Designing AI for Wellbeing (Derek Lomas)

I think we all know recording is on so
that X started recording I think so this
is an information so has Derek wanted to
record the session for people who can't
attend if there is someone that doesn't
want to have the finished recorded just
switch on the camera and that's the
general information so as you might know
that a kiss from the from my department
actually we are from the same place from
the human centered design department is
the new name it is a correct and in the
Faculty of industrial design engineering
doing research and teaching also on AI
for well-being that's correct right and
it's going to show us some projects and
research on how to design meaningful AI
that is meaningful for people and also
trigger some reflections on
controversial aspects of it and I would
say I just leave this stage to you Derek
so you can say more
great thank you I will start my screen
sharing and you can see yeah okay great
but yeah thank you so much for the
invite and the intro this is a topic I
care a lot about when I came to Delft my
interests were around data-driven system
design and figuring out what we want to
be optimizing in those systems I was a
little reluctant to attach to the label
of AI just because the artificiality
seems to exclude humans but no it's the
it's big tent and I'll be talking about
that so in this presentation I'll give
a brief intro and then share a bit of my
design and research journey I'll share
it not quite a design framework but a
towards a design framework for AI for
well-being and definitely open to
comments and feedback as I develop this
and there are a bunch of design examples
that will hopefully be useful for
discussion and we'll see where that
leads us so we're right at the beginning
of all this you know we've been you know
this is what since the late 40s when one
can argue cybernetics but if the world
doesn't collapse which it seems like it
is you know another 50 years we're gonna
have some pretty powerful systems out
there and there's really a concern about
how this is going to play out that the
power of these systems whether they're
actually going to enhance our humanity
or degrade it so you might be familiar
with some of the work that's been going
on an ethical AI just to summarize this
real quick
great recent paper by Florida looked at
some 47 different principles of ethical
API and distilled it down in five
basically it should be good and it
shouldn't be bad it should support human
control it should account for bias and
it should be explainable but even within
this it doesn't really get at what it
should be optimizing for and that's
something that I think is is really
critical it's partially in the be good
part but it's it's hard to
operationalize so you know we need to
have AI systems that don't dehumanize us
that are good for our well-being
and one of the big issues is the
intelligent systems by their nature
optimized numerical metrics but some of
those metrics are more accessible like
GDP or click-through rates than than
others like human wellbeing which is
harder to measure especially in real
time and it's hard to get a lot of data
from it so Don Norman sent this out
yesterday so I thought it was relevant
this is in the context of the dumpster
fire that is the United States of
America at the moment and he's saying
that you know we need to work together
build a long term future um there are
major issues around the world in terms
of hunger poverty racial prejudice and
then he said we need to get rid of the
GDP as a measure of success and replace
it with measures of wellness and
satisfaction so that's that's great
Don ID I really appreciate that that
sort of sets things up here Don was my
postdoc advisor and he wrote the book
design of everyday things and this
notion of shifting from GDP as a measure
of successes is interesting and
challenging so the the main design
challenge as I see it is to design these
well-being metrics these metrics for
good in a sense that they are accessible
to AI systems and to do that we need to
translate our humanistic felt values
into numbers and that is a tricky and
fraught task so this is something that
is economically important so Mark
Zuckerberg a couple years ago was making
some changes to the newsfeed that we're
going to reduce revenues and wanted to
prepare investors for that saying that
we feel a responsibility to make sure
services aren't just fun to use but also
good for people's well-being and so I
think we can all agree that we can leave
to Mark Zuckerberg and he will figure
this all out that's a joke because
Facebook right now is a serious threat
to the stability of society I think one
can very reasonably argue is not figure
this out
but it is important and even from a
self-interested perspective of a
business you can make some short-term
revenue gains but if you're really doing
something that's bad for people bad for
society that is a long-term risk so just
to do some level setting examples of a I
usually this is best approach from
examples so we've got the fame here
we've got the Facebook feed Amazon
recommendations Netflix queue Google
search any online ad that you see
anytime you make a purchase the sort of
fraud detection algorithms that are
taking place facial recognition voice
detects autopilot I think is a great
example of AI because it was invented in
1914 so um that's that's a good example
oh and then this is uh this is a piece
that's sold recently the AI art market
is still fairly small but you know we'll
see where that goes so oftentimes people
try not to go too far into the
definitions of intelligence but I really
like Peter Norvig research director at
Google's definition so he says the
ability to select an action that is
expected to maximize a performance
measure so a little bit arcane but the
basic idea is that to act intelligent
you need to measure outcomes you know
everything in that sense is quantifiable
but even from a human intelligence
perspective Robert Sternberg also talks
about success intelligence that
essentially you know stupid is as stupid
does and smart is as smart does if
you're doing something that's adding to
the success of your system then that's
