense of these fake recordings and how to make sense of it.
Yeah, they they had the Slovakian Liberal Party leader
talking about vote rigging and I think it was raising the price
of beer. Oh geez, of all the that's the
last, That's the final straw. Yeah, we cannot tolerate this.
Yeah. So we're moving into, you know,
the area now 2024 where it feels a little more real when it comes
to this either. We have also, not only are these
bots more like very simple bots that you just jump around and
maybe use retweets or post some very generic things, but they're
actually powered sometimes by large language models where they
can actually have some form of level conversations online and
and they can actually engage with people in some form of
shack communities and and so on. Maybe the last thing I'll say as
an example is recently I've seen this like people being worried
about what we see on images online because someone googled
baby Peacock and they realized that of the 20 images on Google
there was a baby Peacock, only three of them were actually real
baby Peacocks. And all of them else was like AI
generated images. So I think more and more of this
fear is sweeping out now. It's like, OK, where are we
right now when it comes to this kind of technological influence
on misinformation and so on. So you you alluded a little bit
to that already in terms of we're not maybe going in orders
of magnitudes away from where we're before.
Like we're still, we're existing and ordering a pretty, pretty
misinformation high levels. But yeah, how do you make sense
of the current technology global advancements?
Yeah. I mean, I think what the real
concern is essentially is like inauthentic behavior, like what
you in a, in a kind of like a democratic society, we can have
differences of opinion and like people get things wrong and
whatever, and we can learn from each other and all that kind of
stuff. But when people are acting
inauthentically, then it kind of like disrupts the system.
And what that, what that means is like the obvious case that
you're talking about is like literally it's a bot and it's
not really a person. You think it's a person.
And so like you're taking that to mean that there's all these
people are supporting this cause, but actually it's a bunch
of Russian bots and it's not actual Americans or whatever.
Or it's like this is someone talking, but it's actually not
them talking. It's an AI or this is a picture
of something. I think it's not actually that.
But there's also like, I mean, those are all concerns, but of
course, like inauthentic behaviors.
Also people who are influencers who are not generating authentic
opinions, they're trying to just say what they think will get
them the clicks and the likes and the, and the views and the
listens and so on. That's also an authentic
behavior. And So what you end up as a
distorted kind of reality that people are entering online and
which of course leads offline where it's like, it's hard to
know what's going on. Misinformation makes that worse.
But also like it's not just about truth and falsehood.
It's just about like what, how do we know what other people are
like, what's what's actually happening in the country?
And so like our understanding of like in, in the context of like,
you know, given the election of like our political others is
like way off. People have really, really do
not, they totally think that like people on the other side of
the aisle are way more extreme than they actually are.
There was actually a paper that was published recently where,
you know, people think the like way more people are responsible
for trolling than actually are. It's a tiny fraction of people
actually engage in kind of like actual users engage in what you
might call like an authentic, an authentic sort of behavior.
But the, our sense of it is that like 40% of people actually do.
It was actually 3% or something. I can't remember what the actual
status. So we, our perception of reality
is being really distorted by all these things.
And then you enter in, these things are just essentially made
to be inauthentic. Yeah, it's not going to make it
better, that's for sure. It's a it's an issue.
So, so I'm familiar with this research about believing that
others are much more extreme than they really are.
I actually, I feel very strongly the opposite feeling in in my
own experience, which is that I tend to think that other people
think like me, even if they're, you know, not like me.
And I extend my own belief system to the Republicans of the
world as well. And so when I think about, you
know, the tightness of the race, for example, in the 2024
election, and I think, oh, about half the country is going to
vote for Donald Trump, that is so inconsistent with my beliefs
about what other people could possibly even be capable of.
And my liberal bias is very, very strong here.
But, you know, and part of it, I'm sure, could be living
physically in a little liberal bubble myself where I mostly
interact with other people that are very similar to me.
But for me, I am shocked to think about anyone voting for
Donald Trump. I think both of those things
will be true at once. So like you're kind of
intuitive, like sense of you would assume that everyone's
more similar to you than they actually are because you have
to, you know, you live through your own perspective.
