hello and welcome to speaking of
psychology a podcast produced by the
American Psychological Association
I'm your host Kim Mills speaking of
psychology is a podcast for anyone with
an interest in the science of psychology
we talked to psychological researchers
practitioners and educators about any
and every aspect of psychology and its
application to the world around us dr.
Jeff Hancock is founding director of the
Stanford Social Media Lab and a
professor in the Department of
Communication at Stanford University dr.
Hancock works on understanding
psychological and interpersonal
processes in social media his research
team specializes in using computational
linguistics and experiments to
understand how the words we use can
reveal psychological and social dynamics
such as deception trust intimacy and
social support dr. Hancock is well known
for his research on how people use
deception with technology from sending
texts and emails to detecting fake
online reviews we're fortunate to have
him here today with the American
Psychological Association welcome dr.
Hancock Thank You Kim
so I wanted to start by talking a little
bit about social robots and your work in
that arena the first question is just to
explain for the audience what's a social
robot as opposed to any other robot
right right yeah social robot is really
broadly defined basically any robot
that's situated with with humans so a
couple of definitions are that they
should be socially evocative sociable so
any robot that's designed to essentially
work or interact or evoke responses from
humans so it's not a room bot for
example well you know it's funny you
should ask that room is a good question
and our group thought a lot about that
sometimes a Roomba could be made into a
social robot you put some little things
on it and amazingly people will really
interact with that robot as if it's you
know interacting with them but
guess that in the corner there get that
work done for me
but no typically it's it's robots that
are designed to interact with the humans
so it can be in workplaces so factories
now often have robots and a number of
them now have been sort of personalized
made it look a little bit more human so
that the workers around them can
understand what the robots doing what
its intentions are where its attention
is mm-hmm so talk a little bit about the
research that you did I understand you
looked at like the last decade of all
the research that involves social robots
what were you looking for what did you
find
right so the group I was working with
was byron Reeves and sunny Leone at
Stanford with me and we had a group of
10 Ras work on this project where we
looked at a decade worth of research on
social robots and it was fascinating and
a lot of work there was almost 7,000
articles that in Google Scholar that
referenced social robots and then we
narrowed that down to about 1,400 that
mentioned social robots but then also
had a robot interacting with a human or
looking for some sort of social response
so there's been you know over a thousand
articles on social robots and it's
across a dizzying array of disciplines
so psychologists computer scientists
engineers anthropologists it's it's
pretty amazing so we looked at all of
those across a decade and then the thing
we got really excited about was we found
the photo of every robot that was in
that decade's worth of work and found as
many photos as we could for each robot
and so we sort of had like early census
if you will of every social robot that
had been published about and it turns
out there's 342 that we found over that
decade so there was sort of like a one
of the first collections of all social
robots that that's been put together and
what were you trying to find by looking
at that well my colleague Byron Reeves
had this insight when we first started
the project and and one of the reasons I
got involved so I usually study things
like social media so how people interact
through technology but I remember having
a great a meeting with Byron where he
had this insight which was
and we can think of robots as media and
since there are social robots it was
like a form of social media so I got
really excited and it was really my
first big foray into working with robots
and it was all because of Byron's
insight of thinking of them as as media
and and what follows from his insight
then is most of the research on social
robots looks at one robot at a time
there's a good reason for that they're
expensive usually you've built a robot
and you understand you know how does
this robot you know evoke a response or
how is it effective at getting people to
learn or to to feel better if it's an
assistive context the problem with that
which we know from psychology is if
you're trying to generalize to social
robots studying one robot at a time is a
real problem this is a problem of
stimulus sampling and so once I called
you we've known about this issue for
many many decades since the middle of
the last century and what Byron's
insight sort of led to is that we need
to get the whole a big collection of
these stimuli so that we can start
generalizing across social robots as a
category of social actor rather than
well there's this robot do anything or
if we make this robot have an arm and
versus no arm does it do anything and so
that was what we were interested in is
is getting this big collection together
so we could start doing research on a
population a sample if you will have
social robots rather than one exemplar
at a time and so what does this portend
for the future how will this be applied
right that's the key question and it's
been exciting in this conference because
I've already talked to you know half a
dozen people that came up after the talk
that were like hey we'd like to do this
project of that project what we've done
is started by asking well now that we
have this collection of robots and a
collection of photos of them you know
when you look at them and I can share a
image with you to go on the podcast or a
