KYLE: OK.
So my name's Kyle.
I'm here to introduce
Professor Raphael Calvo.
He's here to talk to us
about positive computing.
He's the director of the
positive computing lab
at the University of Sydney.
And, along with Dorian Peters,
who's in the audience here,
co-author of a book
about positive computing.
And we actually have
a limited number
of copies of those available
outside for the $10 subsidy.
So please take
advantage of that.
So in addition to the
positive computing lab work,
he's the co-director of the
Software Engineering Group,
focusing on mental health
medicine and education.
He has a PhD in
artificial intelligence.
And in addition to being an
expert on positive computing,
he's done significant work on
effective computing, learning
systems, and web engineering.
So please join me in
welcoming Professor Calvo.
[APPLAUSE]
RAPHAEL CALVO: Thank you.
Thank you very much for your
kind introduction, Kyle.
As you said, I'm from
the University of Sydney.
This was the first
university in Australia.
Now they has about
50,000 students,
and just over 7,000 staff.
Sydney has a very
strong relationship
with the beaches and the natural
beauty across the country,
as you might know.
You might also know about its
reputation for sports, and some
of the iconic buildings,
like the opera house there
that was finished in 1973.
Now, back then in the
1970s, most people
were foreign to
digital experiences,
both here in the US, in
Australia, everywhere else.
Only in the 1980s
digital experiences
began to get into our homes
through personal computers
and gaming consoles.
In the 1990s, those
clunky mobile phones
started becoming smaller,
cooler, and more common.
And then these
mobile phones started
being able to do more than
just making phone calls.
And in just the last five
years, digital experiences
have begun become part
of everything we do,
from work, business,
friendships, relationships,
romance.
And one critical
question remains.
All these digital experiences--
are they making us any happier?
Is all this effort,
all this investment,
all this carbon emissions
having an impact
on our overall well-being?
Incredibly, according to
the statistics, it isn't.
It's not having any impact.
Populations surveys
for the last 50 years
or so show that wealth,
and, therefore, also
digital devices and
experiences, have
quadrupled in some countries.
Yet well-being has
hardly changed.
Now, as an engineer,
I have to ask myself
if technologies
are being developed
to improve people's lives,
why is the correlation so low?
So we have, over the
last few decades,
been designing for things
like productivity, efficiency,
accuracy, speed, and so on.
And only very
recently we have begun
to work on things like
satisfaction, pleasure, desire.
Productivity has always
played a starring role.
Productivity is generally
easy to measure.
It's easy to design for.
Computers, in general,
began as a tool for work.
And now, this has
gone way beyond this.
Now, computers are
in every aspect
of our moment-to-moment
lived experience.
Now, they see in us track,
measure, compare, judge,
everything we do, from the
number of steps we walk
and miles we run,
the friends we have,
even the number of
times we make love.
Yes, there is an app for that.
So we measure
literally everything.
This has created what we see as
a tyranny of productivity that
makes it all the more
difficult to focus
on one thing at a
time, to be mindful--
so I love that this
week is mindfulness week
here in Google-- to
pause, to disconnect,
to pay attention to
quality over quantity,
to take the time to
be kind, compassionate
towards other people, et cetera.
All things that
are very well known
to be critical to well-being.
In other words, we have
been designing for proxies.
We design for things like
productivity, wealth, pleasure,
because we think those
things will make us happier,
live a better life.
But now we know from
psychology that those are not
very good proxies.
The correlation of those
things with happiness
is not that high.
So we have been designing
for all these proxies,
but we have not been
designing directly
for the thing that matters most.
So if we want to
change or develop
technologies that increase
worldwide well-being,
we have to design for
well-being directly.
Directly.
In fact, we believe that all
technologies, all the products
that Google develops, all the
products that all the software
industry develops, all
digital experiences,
should be designed to support
psychological well-being.
And this is what we
call positive computing.
The research and
development of technology
to support well-being
and human potential.
And that's a shameless
plug for our book
here with Dorian Peters.
Now, when I give a talk to
engineers-- how many of you
are engineers here?
OK.
The majority.