that's a smart move and you know being
able to have a measure of your successes
is critical for this and so those
measures of success and that
optimization of those measures that's
really at the heart of intelligence now
I like to take things back you know to
cybernetics I think cybernetics is a
much more coherent design perspective
than artificial intelligence
you know conceptually theoretically and
you know this is from Norbert wieners
1948 perspective on perception action
feedback loops this is applicable not
just to digital or artificial systems
which is why I like it so much it it's a
general theory of of governance in
systems including biological systems
it's extendable to business systems I
like the notion of a continuous
improvement loop I think it's a very
helpful framework for for designers that
you want to assess and adapt so you're
looking for ways of measuring outcomes
and then modifying your designs in
response to those measures or maybe more
humanely you want to identify areas of
need and then you want to do something
about it and so this this means that
even the design of a chair can be set up
as a cybernetic system if you are
gathering feedback on the outcomes and
making modifications in in response this
is very generalizable but it's also I
think quite specific and so I like it
you wrote a paper about this recently
for tea MCE designing smart systems
reframing artificial intelligence for
human centered designers so just to tell
you a little bit about where I'm coming
from so
when I started my PhD at Carnegie Mellon
in the human-computer interaction
Institute I had just gotten into game
design for learning and looking at the
potential of using low-cost computers
and creating software for low-cost
computers that could have an impact in
developing countries looking at how to
scale digital education by making it
engaging and effective and the
engagement part was so critical I was
really excited about the science of fun
ya wanted to be a fun ologist I am a fun
ologist and wanting to combine that with
learning science and AI and my notion of
phonology at the time it was it was sort
of imagining all these sensors and EEG
posture sensors all these different ways
of measuring fun how do we how do we
measure fun because that's what we're
trying to do optimize and you know we
had these games like this battleship
number line game you're trying to blow
up these targets on a number line you
know you're given a fraction and you've
got to find this hidden submarine made
all kinds of different games for
mathematics release them on app stores
and online ended up making some forty 45
different games on different platforms
and you know big question around all of
them was was whether they were working
and how did we measure whether they were
funny and I came to learn about a/b
testing in online products so this is
some estimates are that there's over
10,000 a day run by the big tech
companies or they'll take different
design variations and randomly assign
them to users and
which design has the best effects on the
outcomes and those evaluation criteria
that the outcomes they could be anything
from revenue to click through rates
whatever is available and I thought it
was a little bit sad that there was so
much technology and an effort put into
improving online advertisements instead
of improving educational outcomes and
what I what I found was that in my
desire to measure fun it didn't take all
those sensors really all it took was a
measure of how long people were
voluntarily playing so this measure of
engagement which was really what we
wanted in the first place with these
educational games we wanted students to
be voluntarily engaging in these games
and playing them this was a great
measure of motivation and a great
measure of fun and so Mihai chips on me
I he's he's famous for his flow theory
he has a particular notion that when
your abilities and a challenge in your
environment are balanced then you can
achieve flow and so the the implication
here is that things shouldn't be too
easy or you get bored or too hard or you
get anxious but when they're just when
there's just enough challenge you enjoy
it
and so yeah not not too lard not too
easy so we have this hypothesis that in
our games if we had a moderate level of
difficulty we'd have the maximum
motivation that kids playing our games
because we get a few thousand players
every day that if we randomly assign
people to different levels of difficulty
then somewhere in the middle we would
find that optimal difficulty where we'd
have maximal motivation maximum fun and
so this is uh this is the the game that
this battleship number line game you're
either typing in a fraction or you're
clicking
at where you think a fraction is and
this is how it looked like back then so
you type in and you click yeah okay so
really simple game yeah again this is
what it looks like now and we're running
these experiments again we actually were
collaborating on an open source a B
testing platform that's funded by the
Bill and Melinda Gates Foundation and
that Eric Schmidt futures fund so this
is a a B testing platform for
educational software it's called upgrade
so that's a current project I'm working
on so back then to create these
different variations of game difficulty
we'd very different design factors so if
we made the target bigger it would be
easier to hit if we made the time limit
longer there's a better chance that they
could answer successfully and certain
items were easier than others and so we
ran in a super experiment with yeah
13,000 different variations at 2 by 9 by
8 by 6 by 4 by 4 factorial with about
70,000 players and to test this
hypothesis so that this was creating all
these different variations in difficulty
and the idea was is that according to
this theory of at moderate difficulty we
should have maximum motivation what we
found was that when we when we created a
model of the difficulty of all these
different factors pretty much the harder
we made the game the less time people
played and the easier we made it the
more time people played and so this was
a bit of a shock
we ran a number of different follow-up
