- Yeah, thank you.
Thanks very much.
I guess first of all thanks to Saskia and Gloria Mark
who sort of organize all these awards, I know
there's a lot of work to it in terms of
the viewers and things like that as well.
I'm Chris Elsden and thanks very much
for coming to the furthest away room.
It's really nice to see some people
who supported me and inspired me at various points
in the room.
I'm just very honored and grateful to get
the chance to talk about this work again at CHI.
So, I currently work in Design Informatics
at the University of Edinburgh.
Until very recently I was at Northumbria University,
but this dissertation took place at Newcastle.
And before I start there's a lot of people
that I need to acknowledge.
I mean these are just a few of the people
who in particular have hugely contributed to
me being here right now.
All I can say is they're all brilliant and
if you get a chance to work with them,
then grab it as you can.
And especially thanks to Dave Kirk and Abby Durrant
who really nourished me and gave me
just the right amount of freedom, and
not too much freedom that I did anything stupid.
So, my thesis, was, this was my thesis title:
"A Quantified Past: Fieldwork and Design for
Remembering a Data-Driven Life".
And the sort of genesis of my thesis begins here
with this quote from Gary Wolf, Gary Wolf is
one of the founders of the Quantified Self movement.
He's an editor of Wired Magazine.
And when I began my thesis, Quantified Self,
sort of 2013/2014, probably at a peak moment of
breaking into the mainstream but still felt like
this quite strange Silicon Valley practice.
And rather kind of rather peculiar.
So, Gary Wolf said, talked about data-driven life
in a New York Times article and said:
"For a long time, only one area of human activity
appeared to be immune.
In the cozy confines of personal life, we
rarely used the power of numbers.
The imposition on oneself or one's family,
of a regime of objective record keeping
seemed ridiculous.
A journal was respectable.
A spreadsheet was creepy."
And I think it's really this creepiness
that I found the most interesting thing to begin with.
The idea that keeping a spreadsheet about yourself,
representing yourself in a quantified and
data-driven fashion,
the sort of peculiar, creepy nature of that.
Yet a the same time the enthusiasm that's around it.
And so when I started my thesis I had the vague idea
that I was supposed to do something about memory
and digital technologies.
So I started to think about the personal histories
of this kind of activity in data,
what was and would generate.
And at the same time Nicholas Felton,
who's a self tracker and graphic designer
has already started producing these incredible
quantified annual reports about his life
to kind of already demonstrate the kind of potential
of a quantified past.
And so in the thesis one of the main contributions
of the conceptualization of what a quantified past is,
but I was really interested in the experience of
remembering a data-driven life.
What does this feel like to have this kind of data,
and what does it mean for us being human
to create these kinds of records of our lives?
And further, I was trying to be quite productive
in the sense of developing design considerations
for services and technologies that would
support us remembering, or at least having
a better relationship with this quantified past,
whatever it was.
I think my work is quite part of that critical turn
towards the design of self-tracking tools in HCI.
I think, sometimes at CHI we can be quite hard
on ourselves in terms of being our ability
to be reflective and critical.
But I think this here is a really interesting one
where we look back at some of the first seminal papers
in this space, which were about kind of very rational
stage-based psychological models hacking habits
for health and happiness.
And then as we've gone along, we've kind of developed
much more detailed and nuanced picture of
what it means to live with these kinds of tools.
From lived informatics, awareness of the politics
of data quantification in general, in these tools.
I see my own work as part of this kind of critical turn
and I think as a community actually we can be
proud of quite a lot the work we now do in this area.
And it allows us to examine
quite sensitive areas as well.
On the memory side I've done a lot
in the field of memory studies,
which is a interdisciplinary field,
but adopted broadly
socio-cultural and phenomenological view of memory.
For me there was a very important focus
on the experience of remembering.
Remembering as a verb, as an action,
as a process, rather than simply
memories as an archive or as a pure recall.
I was interested in what it means to remember,
not simply that we can remember.
In this sense the work of Frederick Bartlett
is very important in sort of establishing
remembering as an imaginative reconstruction.
It's not simply the re-excitation
of innumerable fixed, lifeless and fragmentary traces.
It's something very imaginative
and reconstructive and human.
And similarly, in a more contemporary work,
Middleton and Brown really set out the case for this,
for memory as a present focused action.
And so this is kind of echoed in
a lot of previous HCI work as well,
in our very orientation to digital records
and digital possessions and the idea that
if we takes things as a resource for action,
then we might design lots of memory
and digital possessions very differently,
rather than thinking of them purely as
resources of record or recall.
This quote really sums up I guess why I find my thesis
so interesting and why it was
a really rich space to work in.
It was from one participant.
It said: "I obviously don't take the data as a,
you know, 'this is what happened.'
But at the same time, your memory doesn't always
remember things in the correct way either."
And I think ultimately my thesis worked
because of the interesting overlap between
and tension between data and remembering.
And while a data-driven life as it's presented
to us in most applications is one of quite
radical individual self-optimization and
rationalism, remembering is a far more
constructive and human activity.
It requires us to do very different things
with data than we might be accustomed to
with self-tracking apps, particularly
in the fitness and wellness kind of areas.
Of course, they're both intensely related
to personal identity.
I'm just gonna give a really high level summary
of the studies I undertook in the thesis
and these papers, which go into much more detail.
But I began trying to just find examples of
a quantified past in the wild.
Something that was quite important is that
this is like a very emerging phenomenon,
and in many ways still is an emerging
and anticipated phenomenon.
I had two main pieces of fieldwork,
and both of them were interview based studies.