If I ask you, OK, then like think about a Republican and how
extreme they are or whatever. Now you think, OK, wait, I think
they're similar to me. But then you look and see that
they're supporting Donald Trump. And so you make some sort of
inference of it must be that, oh, they actually must be like
way more extreme or like not different.
So like you take. So then you make an inference
that they're like, now you overcorrect essentially.
I'll give you I'll give you like another kind of like related
examples of this. And this relates to conspiracy
beliefs. So like people there's this like
common thing for conspiracy believers where they think about
the people to, you know, accept mainstream narratives, quote UN
quote as like sheeple. You know, they're like there's
going along, they're conformists.
And like really the conspiracy theorists are the actual kind of
critical thinkers, the unique critical free thinkers, they
often say. And So what you might assume
from that is so people who believe conspiracies probably,
like, know that they're on the fringe, right?
And kind of, they kind of want to be there.
And that's the whole point of it.
And like, if you ask them that, they probably would agree to it,
Yeah. That's a feature, not a bug.
Yeah, yeah. But at the same time, we did a
study where we asked people to estimate the percent of people
that agree with them about conspiracies.
OK. And so I'll give an example in.
So for the Sandy Hook false flag conspiracy, it's a ludicrous
extreme conspiracy. 8% of people in our sample thought it was
true that Sandy Hook didn't actually happen.
It was a whole false flag thing, actors and so on.
And so we asked the people to both the people who believe and
don't believe, but we asked them, estimate the percent of
people that you think agree with you.
And so 8% thought it was true. If they're calibrated, they'll
say 8 to 10%, you know, whatever they said 61%, they thought they
were in the majority. They thought that most people
realize that this was a false flag.
So like both at the same time, they're like, yeah, I'm unique,
I'm critical, freethinker, whatever.
But they also kind of think that everyone agrees with them.
And that's even when you're totally on the fringe.
And so you can see how this there's kind of dueling elements
of our psychology that contribute to these issues.
That's great. Yeah, Sam has been calling AI
and and and specifically Gen. AI weird humans.
And to me, this seems like humans are are really the weird
humans. Yeah, exactly.
It's it's a reflection of us. We're like, oh, how weird AI is.
It's like it's just doing, you know, we created.
It right it's. Just it's a little, it's like a
weird little mirror, but it's still us in the mirror.
Yep, Yep. Yeah, no, but that's super
interesting. So I think we've now spoken
quite a bit of, you know, elements to setting the scene in
terms of OK, where are we, what is the role of humans?
We're humans, we're technology and so on.
But used to really make sure we're on the same page in terms
of misinformation. There's a lot of things run
misinformation that I think it's kind of interesting to to talk
about and that idea in terms of I've seen a lot of versions of
this. You know, we talk about a lie
spreading X amount of faster than truth.
I I've come across this thing called Brandolini's law.
Have you come across this idea Brandolini's Law?
Yeah. It's it's much easier to create
bullshit than to refute it. Yeah, yeah, exactly, exactly.
And yeah, I think it's called some like bullshit, the symmetry
principle or something like that as well.
I wrote the 1st paper on the psychology of bullshit.
You don't think I know about the Brandolini's law?
That's a that's a dining criminal.
Thing. Thank you.
Oh my God, how dare you. Even I've got I've got
Frankfurt's own bullshit on my shelf over here.
That's good representing and and sticking up for your territory
there. So yeah, tell us, tell us about
that. Like what is what is true about
how misinformation spreads? Is it true that it spreads X
much faster? Yeah.
Is it 8 times more? I think so.
I think it is true actually. And So what this is an
interesting case study in itself because so there was a paper
published, Deb Roy and and others published this paper in
Science in the kind of early days of misinformation research
or whatever, saying that like misinformation spreads faster
than true information, false spreads faster than true on it
was a Twitter analysis. We were really dubious about
that because it was like most, it was among things that were
fact checked, false things were spread faster than true things.
And so we thought that was a weird kind of category of
things, like the type of true things that are fact checked is
different than just true things in general.