experiments we did find that novelty
worked really well so when we balance
the amount of novelty in the game that
produced this sort of inverted u-shaped
curve and so we we said okay well it's
not not too hard not too easy but not
too hard not too boring people like
things to be easy if it's new they like
to succeed but so all of all of this is
is just this way in which we can use the
scale of experimentation to both
directly improve the the software but
also to improve the theory underlying
the software so you know we use learning
theory to design these games we bring
them to millions of users and then you
can run these experiments which either
have a direct applied outcome sort of
like a normal a B test or we can
generate new theory like this idea that
it's not too hard not too boring and
this is this is something that is is
generalizable beyond education just that
we can use theory to inform designs and
then when they're it's scale we can run
these different types of experiments to
create generalizable theories about the
effects of designs and so you know we
had about five thousand players subjects
a day and we were able to run thousands
of these experiments every year but it's
it's difficult to set them all up and so
we started thinking about this a I
assisted science of motivation and so
that's a good point to pause if you know
twenty one lessons for the 21st century
or sapiens Homo dias you've all know a
Ferrari has been talking a lot about the
risk of hacking human beings so when we
have
theory and practices that understand how
we operate better than we do ourselves
you know when some other actor can kind
of predict how we're going to act
they're able to manipulate us
so it's against our interests of course
in our case we're trying to do this in
the service of education but that's
probably not the intention behind many
of these experiments that are that are
taking place so this is a pretty serious
risk but this this was our effort to
embed this automated scientific
experimentation at scale paper called
interface design optimization was a
multi-armed bandit problem and the idea
was that we've got this feedback loop
where the online game is used by the
thousands of players and then we use
machine learning sort of simple
reinforcement learning algorithm this
multi-armed bandit approach to search
the design space and figure out which
design improvements are most effective
and automatically increase game
engagement and so this this actually
worked and it worked pretty well but we
started getting these phone calls that
there was a bug in the game and when we
checked out what the algorithm had done
it it made the game something that was
no longer having any real educational
value so all it did was just
dramatically increased the size of the
targets and it decided that that was
what was generating the most engagement
and the problem for us was that yes we
were trying to increase engagement but
we were also trying to improve the
learning outcomes and that wasn't
incorporated in our in our metric in our
optimization metric and so
this showed that it's really quite easy
for AI to optimize for the wrong thing
it also showed that it was a little bit
silly that we just tried to create a
closed-loop system that excluded people
designers it wasn't just like we had a
dashboard we were able to kind of
monitor this so so I suppose technically
there is a human in the loop insofar as
we could look at the numbers but there
wasn't a human in the loop in terms of
monitoring the experience of what was
being optimized and so that's that's
something that's really pretty important
is making sure there's a bridge between
that experience that felt experience and
the quantitative optimization and then
finally that there really is this need
for a continuous alignment between the
objects of optimization and the
underlying values that are behind the
system so this comes to this design
framework that I'm working on around AI
for wellbeing so Delft has been really a
center yeah please sorry we can address
one question that was in the chat if
it's still or maybe it already
Jared what do you because I think it's a
nice now we'll move into the framework
and I thought it was a nice moment if
someone has questions so know when you
were talking about it I was noting like
he was making the jump from education
program fun equals engagement ego smoked
deviation equals playing time and I was
like worried that you were going to
optimize playing time and run into
problems but that was precisely the
point you were making so no it's not
other question any more you already
answered it yeah yeah I kind of set
myself up there yes
so you're thinking about exactly the
right things yeah feel free throw more
questions in as we go and then whenever
I come to a pause I can
to dress yeah there is Afghani that
would like to ask a question I think yes
thanks
Derrick I'd like to ask a question about
so one of the introductory slides that
you gave where you talked about the
definition of one definition of
intelligence so that that definition
that seemed to really focus I knew you
you you came back to this point several
times the idea of maximizing a
quantifiable success and this is so I'd
like to just to to discuss this a bit
more with both hear your thoughts in
more detail about this because it seems
to me that there are many situations
where we are not able to you know put in
a quantifiable measure such a thing as
low being and when we talk about
intelligence if we talk very narrowly
about intelligence is focusing on this
kind of aspect we may be missing out
many many other dimensions of what it
means to different people and society in
a given context of what well-being means
maybe maybe you will be addressing this
in the in the in the remaining parts of
your presentation but I'd like to hear
your thoughts on this thank you yeah I'd
say that that is really the story of the
presentation and so I think that this
would be a really good question to
return to you with that at the end
because it's um it's really central to
the challenge I think sure sounds good
yeah
yes yes a Derek thinks so for the
example that you end it with where the