The first thing that
people tend to ask--
is that something that we
can study scientifically?
Is that something that
we can actually measure?
Well, yes.
You can measure it.
And there are many
different ways of doing so.
I'm going to be covering
some of them today.
Psychologists, and particularly
behavioral economists,
have been working on many
different methodologies
that you can use to
measure well-being.
But first what I want to do
is to review a little bit
about how technologies
are changing us.
And then I will tell you some of
the different disciplines that
can contribute to different
ways of measuring well-being.
And then I will
tell you a little
but about our own projects.
So we know our brains are
adapting to technology.
Technology is changing the
way we remember things.
Technology is changing the
way we relate to each other.
Technology is even
changing the way
that we understand ourselves.
So the ubiquity
of digital devices
means that digital experiences
are slithering their way
into every aspect of our life.
Every aspect that
psychologists know
influence our
psychological well-being.
Obviously, the relationship
between technology
and well-being is
very, very complex.
There is lot of
research in this area,
particularly around social
networking frameworks.
So I have chosen here
a number of papers that
talk about this complexity.
So there are hundreds of papers.
Some of them talk about how
social networking decline,
produce declines in
subjective well-being.
Other ones have focused
on emotional contagion.
Other ones, that
are considered some
of the more nuanced approaches,
like the one by Maria Burke,
look into, or have seen,
that the impact really
depends on what you're
doing with those tools.
These papers show
about the impact.
There are other ones, like "A
Wandering Mind Is an Unhappy
Mind" by Killingsworth, that
talk about the new tools
that we can use to
measure well-being.
So that one in a particular
uses mobile phone technologies
to use experience sampling.
And what they did it they
had 5,000 participants.
And they asked people,
what are you doing?
What are you thinking about?
And how do you feel?
The first very
interesting outcome
was that up to 50% of the time,
we are thinking about something
else to what we're doing.
So roughly, maybe
half of you might
be thinking about something
else than my seminar.
The other interesting outcome
is that it doesn't depend
on the quantity of my seminar.
It doesn't depend on the
quality of our experience.
Our mind wanders no matter
what we're doing, OK?
For all type of
day-to-day activities.
Even in making love,
people were distracted
or thinking about something
else up to 30% of the time.
So this is one of the
many tools that we
can use to understand
people's experiences.
If you thought that 5,000
people was a large number,
think about the other
experiment here.
61 million participants.
It was a Facebook study that
show that different user
interfaces can change the
way people seek information
and vote.
And this was done in the
2010 congressional election.
So the input on behavior and on
people's experiences is huge.
Now, there are many
different techniques
that we can use to understand
people's experiences.
I, and a lot of people in the
human-computer interaction
community, have
worked on something
we call cognitive computing.
It's trying to understand
where people think.
And we particular
have been working
for a few years on technologies
around writing, particularly
academic writing.
One of the cool things about
writing, studying writing,
is that when people write,
is very hard for them
to be thinking about
something else.
So within that, what
we have been doing
is working, developing
concept map summaries,
different type of tools
and visualizations
that help us understand that.
And then those are
feedback interventions
that we can give
writers for them
to reflect on what the right.
Now, one of the best things
that we can do to help people
is to provide feedback.
But it's very
challenging to understand
the impact of that
feedback, to know which
is the best type of feedback.
So we have using
behavioral analytics tools
and visualizations,
like in this study.
So I hear different roles
or different writer.
Each of the is green balls
is a writing session.
So you can see
there's people that
spend more time writing,
other people that
spend less time writing.
And then we have two
types of intervention.
So the triangles are
reflective feedback,
and the squares are
directive feedback.
So in on one type of
feedback, we tell the person,
there's something wrong
in what you wrote.
And in the other one, we
say, there's something wrong.
This is what you
should do to fix it.
The cool thing with these
tools is that then you
can tracks and see if people
is reading the feedback,
if people is going
and addressing
the feedback, how much time they
spend addressing the feedback,
and so on.
The third type of
techniques that we are using
is affective computing,
so detecting emotions.
In this case, we have facial
expression recognition.
So the writer is working there.
And you can detect
if the person is
being bored, confused,
delighted, et cetera.