But we've, there's actually been more follow-ups and we've looked
at data ourselves and like it does seem to be the case that
things that are dubious are have a kind of extra bit of our
virality on social media. If you and if you look at all
kind of ways of slicing that, it seems to be kind of generally
the case. And there's a there's a kind of
simple logic to it, which is that if you have freedom to say
whatever you want and you're unconstrained by reality and the
truth, you can say something more interesting.
I mean, This is why we watch movies and TV.
We kind of like say, OK, this is a different world now.
It's OK that we can, you know, they're superheroes or whatever
it is that's interesting. That's what narratives are, you
know? And so it is the case that like,
yeah, in certainly in the context of like kind of news
content, if you want to stretch the truth, it's going to get
more clicks. And like, it's part of that
also, like if you're stretching the truth, then you're probably
also being more willing to really hype up the emotional
language or like, play on people's fears or whatever.
And so, yeah, if you have no scruples, you can you can make a
buck on social media, unfortunately.
It's interesting the, the statement that a lie spreads 8
times faster than the truth to me, I, I feel it doesn't have,
it doesn't have all of those characteristics, right?
It's, there's not as much emotion or creativity to it.
But I, I think it has enough of those elements that it makes me
wonder, is that true? You know, like it kind of feels
like a lie. That's so excessively precise.
It's like there's no way you can estimate that because how?
Because think about what the think about what the claim is
there. You're like, OK, we've done it.
We've captured a representative sent of all true things and all
false things. It's eight times we did it.
Yeah, yeah. We're we're going to shoot them
both out of a rocket and see how quickly they, yeah, they go.
It's also a round Number. It's not like 8.35 times, it's
eight times, Yeah. Anyways, in general, false
things can spread faster than true things.
But it's just, it doesn't mean all false.
It's. And who knows how many times
more is it's. Yeah.
What would you say are some more characteristics of lies?
If you're trying to arm someone to maybe spot misinformation out
there, this sort of false precision might be part of it.
You talked about the the emotional aspect.
What are some other features of misinformation?
Let's shrink the category to the like, online viral falsehoods
because that's easier to kind of wrestle with.
But yes, so I mean, So what? Those sorts of things are
common, like using highly emotional language.
But really that's what it's about is there's like an angle,
a narrow way to think about misinformation is like things
strictly speaking being false, which would be like something
like if someone were to claim, oh, 10 million people died due
to COVID. I actually have no idea how many
people I should probably look that up.
But actually it was half that number that was strictly
speaking being false. But like ultimately those
quantities are not really that different for people to
understand. And really the ultimate the, the
kind of like actual kind of just you're getting across.
There is a lot of people. And so it's in a certain sense,
it's kind of true. Yeah, people can't think about
those numbers anyway, so it doesn't really.
Yeah, exactly. So it's just it's a distinction
without a difference. And so like misinformation often
has this kind of quality where it's not just that it's like
strictly speaking is false, but there's misleading that you're
being deflected over here instead of over there.
Haitians are eating their pets, for example.
Yeah, yeah, exactly. Because that what that's about
is like, so there's the specific fact, the claim that like
they're eating the pets, but what's really being communicated
there is that these are dangerous people that are
different than you and and so on.
And that's also false. You know, that's all misleading
like that, you know, exactly. So when when you're kind of
engaging online, you have to think about who is the message
coming from and what are they trying to get from me?
You have to kind of look behind the actual literal facts.
Yeah, what's the point of this message?
1 So 1 issue is that so my oldest brother there is like
kind of down the rabbit hole or he more than in the past than he
is now. But I had conversations about
kind of who he's listening to and what kind of sources he gets
because he thinks all mainstream media is fake news and so on.
And the, you know, the problem with that is that people who are
journalists can actually be fired.
You know what I mean? Like if they would make
something up, there's some mechanism by which they could be
fired. But he likes listening to some
dude on YouTube who like just says a bunch of stuff.
That's OK. What stops this guy from lying
or like saying like that he can't be fired.
In fact, if anything is incentivized to say extreme
things that people will listen to the so they listen to his
videos or watch his videos and he says, yeah, but he doesn't
lie though, So you know what I mean?
But that didn't work. But but I think there's a good
old underlying point you have to think about, like, what is this
person's incentive to mislead me?
And that's that's one way to kind of get around try to figure
out what's true or false on social media.