website it's astonishing how varied they
are I mean even when we show it to
people that are in the field and been in
the field for a decade they're like well
okay these are really really different I
mean it's sort of like thinking you know
I could take you and study you as an
example of an extrovert and then you
know generalize to all the extroverts
but we know that people are really
different
well robots are even more different than
different people so the first question
then is do we needed a whole new
psychology a whole new side called you
understand social responses to social
robots and the answer when we look at
the literature is pretty clearly no
people tend to bring sort of standard
social psychological processes to new
media so there's tons of work that shows
that we treat technology kind of as
social actors and we bring our old brain
which has been evolving for a long time
to understand social actors like you
know is this a friend or a foe we bring
that to technology so the next question
then is well if we don't need a new
psychology because people you know sort
of react and perceive technology the
same way they do humans what's a good
place to start to look at you know is is
there a fundamental dimension or two in
which people perceive robots when we
looked at the literature in social
psychology around person perception
there's a lot of evidence that people
judge others along two dimensions
very quickly automatically and and you
know comprehensively so their warmth and
competence and some of the main research
on this are Susan Fiske and her
colleagues Amy Cuddy for example they've
done a tremendous amount of work showing
that over you know a hundred years of
research across cultures people's
perceptions initial perceptions of other
people really boil down to warmth so is
this person going to be trustworthy kind
warm towards me or are they cold perhaps
threatening and they argue this is an
evolutionary question is this a friend
or a foe I need to determine that right
away
and then another is competence so
does this person seem capable
competitive strong these sort of terms
and so we thought let's let's start
there let's take a look at that and what
we did is we we had several thousand
over three thousand Mechanical Turk
participants take a look at a single
robot and then answer a bunch of
questions like does this person this
robot seem warm or cold bunch of those
bunch ones related to competence a lot
and then we did what you know
psychological researchers do you factor
analyze those to see if they resolve to
some factors and it's amazing Kim it's
exactly the same as if we just like
people it's just like people so what
makes a robot warm or cold alright so
that was our next question exactly
because designers are gonna want to know
this right like how do I make it warm or
cold or competent or in common warmth it
turns out is really driven by eyes so
does it have eyes or not which you
wouldn't normally think of right away is
but they don't I mean Gebo doesn't have
eyes for example right exactly exactly
so there's this that's a major thing and
not only anything about eyes so once you
have eyes that's a big predictor then
it's um the ratio of the eye size to
your head size and there's lots of
evidence that this is about warmth a--to
so Disney characters for example tend to
have really big eyes so that's a really
huge factor and then in terms of
confidence it's the lack of fur so if
you can see the mechanics you know like
steel and you know actuators of that
they're gonna actually appear more
competent if there's further gonna
appear less confident and then mobility
is a big one for confidence if that if
that thing can move around whether it's
you know arms or moving around like that
then then there's more competence and
and and so it's amazing and it actually
has really fascinating and potentially
disturbing implications so Fisk and her
colleagues have this model called a
stereotype content model and they say
with warmth and calm
you can kind of predict in these in this
2d space stereotypes so confident
competent is up in the right those are
people that are Earth's alright warm hi
warm hi competent and that's the default
in group so when they were doing their
research in the early 2000s late 90s
this would be like white middle-class
America so if you ask Americans at that
time you know the default group the high
confidence high warmth that was white
middle-class men you go down into the
lower space where it's high confidence
little warmth these are like engineers
rich people and these people are they
evoke a different kind of emotion so
it's envy right so and a little bit of
so you're like you admire them a little
bit but it's more like a little
suspicious so they evoke this Envy thing
whereas the default group evokes like
admiration and positive emotions you
keep going around so you're down a
little low low space and stereotypes
down there would be poor people so this
be poor white part black homeless people
on welfare and and they evoke a
different kind of emotion as well which
is contempt and so you keep going around
you get up to the high warmth low
competence these are people in the 90s
would be like housewives people in that
sort of space you know mentally
handicapped individuals you know so the
again these are stereotypes yeah and the
emotion of oak there is pity so as a
designer if you're designing a robot
with these different features
unbeknownst to you you could actually be
causing an initial emotional response
that is deep-seated in our psychology
that's pretty interesting yeah we
thought so does this did this research
tie-in at all with the work that you're
doing on deception yeah so now we're
doing a bunch of things about like trust
of robots so how much would you trust
this robot and the initial work there is
that you know warmth is is going to be a
big predictor of that your sense of its
status but then we'll need to move it
into different
situation so I might trust Jibo in an