Here's another plug.
That's "Oxford Handbook
of Affective Computing"
that was also
released last month.
And that brings
research literature
from the whole discipline.
So the 50 chapters
cover everything
in the area of
affective computing.
The second thing that we're
doing with these tools
is looking at how they
can be used in training.
This is in medical education,
so we're using it in telehealth,
trying to help future doctors
connect better to patients,
interact better to patients,
through telehealth system.
So the system detects basic
emotions and acknowledgment
expressions.
So it could be
nodding and shaking,
turn-taking, et cetera.
And you can use different
modalities, not just
computer vision.
In this video, we have an
intelligent tutoring system
that is teaching the person
about information technologies.
And it will ask questions.
And the person replies.
So what you see there
on the top is what
the person sees on the screen.
And he's plugged to a number
of physiological sensors.
You can--
ON-SCREEN NARRATOR: Faster
and more efficient than CIFC
processors.
RISC has a reduced
instruction set,
which prevents fewer
bottlenecks in processing.
Also, RISC processors can
execute multiple instructions
simultaneously.
Let's go on to something else.
Take a close look at
these four pictures.
RAPHAEL CALVO: So
here what you can
see is the different
physiological signals are being
used, these machine
learning techniques,
to detect the
different emotions.
And the system can
then be adapted
to what the person is feeling.
If the person is
feeling confused,
you might give him
more explanations.
If the person is
bored, you can raise
the challenge of the questions.
Now, if we have
new techniques that
allow us to understand people's
cognitions, people's behaviors,
and people's
emotions, shouldn't we
be using these to
improve well-being?
And this is the
new field-- I think
it's a very interdisciplinary
field-- that we
call positive computing.
And so the disciplines include,
of course, all the ones
from psychology
and brain sciences.
Computing, there's
a lot of work being
done in the areas of
affective computing,
personal informatics,
persuasive technologies,
attentive technologies.
Very interestingly, there's
some work in education,
and a lot of work on behavioral
economics on well-being.
And finally, in design,
human-computer interaction,
value-sensitive
design, et cetera.
People there have
been working on this.
Now, this is a highly
interdisciplinary area.
So when we were
writing the book,
we sought advice from experts
in those different disciplines.
We're all [INAUDIBLE].
So here we have people
from positive psychology
and emotional intelligence.
Maybe the most commonly
used instrument
to measure well-being is the
DSM diagnosis statistical manual
depression scale.
They see as the
depression scale,
Center for Epidemiological
Studies depression scale.
These are small
questionnaires that
are considered so
reliable, for example
by insurance companies,
that if you score very
high on those surveys,
the insurance company is
willing to pay for
your treatment.
In these model, depression--
or the absence of depression--
means you're doing well.
That's the definition
of well-being--
the absence of illness.
Positive psychology
is a movement
that arose from the critics
of this clinical model.
People like Martin
Seligman, [INAUDIBLE],
Felicia Huppert,
they were focusing
on looking at the
factors that we
can use to identify those
peoples that are flourishing,
that are very high in
the well-being scale,
and then in studying
how those factors can
be promoted across population.
One of these factors,
or set of factors,
would be the socio-emotional
intelligence.
This is something that people
in human resources in business
has focused a lot, but
also in psychology.
And looking at how being able
to recognize our own emotions
and regulate them, how
being able to recognize
other people's emotions and
regulate them, and maintain
relationships, how
all those skills
help us live better lives, be
more productive, et cetera.
But mostly about well-being.
Some of these
factors also include,
in self-determination
theory and other theories,
things like autonomy,
competence, connectedness.
And generally, different
psychological theories
will have different factors.
Another approach
that has been taken,
especially by economists like
Nobel Prize winner Daniel
Kahneman, has been to follow
subjective well-being.
Ask people about
their subjective,
their personal experience.
Of course, asking people
directly what they think
sometimes is troublesome.
But using experience sampling
and other techniques that
have been developed by
economists and psychologists,
you can get a quite accurate
measure over a period of time.
Another approach is,
obviously, using neuroscience.