game optimize something that you really
did not want to optimize this I think
typical example of what they call an AI
reward hacking right so you have a
reward function and you optimize the
heck out of it and you get something
that was not the intention so I was
trying to understand your last slide
what are you saying are you saying we
should keep optimizing the reward
functions and try to get closer and
closer to what we really want or do you
say well this is an impossible task
maybe Eva you set in the beginning of
only a tricky but a fraught task and we
should never get the human out of the
loop to make it a little bit black and
white so where are you in oh that's what
I would break apart the the the option
that you gave there so I I think it's
really important that we try and that we
don't give up the the effort to quantify
some of our most deeply head held values
even though it is a serious risk and
it's part of why I think it's really
important to do this work in an academic
context because it you know that I can
imagine there being proofs that this is
a bad idea but I don't think we'll get
there until we try and what I'm more
concerned about is that if we abandon
the effort to measure what we treasure
the systems for optimization are so
powerful that they will be used on
values that we don't care about as much
and just an example here is something
like test scores and education and
well-being and education so we measure
test scores we don't measure well-being
and well-being is an input to education
but it's also an output of Education and
by because we don't measure well-being
it's almost invisible to large
institutions so large institutions are
unable
to take institutional action to improve
well-being without measures and
awareness or at least that's that's an
argument that I'd make yeah it's an
interesting point if I may because this
is not necessarily tied to artificial
intelligence machine learning or any
recent advance of Technology this is a
this has been a problem of society for a
much longer time we quantify stuff and
we know that we're limiting to that like
your GDP example but hey there's nothing
else I will live with it and we have a
certain resilience to the interpretation
of that number you would hope
reducing deeply held values to just
numbers and so I think you know I
definitely sympathize with people that
have had a lot of really nice arguments
with people about whether we should be
measuring at all these things that we
value and what the alternatives are and
from my you know again my perspective is
that it would be dangerous to not try
and I think that the solution is not
just having humans in the loop but
having this continuous alignment
methodology so really moving away from
autonomous systems
I think autonomous systems are an
illusion and I think they are it yeah I
feel I'd be interested in encounter
examples but I think that they are such
a profound illusion that they cause a
conceptual barrier to the proper
involvement of people simply because
it's interesting that things can be done
without peace
even though you know the involvement of
people can make the system work better
so that's why I put the you know instead
of saying we're going for artificial
intelligence here no no we're going for
smart systems if the involvement of
people and algorithms make the system
work better that's always preferable to
a purely autonomous system okay thank
you very much Derek I think time for the
next question yeah damn it with a
complex question or at least it's long
indeed yes so thanks a lot for the for
the talk so far and my my question is
about your connection to flow from
Csikszentmihalyi and so my understanding
flow is a dynamic emergent property and
it seemed that your hypothesis was based
on the assumption that humans would stay
static but perhaps I misunderstood and
so my question was it seemed your
machine learning example actually put
some dynamics in and in making the game
more difficult perhaps his people
progressed and so I was wondering if
there would be a difference let's say
underlying hypothesis for the change in
task difficulty and all these these
elements of your game yeah more related
to the dynamics yeah so I I didn't
include a lot of this background but
part of what I was responding to was a
study done by chip send me hi very
recently that that tested this
hypothesis about moderate difficulty and
enjoyment with chess games and showed
this very clear inverted u-shaped curve
and my my conclusion out of all of this
is that difficulty is not the same as
challenge
actually so difficulty as defined by as
the probability of failure is not
actually what he means by challenge
going back and looking at what he's
written in past work and that challenge
actually has a lot more to do with
novelty and suspense and and choice even
than difficulty and so that's one piece
I also don't really buy this balanced
approach as a design method my current
leading there chick semi-high and sort
of hypothesis around flow which is a
beautiful concept I mean it's a really
beautiful concept and I share your
reluctance to simplify it into the you
know just difficulty I view flow as
whole mindedness so when it is the only
thing occupying your attention and
behavior that that is really the
underlying nature of the flow state when
everything is harmoniously coherent and
Csikszentmihalyi talks about that
actually extensively but I think part of
the value of his model with regards to
challenge and ability is that it's more
measurable and at the very end of the
presentation I probably won't have time
to get to I talk about how well at 1:1
approach for how we might be able to
measure that deep engagement with with
EEG and and some work that I'm doing
around that but yeah transition is what
I what I would position is the core
theory of flow
I have a suggestion from personal
experience you have to measure the
amount of time between that you need to
go to the bathroom and actually going to
the bathroom thank you what's that what
the hell is that I would say again
excellent I like that
okay well on that note all I'll keep
going but keep throwing in questions and
so here's this this basic design printer