interpersonal interaction where we're
just having a fun social interaction but
I might not trust G Bo if I'm on the
battlefield and I need a robot to help
me find bombs and defuse them right so
situations gonna play a really huge role
and our collection of photos really is
an instead of a totally neutral like
there's there's zero context so that's
the next step but yeah I'm really
interested in deception with these
robots you know one of my favorite
examples of deception with technology
wasn't a robot but kind of similar and
that's the Volkswagen scandal where they
programmed their cars to lie to
investigators who were looking for like
how much pollution it would produce
right so it's fascinating this car when
figured out that it was being tested
changed its behavior right like it would
literally have less power but produce
fewer emissions and not one car millions
of these and programmed to lie to humans
and so I mean it's really fascinating
and so and so you know the engineers use
robotics when they were developing this
well we we don't know that but we can
kind of think of the car a little bit
like a robot that's a it's a technology
that it wasn't making its own decision
it was programmed in but it was
programmed by humans to lie to humans
via you know it's it's sort of
technology so right what's gonna happen
with robots we've seen some autonomous
robots that have learned to lie so these
are small little robots and their job is
to go around and find food and they're
competing with other little robots and
the food is like a little electrical
charge that they get and they are given
some artificial intelligence so they're
trying to find food but not let their
other robots get the food and and these
robots would learn to lie they would go
to any area once they found where the
electricity was they would then go to
another area and buzz around there and
then other robots would come and when
they all came there and we see this with
animals like crows are very good at
doing deception so a younger male crow
that will get beat up by the higher
status crow will pretend to find food
somewhere and then when all the big crow
come it goes off right right so right so
we're gonna we're seeing humans using
technology like robots to lie to other
humans and we're seeing some of the very
earliest evolution of deception in these
in these sort of artificial intelligence
systems what was were those robots
actually programmed to learn deception
so they just they were given these
constraints and objectives and the
objective was to get as much of this
food their electricity as possible and
that they were competing with these
other robots and so from that they
learned that you know deception was a
good tactic to do and we see this with
with non-physical AI so things like
chatbox conversationally I in a
negotiation game where they're
negotiating negotiating with another
human or with a human or with another AI
we saw that that deception that same
kind of idea of deceiving evolved in
that as well so it's it's pretty clearly
an advantageous evolutionary strategy
once you're able to communicate
something that isn't necessarily true
then deception becomes a strategy for
achieving your goals
it comes with risks so if you're having
a one-off interaction with another
person where you're trying to get goods
from them then deception can be very
useful but over the long term deception
has been shown to not be necessarily the
best strategy so are we moving in any
particular direction around around the
design of robots I mean I'm thinking are
they going to become more human-like
less human-like or does it really depend
on the context yeah I mean that's a
really great question and I think
Justine Cassell who did the keynote
yesterday I think sort of like wreath we
asked that question which was it's not
about what the robots or the these
conversational agents and their
humaneness necessarily but rather about
our humaneness and so she really put us
into this concept of intercept
subjectivity which is when I feel like
I'm engaging with the technology
I'm doing that as a human and I'm having
a very human attraction then whatever
that agent is is a success in that
regard so it's about creating a sense of
of intercept subjectivity and I thought
that was a really nice way of asking the
question because then they can be
human-like and they can be machine like
but it's going to be about how that's
sort of dyadic interaction works so I
think it's you know one of my
intellectual Heroes is is herb Clark
who's also at Stanford and and his work
shows that a lot of conversation and
interaction communication is really
tightly coupled it's a joint action so
what we're doing right now is very joint
so we're nodding at each other and we're
agreeing and suave the right time and
looking and I know I'm in a very human
activity right is amazing joint activity
of communication and so that's what's
gonna matter I think with with robots
and with with you know AI type
technologies is Lugar to which they're
coordinating with us and and and
building up that in your subjectivity so
they could look kind of artificial still
machine-like and exactly it will relate
to them in a right way right in theory
Brazil's geebo and you know she gave the
first keynote here doesn't look human at
all but people really react to it right
yeah oh she showed was amazing evocative
right and then they're having this meal
pleasant and and intriguing and
surprising kind of interaction and
there's zero you know appearance of
humaneness but geebo has this ability to
sense and respond in a way that feels
very evocative and it's kind of like you
know people love dogs right and they
don't look human at all but you know
people form these really deep bonds with
them and it's because of that sense of
intersubjectivity
well it's very interesting yeah thank
you so much for for being with us today
my pleasure Kim I really enjoyed it
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