People like Richard
Davidson, for example,
has been studying the impact
of mindfulness training
on the brain.
So you can see how when you
promote certain factors,
you can see how that change your
brain over a period of time.
So different
psychological theories
will contribute to
our understanding
of these different factors--
autonomy, connectedness,
competence, meaning positive
emotions, engagement,
et cetera.
Now as a human-computer
interaction,
I don't have to
become a psychologist,
although, obviously, we
need to work with them.
We can combine some of these
different factors, some
of these different theories, and
look into how we can use them
into our own designs.
Economists, as I
was saying, have
been using measures of
well-being significantly.
The World Happiness
Report, for example,
provides a summary of the
statistics across the world.
This is something that
is done frequently.
Last one, I think, was 2012.
In the United Kingdom,
the government
actually has a special
unit of goals and surveys,
and measures well-being
across the country.
And here you'll see a map,
and the different regions
are mapped and measured, and
they use this in policy-making.
So they make decisions on where
to invest government money, tax
money, depending on the
impact it has on well-being.
And this has been done
across Europe, as well.
In the US, rather
than governments,
a lot of the initiatives
are commercial.
The Gallup Healthways survey
is done, actually, every day.
So they have the [INAUDIBLE].
You can go to a website.
And they give you
measures of well-being
in different
regions, done daily.
So all these are different
ways of measuring
subjective well-being.
And we have used
experience utility.
Those are of the measures
introduced by Daniel Kahneman,
other people.
You can also use experience
sampling techniques,
like the study I mentioned
on mind wandering.
Nowadays, we can start using
affective computing techniques
to automatically detect
things like engagement,
to understand better about
people's emotions, et cetera.
So you don't have to be
interrupting users that often.
Now, of course,
we're talking here
about well-being promotion.
Many mental health
professionals,
as the ones that we work
with, have to understandably
be focusing on mental illness.
But in this diagram
by Felicia Huppert,
I think it's very
interesting, because she
shows how moving the mean
can improve well-being
across the population.
So it can increase the number
of people who are flourishing,
and reduce the number of people
who have a mental disorder.
So that we should be using the
technologies, the approaches,
for mental health
promotion in the design
of all our technologies.
This is, I think,
where technology
can have the most impact.
And to design for
well-being, we could
look into the different
factors that psychologists
have identified.
These are some of the ones
that we cover in the book.
They are covered
there in more detail.
And for each of them, we have
looked into the literature that
shows that they are correlated,
strongly correlated,
or have an impact on well-being.
And there are a number
of interventions
that have shown to be successful
in improving each of these.
So for example, in
positive emotions,
is probably the one
that we focus most often
in human-computer interaction.
Designers generally talk about
delight, pleasure, and fun,
to describe their design briefs.
Now, generally, when we talk
about pleasure, fun, et cetera,
we do it because we
know that it will
make the product sell more.
People will spend more time
on the websites, et cetera.
There's very little
research looking
at the effect of the impact of
positive emotions in long term
well-being.
Some of that is done, for
example, by Jane McGonigal, who
has looked at them by the
impact of positive emotions
triggered by games, et
cetera, on personal change.
Don Norman has worked a
lot on emotional design,
the impact of how we can
use positive emotions.
So both of them also have
contribute to the book.
Another area that
we have worked on
is how you can use technologies
to develop empathy.
Often, here, it's about
role-playing games,
like in this one,
the Frontiers game,
that allows you to play either
the side of a person escaping
Africa, the refugee
into Europe, or the side
of a policeman whose job
is to stop these people.
Or this other one,
the Peacemaker game,
that you can play the role of
the prime minister of Israel
or Palestine.
And you can see what is the
impact of your decisions.
They have gone through so many
phases and decision-making
there, that they have
actual video that
shows when you take this
decision, this is what happens.
Developing altruism.
Here in Stanford, Jeremy
Bailenson , for example,
has works a lot on interventions
that can help people become
more altruistic and more
helpful towards others.
So in this experiment, he
allows you to play either
the side of Superman, so you go
flying around the city trying
to find a kid who needs help.
Or you fly around the
city, but your character
is just in a
helicopter, just doing
a tourist trip around the city.
then something happens when
you come out of the lab.