so Delta's been a great place a Peter
Desmond on a pole Meyer have been
promoting and developing this theory of
positive design that combines a design
for virtue you design for pleasure and
design for personal significance as a
design early approach for well-being
they primarily use this perma model of
well-being but they're pretty open to
the various measures and models of
well-being and you know in addition to
positive emotions engagement
relationships meaning and accomplishment
they're obvious things like physical
health that include factors like sleep
nutrition and exercise and mental health
there are many factors that affect
well-being one of the interesting
notions about well-being is how
amazingly unitarity of a concept it
becomes of a construct it becomes in
terms of subjective well-being because
when you feel good that is really be
part of it and of course there are
things you can do that can make you feel
good momentarily but not in the longer
term and that's that's the whole
challenge of human life in a way but it
is incredible how much gets integrated
into this singular notion of
feeling good so again this idea of
cybernetic loops and smart systems the
algorithm for AI for well-being is that
we need to assess well-being meets and
do something in response it's not that
complicated
it doesn't necessarily involve machine
learning at all but it does involve the
assessment of well-being and this is
you'll see this in a number of
subsequent examples a place that I think
design and human centered design have a
real role to play as an aside I'm doing
some work now with Freddy Hooper share
on the role of human centered design in
AI system production which i think is
there are a lot of roles for human
centered designers in AI not just the
development of measures there are a lot
of different places where human centered
design plays a role and that's that's a
topic for another talk
but this towards a framework so first of
all that human intelligence needs to be
welcome in these AI systems or smart
systems for well-being it cannot be
something that is a kind of gadget
oriented approach it needs to be
involving human decision-making and
human awareness and I'll give some
examples of how I think that contributes
to the efficiency of the systems and you
know how to humanize that the AI because
in and in human AI future is just
doesn't sound right so another part of
this framework is this idea that smart
systems or subsystems I really really
think it's important to recognize that
we're always designing subsystems or
never making an autonomous system it's
always part of something else and
therefore we need to think about those
interfaces
um in general we want to be focusing on
improving measures but we should be
looking at diverse measures of
well-being and a key idea that I think
is that the best articulate and this
talk is how to combine metrics with
design early vision and Paul Hecker
wrote the book on vision and product
design and it's largely his notion of
vision that I'm referring to here but
what I see is a productive tension
between the qualitative and the
quantitative the felt experience and the
measurable these are not choices these
are two approaches to the world that it
goes back to some of the earliest
philosophy the Pythagorean idea of
numerical harmonies in the cosmos
but this this idea that there is a
tension between these approaches and
that that tension is productive so when
I teach design students I often have
them develop measurable goals you know
two SMART goals right you want to have
goals that are very clear and measurable
but you want to supplement that with a
vision that is that is felt that is
metaphorical that is giving the sense of
feeling that you're going for
not just the the defined operationalize
goal and when you have those both
together they work with each other and
this is this is an approach that I think
is useful in in any kind of design
process and is is really critical for an
AI system that will by definition have
these defined operationalized goals but
having the vision and developing strong
visions of what that future is that we
want to
I think is critical so now I'm gonna
give some examples but I can take a
moment if there are any questions Jenna
wanted to ask a question right yes so
it's it's might be a small question so
I'm wondering which of the following two
questions or another one you are trying
to match are you looking for a good
metric for good AI or are you trying to
find out how we should use such metric
so I have a feeling that's different
questions are hearing your story and I'm
not sure do your most on well I think
it's the former but I think the former
implies the the latter so you know yes
what how do we want to think about you
know so Facebook take Facebook they want
to improve user well-being
with their newsfeed how do they measure
that I don't know whether what they're
doing is working how can they approach
that problem in a tractable way and when
they have found something how should
they go about responding to it I think
those are part of the same effort I'm
not convinced yet but I'll wait until
you've given more examples to throw more
questions about that to you yeah great
and and please do that's a good point of
clarity that I'd like to address so yeah
any other questions before I go on to
these examples I didn't see has pretty
late yeah so most recently the notion of
well-being has come up quite strongly in
the context of the Cova 19 pandemic and
so we've produced and released a new
system called my wellness check it's an
open science project to understand human
wellbeing at
scale and over time the pandemic has
produced a lot of effects on our economy
a lot of effects on individual and
social health and a lot of effects on
mental health and so in trying to
understand how the lockdowns and other
actions are affecting people's
well-being we wanted to figure out
what's up what's a better way of
measuring it how can we use human
centered design to understand what
people are going through and you know
what their needs are and how can we
responsibly assess and and from there
think about what we can do about it so