You got to think about what they're trying to do with the
sources. Yeah, yeah.
And I guess like one specific element we talked a little bit
about that, you know, something that's emotionally arousing or
appealing in some emotional way can have impact.
And a very specific part of that, that honestly, it's always
kind of pisses me off in some ways, is it's funny.
That funny is one of the few things that can like really
amplify a message more than anything.
And I love funny. Like I, I love comedy.
I love watching everything from yeah comedy specials to stand up
to TV shows and and done some improv comedy myself.
That's so ironic given how unfunny you are.
I know it's it's. Wow, way to Crest the man.
Anyway, what is unfortunate though is I feel like fun is
it's kind of taking hostage by like this really bad actors
where you have funny being used. I would say honestly very well
by Trump. Most people are on the same page
in terms of like part of his appeal and why it's hard to also
counteract his bullshit is that he often times veils it in fun
and or funny. Same with, like we mentioned,
the idea that certain people have a lot of sway online and
and can like amplify things. Elon Musk is probably one of
those people. And there's few things that he
loves to retweet as much as funny memes, you know, like a
fun meme, even if it's lie, it's like that doesn't really bother
him. You know, if it's funny, that
kind of takes the box and and I'm just interested to hear your
thoughts on on funny and it's really misinformation.
Well, I mean, people can use it as a excuse essentially, or like
you say something inappropriate, like that was a joke, you know
what I mean? Or like, that's what Musk
basically does on Twitter where he's like, oh, I was just trying
to make people laugh. It just so happens that it was
extremely harmful misinformation or whatever, you know what I
mean? But but I was thinking, I
thought it was funny, You know, if you have to.
So you have to think this is the tension when it comes to comedy,
which is like you have to think about what the consequences of
the jokes are. And so like, I know that
comedians do actually like lament this often, but I saw
Jerry Seinfeld, he said he was wrong about it.
He said what happens is the culture shifts.
You have to know what's funny within the culture.
And so that's I think that's a good way to put it.
So I think one more thing about it too, is The Onion was like
the original kind of fake news site.
Of course, they did it in such a way that it was explicitly and
kind of obviously satirical. What happened was used to be it
used to. Yeah.
And then I was just like reality used.
To be an obvious difference. Yeah, yeah, yeah.
So Facebook was was started clamping down on this kind of
fake news, like where people are, you know, making these
websites and this making things up.
And So what those websites started to do is like, oh, we're
actually we're satire sites, but they weren't promoting the
satirical. And it was like, you could see
that they were like the, the jokes were not, they were
political. It was like really not meant and
also wasn't really funny, unlike the Onion, which is actually
quite funny. You know, you can see that they
were putting effort into the political side, but not the
funny side. And, and someone who knows
comedy knows which, which one you're talking about.
And in terms of like Trump being funny, he's usually funny kind
of incidentally, you know what I mean?
Like he, he doesn't really make jokes.
He just says things that are funny.
And so that's, you know, that's amusing for people that enjoy
things that are funny. But but I think there's a deeper
problem there, which is like there's conduct you'd expect
from somebody and said that's a position which is like, it's OK
to make jokes, but sometimes you have to be serious or whatever.
I think. And it's actually, it's worse
than it's different than that, which is Trump.
So Trump's the apparent way that he approaches communication is
very different than what you would expect and probably want
from somebody in that sort of position, which is it doesn't
really matter what I'm saying in a strict sense.
I don't like that is the facts don't don't matter.
It's the message that matters. That's what the the example was
somebody pushed back to on. They asked them like, do you
really think that they're eating the cats and the dogs in
Springfield? And he said that was just a
report that I heard. He's like, he's like, it doesn't
he's like for him, it doesn't matter what I believe.
I'm just saying things. I'm just saying things like.
Yeah, that's totally fine. It could be true.
I'll just say it like it doesn't matter if it's true or not.
Like he doesn't. There's no regard for the truth.
And so like whether something's funny that was, that's funny,
I'll say it does it. Will some people be misled by
it? Will it make people like other
people angry? It doesn't matter because like
I, you know, it's just something I want to say.
So I'm going to say whatever it is that I want to say.