A person has an emergency.
And they measure how
much people help.
And the people who have
played Superman's role
is much more likely to help.
And they spend more time
helping the person that need.
We can introduce this in
everyday software designs.
I think praise, praise is
such an important element
in our relationship with others.
And in online systems,
we can actually
tend to optimise too
much through usability,
so if you look at the
design of LinkedIn,
and you probably have seen the
endorsements feature there.
Is so easy to endorse other
people for whatever skill
that it becomes meaningless.
Because I have been
endorsed for Microsoft Word.
It's like, what does it mean?
What does it mean when
you endorse someone else?
And the problem is that we have
made it so efficient, so easy
to endorse other people,
that people just do it.
Now, Yammer does
a much better job,
because you have to explain why
you are praising someone else.
And because of efficiency,
we are actually
missing the opportunity
of helping the two sides--
on the one hand, the
person who is helping,
and on the other, the person,
obviously, who receives
the help or the praise.
So what we have been doing
is working with organizations
like Google and others,
looking into how
we can introduce
positive computing
approaches into the development
of everyday software.
And we look at-- we call them
the happy camper factors--
because is just to
remember the acronym.
So you have competence,
autonomy, meaning,
positive emotions,
engagement, and relatedness.
OK?
This is a combination from
self-determination theory
and from PERMA.
That is one of the most popular
positive psychology theories.
And these factors have shown
to be effective in promoting
well-being.
And there are interventions that
we know work in promoting them.
I'm not going to go through
the details of each of them,
but the important thing here
is that software engineers can
go look at the impact this
has on their trade-off,
on their designs.
And the way you
can do that is you
can use those as
hypotheses, and then you
can do different designs,
and do AB testing,
and see which one has a positive
impact on any of those factors.
So when you introduce a new
product, you see, oh, OK.
I changed the interface
for Google Drive.
Is it increasing people's
sense of autonomy?
Or is it decreasing it?
Do people feel
that they are more
in control of the outcomes?
Or do they feel they are less in
control of the outcomes of what
is happening?
And studies have used
different approaches
to measure the impact of
the designs on well-being.
On this study, for example,
by people in Facebook
detecting emotional
contagion, they
looked into how
emotions propagate
through a social network.
And they used a very nifty
statistical technique.
So it was not an
experimental design.
They used weather.
So obviously, our emotions
do not influence weather,
but we are influenced
by the weather.
OK?
So if you have a
friend in Australia,
and he's enjoying
nice weather, he
will influence your emotions
through the social network.
So that's a really
interesting outcome.
Well, one, we already know
people are happier on weekends,
on sunny days.
And they use that fact.
But also, happiness spreads
more than negative emotions.
Positive posts
decrease the number
of negative emotions 1.8,
while negative posts,
and negative posts by
one of your friends,
decreases 1.26
the positive ones.
Another design that
was controversial,
because used an
experimental approach,
was this other study by Facebook
that you might have read.
And it also was looking
into how emotions propagate
through the social network.
So in this case, they had a
negativity-reduced design,
where the filter
in the news feed
show fewer news stories
from your contacts.
And another one there was
the positivity reviews.
So they show fewer positive
posts from your contacts.
And this, you
might have read it,
it was a very controversial
study, because is raised issues
about ethics, if
companies should
have different obligations,
ethical obligations.
I personally think
that it raised
an issue of the
value of autonomy
in design, because people
felt that they wanted to have
been able to change the filter.
And there is also
technical issue is,
are the things that we say
online a sign of empathy
or compassionate distress?
Is it always about
our own emotions?
So the interpretation
of the data
also is something
that could be debated.
So we have been looking at four
different ways of introducing
positive computing in design.
The first one is actually
not positive computing.
That is what we mostly do when
we're developing software.
So we do not
consider well-being.
The second one is what I will
call preventative integration.
So if you have an
application, and there's
a lot of trolling or
anti-social behavior,
you do a new design to try to
reduce anti-social behavior.
So basically, the
obstacles or problems
are considered like a bug,
and you go and fix them.