this is eventually trying to produce mmm
this complete cybernetic loop but the
emphasis for now is on using design to
improve the assessment of well-being
over time and so this my wellness check
dot org this is a website and encourage
you to sign up you'll receive messages
via email or SMS that asks you to fill
in a short assessment of well-being and
the the idea is how could we come up
with a sort of weather report to
understand how well-being is affected
and changing over time so these are just
some example screens that people have or
asking people about their energy level
we're having them fill in emojis that
represent some of the feelings that
they've had recently and really trying
to be innovative around the types of
measures and assessment while still
including standardized validated
measures all while keeping things as
short as possible
so in the past month after after a month
we had just over a thousand total
responses and one thing that was quite
interesting that one of the most common
measures of cognitive well-being is life
satisfaction and you can see this
bimodal distribution popping up where
there are a number of people that are
really they're struggling they are they
are dissatisfied and you can see some of
the recent behaviors people are having a
hard time exercising sleeping not so
hard of a time eating and these are just
some of the other questions and then the
qualitative data that's come out as well
you know by far been the most
interesting part so we we've gathered a
lot of this and being able to see how
our people for instance with financial
challenges with low well being affected
differently from those without financial
challenges you know that are also
struggling so here are just some some
quotes one in the middle is a person
who's doing well they've they feel like
they've been doing better since the lock
downs and these are just representative
quotes so this this project continues
we've now yesterday we had to redesign
pretty much all the messaging because of
the protests in the States some of the
emphasis on Kovan 19 alone has started
to sound a little tone deaf and so we
needed to adapt the the messaging and
the questions to try to capture how
people are are feeling without trying to
is it too much on the the political
situation but you know when there are
riots and dozens of cities across the
states people aren't doing well it's a
pretty clear sign and again this comes
back to some of the orientations of
replacing GDP if this isn't a technology
there are some technology challenges in
that I mean if we want to better assess
well-being if we wanted to improve
well-being address people's needs in a
more systematic way as opposed to just
grow the economy and there are real
technical challenges with that but it's
not just a technology issue I mean it's
a it's a policy issue and that's
something that is a philosophy issue and
these are things that we can't help but
engage with we need to engage with as as
designers and and human beings it's not
always going to be at this social level
but even in the context of a company
that's you know setting up new metrics
for optimization the question of of what
those goals are and how those metrics
represent those goals this is this is
something that I'm trying to prepare
designers to be able to dialogue with I
think they need to have the the you know
some basic data science skills and they
need to have some basic rhetorical
skills to to engage these political and
philosophical questions so now I'm going
to go through a set of design examples
from students so this is an ITT project
that used a nightlight that would
respond to a child's mood as represented
by these different
and it was also tracking the button
pushes overtime and saving them in an
app and the idea was to help families
talk about emotions and keep track of
difficult emotions and support
social-emotional learning it's a cool
project this is and in this project
you'll notice there's no optimization in
the system the system is providing
measurement but any sort of optimization
is only on the human side in contrast
this good vibes project a smart blanket
to help insomniacs fall asleep faster
this uses vibrotactile vibrations that
are embedded in a way to blink it you
get this kind of body scanning huh up
and down your your body it just feels
nice sort of zone out and the intention
of this is to have it be based on some
physiological signals and so have a
closed loop here we don't you know we
can involve people but you don't really
want to be controlling it on your phone
while you're trying to fall asleep and
so this is a much more appropriate place
for an you know automated system because
you're trying to fall asleep and when
you do fall asleep it should probably
turn off those those sorts of decisions
so this is in contrast where the
algorithmic optimization you know should
be in the system
and not relying on on the people this is
another system like this that uses the
muse eg for channel EEG to measure the
individual peak alpha frequency of a
person's brain waves so most in the
visual cortex you can the Alpha
frequencies the dominant frequency and
individuals have different alpha peak
frequencies that range from you know 8
to 12 Hertz this varies between
individuals and over time and the
hypothesis is this has not been tested
is that by flickering lights at those
frequencies or at offsets of those
frequencies will be able to disrupt the
rumination loops that are associated
with depression and burnout the kind of
repetitive strings of negative thoughts
this is an example of trying to combine
artificial intelligence and human
intelligence so it uses adaptive
learning algorithms to keep track of
math facts that a student has mastered
and the ones that they struggle with and
to provide those to parents so that the
parent holding the question of their
child the algorithm determines what is
the next question to answer and this is
able to leverage the you know parents
ability to intuit their child's emotion
and support the motivation and so this
is this AI human teamwork approach that
is again just another example of
involving humans and AI and smart
systems census was the original