And like, that's literally the stream of consciousness thing
that he he does. So there's no filtering on like
whether something is true, obviously, or like whether it
would hurt people or whatever it is.
That's just literally just. And so people, people, what's
interesting is that people take that to mean honesty.
And it's it's honesty in a certain sense.
It's honesty to yourself. Like you're just like, in a
certain sense, like a little kids.
Yeah. The ones that.
Like having any responsibility? Yeah, there's.
No, there's no responsibility. There's no like, there's no
filter in this. It's like everything that comes
in their head comes out of their mouth.
That's one way of being honest. I mean, what we kind of want
honesty is like caring about the truth and getting things right.
That's what is the important part of being honest.
For a president, yeah, yeah. Of the United States.
Or someone who's like a science scientist or like, a
communicator. These are the things that are
important. If you're in the public space
and you have a large audience, being honest and being truthful
is what important, not just being, like, genuine.
You know, doesn't matter who you are.
What matters is that you're doing good in the world.
Yeah. All right, it is time for us to
jump to our quick fire round. This is a game, little game that
we play. It's called to AI or Not to AI,
and we're going to give you a bunch of tasks and you're going
to tell us whether that use case is well suited to AI or not.
OK. All right, So the first one is
about polling to AI or not to AI.
Poll individual AI chat bots that have been trained on US
demographics, past polling data, and representative media diets
in order to predict the outcome of an election.
I think the field says unsure. I'm going to say no because I'm
a psychologist. OK, to AI or not to AI cast most
likely votes for people who can't make it to the polls.
No, no. I mean it's from based on the
other one. Obviously, it's enough.
OK, translate from brash American English to polite
Canadian English. Oh yes, very good.
Great use. We'll see if there's some bias
to filter saying like it started recommending team.
What is it called? Tim horton's.
Tim Horton's. Tim horton's.
Yeah, exactly. You get a copy.
Double double Tim Horton's, which is so much sugar, by the
way. You start getting all these
hockey ads. Yeah, I would be fine.
I would make me more like AI more appealing if it just like
had a tuque on. A tuque is a winter hat, Sorry.
I didn't even know that. It's a winter hat.
OK, what about this? To AI or not to AI create a new
celebrity. No, no, that's what is the Black
Mirror. Yeah, let's just not.
If it sounds like a Black Mirror episode, don't do it.
OK, generate a gullibility profile for every person in the
US. What do you mean by goal ability
profile? How acceptable is that person to
misinformation, for example? That's part.
I think that's something that could be useful and interesting.
Create pseudo profile bullshit memes.
Oh yeah, yes, no question. Very quick.
Did you come across Truth Terminal the the bot that's
called Truth Terminal? No.
OK, Basically it was a controversial AAI bought that
has been able to generate millions in crypto by itself by
creating really really obscene memes online.
Oh, interesting. Spread fake news on social
media. Wait is the answer.
Can it do it or should it do it? Is it a use case well suited to
AI? Sure.
Oh yeah, making things up. OK then this is the big one
then. To AI or not to AI combat the
spread of fake news on social media.
Yeah, yeah, for sure. TuneIn for the next episode.
Perfect. Yes, the battle of the bots.
OK. And that's a wrap.
You've been listening to the Behavioral Design Podcast,
brought to you by Habit Weekly and Nuanced Behavior.
Sam and Aline tell me this season is packed with incredible
insights about behavioral design and AI, so be sure to subscribe
and share the podcast with your friends.
Though you might want to keep it away from your enemies.
In case you haven't noticed, I'm an AI voice.
Yep, pretty crazy. Quite the improvement since last
season's AI outro, don't you think?
And if you'd like to collaborate with us at Nuance Behavior,
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A special thanks to the amazing Dave Pizarro for our show music,
and to Mei Chen Yap and April English for their help in
producing and publishing this episode.
Thanks again for tuning in. We'll be back soon with another
exciting conversation where behavioral design and AI
intersect. Oh.
I still feel burned by that. You said that wasn't funny, but
I'll I'll recover it. You know, it was a joke.
That's like the irony of that. Like that was me trying to be
funny and not being funny. That's that's the deep, deep
irony.