The next one is what I will
call active integration.
This is where we go and
introduce new features
that we think would
promote certain factors.
So we could go and
introduce a new word
processor that
promotes flow, that
has fewer distractions around.
So the person is
just concentrating
in that particular task.
Less mind wandering.
Another one could be a
social media, Google+,
that promotes
social intelligence,
emotional intelligence.
Finally-- and maybe
this is the one
that has received the most
attention-- is what I will
call dedicated integration.
So this is when you build an
app specifically for developing,
let's say, mindfulness training.
Goal-setting.
So the whole app is
just dedicated to that.
And here, you'll have to
read the whole-- it's mostly
a summary of the factors that
we have taken into account.
Each of them has a theory.
And each of them have
proven strategies
that have shown to work
in developing that factor.
And there are methods and
measures that you guys can use.
These are
questionnaires, surveys,
that have already been tested
for reliability, et cetera,
by psychologists.
And many of them you
can just go and use,
and see if that one
is having an impact,
for example, in building
resilience, building motivation
and engagement, et cetera.
And then we divided them in
self, social, and transcendent.
Self are those factors that
have to do just with you,
are internal.
Things like mindfulness
in mindfulness week.
Social are the ones that
depend on more than one person,
or what relationship
with others.
And finally,
transcendent is those
that depend on where we
care about other people
with whom, maybe, we
don't have a relationship.
Things like compassion
and altruism.
There are strategies
for each of them
that we can use and have
been proven by psychologists.
And we should be
introducing more of those
into our applications.
So again, we have
gone and asked others,
because this is such an
interdisciplinary work,
we have asked experts
in other disciplines
to provide and contribute their
personal, professional opinions
on how we can
support well-being.
And these are some of them.
And some of them are
collaborating with us
in a number of projects.
In this one is with the
Young and Well Comparative
Research Center in
Australia and retail.com.
That is mental health
organization for young people.
And what we're doing here
is helping moderators
in these social networks who
have to go, read posts, read
them by other people, detect
people that might be at risk,
and answered questions.
So these are things,
issues on relationships,
coming out, sexuality.
These are young people
that are seeking help.
And what we're trying
to help the moderators
be able to reach out to more
people, be more efficient,
but also enjoy and find
more meaning in their work.
In this work, we obviously
collaborate a lot
with psychologists,
psychiatrists,
from Brain and Mind
Research Institute,
and from these
other institutions.
So what we do here is
we automatically you
and grab the data from
their social media platform.
We process it
automatically using
machine learning algorithms.
And we can classify
what the post is about.
Is a person depressed?
Is a person anxious?
Is he seeking help?
And then we can automatically
generate some interventions
that are psychologically
informed.
So it could be a cognitive
behavioral therapy type
intervention.
It could be a psychoeducation
type intervention.
And the moderator
goes, sees the template
that we have generated
that is personalized
with information about
the particular individual.
And they can customize it.
So a lot of these
moderators are people
that have lived
experiences, that
have themselves suffer from
depression, anxiety, et cetera.
And then, so they can contribute
that to the other person.
There's a lot of human contact.
And then the
moderator changes it,
and it can go back to the users.
So, well, this is
moderator assistant.
And again, what we're trying
to do is use one factor here.
That is compassion.
It's trying to help the
moderators help other people.
In another two
projects, we're working
with young people in one
that have cystic fibrosis
or diabetes Type 1, in the
other one that have asthma.
And what the two
projects have in common
is that we're trying to
find ways in which we
can promote autonomy.
Doctors, medical professionals,
call this self-management
of the disease.
So they're looking for
new ways in which patients
can go out, and do what is
needed to do without having
to remind them all the
time, and controlling them,
so it's self-management
of the disease.
So we're looking for
new ways of doing
that using mobile phone
and other technologies.
Another project we are studying
now, it's in the workplace,
particularly in
male-dominated industries.
Males have a particular
mental health risk profile,
often because we don't go and
seek help when we need it.
We are working with the
police department, the fire
department, and
ambulance services
in New South Wales
in Australia, looking
at how we can detect
people at risk,
and then provide
them with services
help that they might need.