implementation of the my wellness check
but focused on a health care setting my
my my father had cancer this past year
he passed away and in the year that he
was on chemo I was just I was a little
bummed that the medical system that was
extremely expensive and super high-tech
didn't really seem to be very interested
in the other aspects of his well-being
as a patient
even on the aspects that would affect
outcomes like you know getting exercise
you know eating sleeping
they just weren't tracking this sort of
thing and other aspects of well-being
like yeah I'm talking it's are you doing
things for fun these these are both
inputs to medical treatment but they're
also outputs I mean that's the point of
the medicine is that you can have
well-being and that is somehow a little
bit divorced from the system today and
so this is just an approach for making
it easier for doctors or hospitals to
prescribe remote wellness checks neuro
UX is a company that started a couple of
years ago with a psychiatrist at UC San
Diego we produce these mobile cognitive
assessment tasks that are used by
different psychiatric researchers to
assess working memory and efficient
control as well as these ecological
momentary assessment and what people are
doing different aspects of their
behavior attitudes etc and so the basic
idea is how do we get more data into
psychiatry so that treatments can be
better researched and supported this is
a graduation project with GERD quartum
and Jackie bourgeois with song shan liu
and the idea was to embed sensors in a
wheelchair that could identify behaviors
associated with well-being like posture
and indifferent exercises and then and
to motivate those behaviors so it was it
was a really nice project because it was
a clear you had a very clear approach to
the data collection and the alignment of
measures with these underlying goals and
it worked pretty well and cinah pal this
is a graduation project done with paul
Heckert and Mattias
Heydrich I should know how to pronounce
his last name but apologies this was in
response to the challenges observed with
Netflix and other couldn't modern
entertainment systems that are more or
less trying to hack us into consuming
you know spending as much of our
attention there as possible so he looked
at well what would an AI streaming
service look like if it were designed to
contribute to individual well-being and
there is this whole notion of how can
the system better understand a person's
intentions so that they can be supported
you know intentions everything from you
know how many episodes of Breaking Bad
do I really want to watch ahead of time
to what kinds of feelings do I want from
my media consumption and using a kind of
data collection and discovery process to
inform the streaming service this is a
really beautiful project that was a rare
graduation project that was launched the
day of graduation so this is available
for sale today
envision glasses with the t delta
startup envision this is a firkin Menten
and it was an application of google's
smart glasses for the visually impaired
and the key insight here was
how to use human involvement when the AI
computer vision breaks down which of
course that inevitably does and to allow
a person within the interface to very
easily call a friend or a volunteer or
paid worker on several different
platforms for the blind and it works and
it's it was a really well-done project
is a presentation this video very
defines it as the ability to live your
life without being helped or influenced
by others good also mean the ability to
discover new recipe chicken and pumpkin
soup means knitting an assignment just
before the deadline it could be sharing
your lap with a colleague looks like
Alex from finance to step up or some
fresh air and roam the streets with any
worry looks like a body of water running
through a grassy field just managing to
catch that train during rush hour
15:41 sprinted Amsterdam's patron by
memory evolved to be able to sort and
read my own letters credit card
statements post box two eight nine
should be able to quickly into my
favorites local store mango chutney it
is to note that when I get stuck
I've people to call upon hey there um
there seems to be a rough look here he
helped me out gonna help ya you want to
use so I wrote in it for something way
don't share my location All Hands
meeting to its minimum to look three
[Music]
looks like a birthday cake with lit
candles to cook my favorite meal that my
lovely family can't get enough of to
push my physical limits to move to jump
to function to feel alive I wish these
it happiest year again to be me to be
induced to be me to be yes abhi notes
introducing envision glasses the new AI
powered smart classes by envision
empowering the blind and visually
impaired to be more independent
available for pretty order now I'm so
sorry I think we finish time so if you
can wrap up a meet yeah that's that's
perfect so I'm right at the end here
I'll just say that there are definite
there are a lot of limitations and using
metrics
good hearts law is a big one to be aware
of that when a measure becomes a target
it ceases to be a good measure and there
here are some kind of ongoing research
questions you know we're looking at how
do we generally design AI for well-being
which metrics should be optimized how do
we translate our values into metrics and
what can go wrong there are some really
nice opportunities for using AI to
assess well-being so this is everything
from adaptive assessments like in our my
wellness check or in chat pots as well
as sentiment detection within writing
speech posture facial expressions and
even though by
sensing has been very unfruitful for
assessing well-being so far I do think
that there are some strong theoretical
opportunities that that I've been
exploring and I'll close with this one
this is more future forward but being
able to link AI and experience again
that kind of quantified and the
qualified so we've been using
convolutional neural networks to predict
the qualities of musical experiences
using high-density EEG data specifically
the enjoyment and familiarity and the
hypothesis is that neural entrainment
can serve as a metric for engagement and
enjoyment this is what I was referring
to in terms of the whole mindedness a
theory of flow that when you are fully
coupled to your environment
there are resonance processes that may
well be observable and this is an active
area in the neurosciences now and this
is a hard this is a hard problem but
it's been one we've been pursuing in
collaboration with a group at IIT in in
India and so this didn't in conclusion
here that I've got a very big interest
in the idea of harmony as a general
theory of well-being it's a very old
theory from Confucius and Lao Tzu and
Plato Pythagoras that there's a notion
of harmony and the self and our
relationships and society and nature lay
definitions of happiness so recently
these researchers interviewed some 3,000
different people and found that inner
harmony was a major component of how
everyday people defined happiness and
since harmony is often defined as
diversity and unity
there are these sort of pre-existing
measures of diversity and integration in
natural ecosystems and economic markets
and social networks and I think that
this frame of Harmony which is a
quantitative theory brings up some new
measurement opportunities so thanks a
ton for listening and really really
appreciate the opportunity to share yeah
thank you I've gotta do we still have
time for questions or we have to wrap up
and close well we still have 16 people
out there so if any of you have
questions we have time Derek and yeah we
can keep going for five minutes or so I
think I have eventually a question but I
want to give the stage to others if yeah
so I do have question for me I find it a
very inspiring talk also of many
examples so that you gave and I'd like
to come back to a point that you set at
the beginning or ending anyway about
autonomy so in the end what is your
answer to this you know for yourself to
what extent would you go for autonomy to
what extent would you say no let's keep
it basically like tools right yeah
tools very very strong on the tools side
I am very skeptical of autonomous
systems I think it's much better that we
design interfaces between systems and
not try to delude ourselves with pure
autonomy because I think it's very
rarely the goal using ourselves as
autonomous do I see myself as autonomous
beings in general so well in a certain
way yes we're in a certain way no I
think that our individual personas of
more losery than we often admit
um but at the same time our our desire
for freedom is very deeply ingrained and
and indeed necessary for for us to
thrive so I I think there's a important
philosophical relationship between
autonomy and interdependence that a lot
of people have talked about in the past
that when you have differentiated people
that are individuals and autonomous it
creates opportunities for
interdependence because of the diversity
of individuals mm-hmm yeah yeah I
understand okay Thank You Luciano maybe
you had a question
oh no yes I do have a question regarding
the first example you gave her so first
of all just thank you for the
presentation was very interesting very
expiring and regarding to my wellness
check platform you mentioned that the
people have like so much space you put
some qualitative data and I'm just
wondering because you have quite a few
thousand people ready respond how does
this scale up how can you manually go
there what can you do in the from each
how do you process this information yeah
it's a huge issue and it's something
that started to collaborate with SEPA de
who's been working with us and Roe
Poisson on some different text
processing approaches because something
like sentiment analysis is not so
interesting with it because people are
self reporting their sentiment but
because of that it allows the the
discovery like the basic approach that
we've been do using now is cream I'll
say creating an interface
even though it's really just like Google
sheets and things like that but creating
an interface for people to explore the
experiences that people are having using
the quantitative metrics for
organization so the quantitative metrics
make it much easier and more informative
to explore those experiences and then
the goal is really sort of storytelling
but it takes quite a bit of love you
know human engagement to make use it
yeah I can imagine that yeah okay thank
you very much
someone else asked questions or I can
ask something maybe because it's related
to my wellness check so I was curious
because you introduced it as a service
but then for now as far as I understand
you are collecting data right what will
be the service I finished so what will
it be and is it similar somehow to
existing AI with mental health
applications yeah
so the the service has a few different
stakeholders and initially the primary
stakeholder that we were imagining was
institutions institutions and
organizations that are no longer able to
check in on their people in person and
being able to make sure that everyone's
sort of doing ok anonymously was our
goal and so this is everything from
schools and hospitals and those sorts of
things and so in that sense it's a
service for those organizations to be
responsive to the well-being of their
people but you know the call that all
the data that we have now is from people
that are just signing up
and what we're building out is some
feedback loops where we first of all
allow people to self assess on
particular topics so you know take
validated assessments on anxiety or
loneliness or things like that and then
provide existing appropriate mental
health resources and then one other
aspect is that we've been gathering from
participants their own tips and
recommendations for supporting well
their own well-being and then sharing
those back out with people in the
interface so trying to have a kind of
crowdsource
plus AI approach towards community
well-being okay thank you other
questions or maybe we can wrap it up
here since we are a bit out of time okay
so thank you very much again thetic was
really nice and I hope to see you next I
gotta
which I'm not okay yeah thanks again for
the invite and appreciated the the
questions thank you
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