Another project that
we have been working on
is a new fellowship
that is basically
coming and talking with
organizations here like Google,
trying to collaborate, find
ways in which we can inform
engineers, developers, in the
different industries on how
to develop software
that takes into account
psychological well-being,
or takes into account
all the factors that
we just mentioned.
And this, obviously,
requires talking
with people from
multiple disciplines,
not just engineers or
psychologists in the company,
but the people in
other organizations
like mental health
charities, et cetera.
So just as a summary, we know
that technology is changing us.
There are psychological factors
we know increase well-being.
And these factors often,
very often, can be used
and introduced into the design
of the platforms we build.
And they would be
promoting well-being.
And positive computing
provides a framework
to support well-being
by considering
this multidisciplinary
work and targeting
the promotion of flourishing
in the software platforms.
Thank you.
[APPLAUSE]
AUDIENCE: I really
enjoyed the talk.
I agree with a lot
of what you said.
But one of things that
I've asked myself a lot
is let me go back to the
first graph you showed right
at the beginning about how gross
national product has increased,
but some measure of
happiness is not.
Whenever I've looked
at graphs like that,
I've always had two questions.
Is the gross national
product, has the GNP accounted
for inflation?
And B, are there
actually examples
of graphs where life
satisfaction has increased,
and not reverted back
to a mean, right?
So I was hoping to hear
your thoughts on that.
RAPHAEL CALVO: Yeah.
Very good question.
Yes.
The first one,
economists are very
aware of how to take into
account inflation and so on.
We have become wealthier, a
lot wealthier, some people more
than others.
But in general, across
society, societies
in both poor and
developed countries
have become much,
much wealthier.
The second one is
related to something
called hedonic treadmill.
Maybe that you have heard?
And there is some evidence
that after you've enjoyed,
you buy something that
gives you positive emotions.
Let's say you buy
a new mobile phone.
And you enjoy it.
And after a little while,
the new gadget you bought
doesn't mean much.
And your positive
emotions go down.
And then you seek
the next product.
Now, that refers to
hedonic well-being.
That is only the
positive emotions aspect,
the ephemeral aspect
of well-being.
And that's why there is
many other factors that
support well-being, not
just positive emotions.
Meaning.
If you find meaning
in what you do,
that will have a positive
impact across your life.
It's not going to fade
away after a few days.
If you involve yourself
in helping others,
being compassionate
or altruistic,
or if you work for
a not-for-profit,
that will have a positive
impact on your life
beyond one or two days.
So there are ways of changing
that kind of baseline that
expands for all your life, for
an extended period of time.
AUDIENCE: So there are obviously
a lot of subtle software
and user interface issues here.
All I'm wondering
if also the way
we interact with these
devices, we hold them and touch
them and look at them
then, and we talk to them
and they talk to
us, and they measure
our physiological
functions and so forth.
And from a McLuhaneque
point of view,
you might think that the actual
physical interactions that we
have with these devices might
also have a pretty profound,
regardless of the
details of the interface,
just the basic interactions
with these things
might have an impact
on our well-being.
And I wonder if there's any data
available, even tentatively,
on that.
RAPHAEL CALVO: The research, for
example, using seeing internet
and viewing TV, numbers of
TV hours, is very complex.
So I've seen papers where it
says that if you have a TV,
you will increase
your well-being.
And there are studies
that, obviously,
show exactly the opposite.
And then there are studies
that show if you have the TV
and you have the internet,
your decrease goes down.
And sometimes no.
If you have the two
together, it goes up.
I think we still have to
work on the methodologies
to measure that.
Some of those studies
are a little bit off.
The approaches that you have
for tracking and understanding
what people is doing with
those devices has changed.
So I don't have a simple answer.
I think there is studies.
In general, they are
very subtle differences
that can have an impact, no?
And you really have to go
into the details of the study
to see what is happening.
I think with the new
techniques that we
have to track people's
views of these devices,
then we will have a
better way of doing,
of understanding
what's happening.
AUDIENCE: So for many years
we brought people into labs.
We've stuck stuff to them.
We've pointed cameras
at them and et cetera
to sort of understand
these things, when we ever
bothered to look, which
wasn't very often.
Now that these things mobile,
people are all over the planet.
You can't bring
them in to study.
They're using devices like
the Fitbits and other things,
and all kinds of stuff.
And I'm wondering, what
are emerging technologies
and approaches to handling this
multi-device world in which we
are trying to understand the
technology impact on wellness
and happiness?
RAPHAEL CALVO: I think
that when we are developing
these new gadgets
like the Fitbit,
the different technology
for activity tracking,
they can have a very positive
impact on improving health,
and, possibly, well-being.
On the other hand,
you have to take
into account psychological
well-being that sometimes
is different to
the physical one,
and see if it's not
creating or triggering
different consequences
on different people.
So if you're
obsessive compulsive,
you might be more inclined
to use a particular tool that
tracks everything, et cetera.
The tool is not necessarily
helping you come out
of this pattern
that you have that
is likely to be affecting
your well-being.
So sometimes we do
studies where we
assume the whole population
will received these new tools
in the same way.
But that you have
people that have
the different
personal attributes,
and will react to them
in different ways.
And I think the devices
that you're thinking about,
like the Fitbit, et
cetera, sometimes
we look for general solutions,
design approaches that
will apply to everybody.
And different people will
have different impact.
If you have an eating
disorder, if you're
focusing on weight too much,
the impact can be negative.
Maybe for the
majority, the average
maybe is moving positive.
But then maybe you might
be affecting people who
need it most in a negative way.
So what I'm going
to there is that we
need to look at the
different groups of people
personalisation.
And when you design,
consider ways
of not designing
in a general way,
but also taking into
account minorities--
for example, people that might
be at risk of mental health
problems, or might be at risk
of physical problems, et cetera.
That was an issue,
for example, that
arose in that controversial
study by Facebook.
People argue, well, a number of
people that have mental health
problems, so if you are
driving and pushing them
towards more negative
emotions, that can
have very serious consequences.
AUDIENCE: I can see thinking of
an organization like Facebook
or Google, or a company
that's not Fitbit,
not directly trying to
create software that's
going to increase an
aspect of well-being,
I can see a strong
incentive for-- I
forget your exact term--
reactive design for well-being.
You don't want trolls on
your service, for instance.
What are the incentives,
do they exist right now,
for companies to take an
active interest in increasing
well-being, even if that's
not the main purpose
of their product?
RAPHAEL CALVO: Yeah.
That's a fantastic question.
I think yes.
Europe and Australia,
in many countries,
just to give you an
example, organizations
are liable for mental
disabilities caused by stress,
for example.
And they have initiated a
number of well-being programs.
So there's hundreds
of companies that
are looking at providing
servicing the industry that
helps those organizations reduce
the likelihood of having people
burn out, et cetera.
Now, you guys view the
software that those companies
are building to serve
the employees, right?
So if you can build
software that you
show reduces the
likelihood of burnout,
if you design a new
type of email system
that reduces the likelihood
of people working late hours,
that has a strong impact
on mental illness,
that's a fantastic sales point.
I think I will
love, and I would be
willing to pay extra,
if I have software
that I knew will
help my kids grow up
as stronger individuals, more
compassionate individuals.
A software or
platform that allow
them to have more
emotional intelligence.
And if they are relating to
other through social media,
if they use Google+,
if they use Facebook,
if they use any of those
products to connect,
and learn about other
people's emotions,
about interacting
with other people,
those platforms need to include
the things that psychologists
know promote prosocial
behaviors, promoting empathy,
promote compassion.
As a consumer, I will look
for that type of product.
As a person that works
in a large organization,
I know my organization will
like to know of products
that can offer that.
And there is already
companies that are doing that.
Yammer, for example,
has a number
of companies that are
providing services
that allow organizations
to understand
what is happening internally.
Like when a manager
changes a policy,
you can see, well, this
is what has happened.
Emotional state of the
organization changed.
Or it has activities
for people to engage
improving the connection
between the employees.
KYLE: Well, let's thank
Professor Calvo again.
Thanks.
[APPLAUSE]