The first one was with long-term self-trackers.
I spoke to people self-tracking a range of things
using a range of technologies.
And some of them has records going back six or seven years.
I got them to talk through their self-tracking
practice, and when ever at all they look back
at these things.
Walking through the data with them during the interview.
And so that was really telling that for some people
this was the first time they looked back at that data,
or even realized it had anything meaningful to say
about them in a retrospective way.
I also did a study with our own diary keeping
and what we called smart journals,
a sort of range of apps that allow you
to capture and document different media
about your life.
And this really helped to see how people were
interweaving a variety of media,
including some quantified data,
to try and document their lives.
And also understanding the really distinct
and different reasons and approaches
people had to documenting their lives.
People keep diaries for really really different reasons.
And that really kind of helped to understand
the qualities of different media in helping people
achieve their goals in that regard.
As I said I point to the papers for most of
the kind of findings and the data,
but we got things like this as well.
So this is like a year's worth of night pulse data.
And many of these things have ignored,
people haven't looked at them before,
and I was quite a bit surprised about how telling
they could be.
But some of it was quite treasured by people as well.
We also saw some, in sort of the diaries,
examples of people recording prices
and using quantitative data already
to write things down and record them about themselves,
in numerous smart journal apps like this,
So in the thesis we start to try and
distinguish and summarize some characteristics
for quantified past, like what makes this
different from other kinds of media.
Why is this different from remembering with photographs,
with a diary or something else?
This is sort of six qualities that we sort of
distinguished in starting to think towards
how do we start to design with this in mind.
Some of those are experiential,
so quantified past is generally passive
and third party.
So it's generally something that's going on
in the background.
It's not as kind of active as you taking a photograph.
It's ego-centric.
It's generally taken as a selfie.
Most of the data we collect,
at least in this guise is about yourself.
And it's been moved from the past as remembered,
it's quite distinct.
It's got qualities that are quite different
from the way we tend to remember,
see in a visual sense as well.
Materialistically, it's obviously quantitative
and very much presented in an objective
and kind of very precise way.
By determinatively saying you did 9,872 steps
there's no question that that might be wrong
or that be something else in between
or might be something more to it than that.
Our experiences are abstracted,
it's reductive, it's commensurated.
That's the value of data that we can compare
different sets of steps,
even if 10,000 of them were around this amphitheater
and 10,000 of them were on your commute,
in terms of the data that can very often
be commensurated into the same.
And of course it's amorphous in the sense that
this data could be represented
in many different fashions,
and I'd argue that we're really very limited in
the way that it's currently represented to us.
I just want to highlight one thing around
that was quite interesting about the field work
and that continues to really interest me,
is that a key feature of this field work
was about getting people to talk
their own way through their own data.
And we became attentive to the sort of the rhetoric
and the talk that was required to make sense of data.
And the data certainly doesn't speak for itself
as much as we're promised about how much insight
and rich meaning it's going to bring to us.
And the term data work has been used previously
and a few times since in slightly different ways,
but broadly acknowledges that
data doesn't work on its own.
And so a lot of the data we have is much of these words,
apparently this,
and I don't really believe it,
or it doesn't feel like very much,
or I don't know,
maybe people negotiating or trying to understand
or trying to in this case achieve some sense of
verisimilitude between what the data says
and their own remembering,
going back to that quote from the participant earlier.
Following this field work, as I said before
there's a kind of anticipatory
and sort of emerging phenomenon.
And that's quite a challenge to study things
that are just in that near future.
And so I turned to speculative methods,
but I wanted to more than just provoke or critique.
I really was intrigued by how can we do more
kind of empirical studies
with such emerging and anticipated phenomena.
And so through the thesis and collaborating
with a lot of colleagues, developed an approach
called speculative enactments.
And this first came to life in a project called
meta-dating, where we used
a live speed dating event to get people to explore how
they would talk about themselves
and represent themselves with data
in a sort of very live, romantic context.
And so in thesis, I looked at it
in the context of contemporary weddings,
and viewed weddings as a really rich sort of
documentary context through which
I could start to speculate about
how people might record their lives with data.
So I developed a speculative serv,
it's called Abacus,
to document one's wedding with data.
This entailed a kind of research through design
approach to this service.
And a number of other sort of interviews
and things, and then ultimately meeting with
two engaged couples, and sort of
posing or engaging with them
as a 'data-grapher', like a photographer for data.
And to get them to think about and choose ways
in which they might try to document
their wedding with data.
What would they try to capture,
and what qualities would data bring to that
that might be different or distinct
from other media?
And finally this produced a sort of promotional brochure
about the service which they were a part.
So it created some consequence to their involvement
in this speculation with me.
There's a series of documentary data artifacts
that we then designed.
And they explore the kind of semiotics
of remembering with data,
the importance of curation,
the way that data can act as an alternative lens,
and particularly playing around with
the sense that a wedding,
you know there's a sort of magic to this big day,
and there's a lot of,
how do we get data to reflect that,
and perhaps in a poetic fashion?
And the sort of final concept we come up with
in terms of a design approach concerns
what we call documentary informatics.
And really this is about the fact that
data becomes meaningful when people
are able to make it accountable to their experience.
So, it's really clear that the purpose of
documenting a wedding is not to obtain
a complete and unerring record of the date.
But it's valuable when it's a resource
for you to do a particular kind of
remembering with particular social ends.
You need a photograph to put in your hall,
you need something to put on your invites,
you need something to give to your parents,
you need something to reminisce with your partner,
these are the kinds of things
that remembering is valuable for.
And so what we argue is that we need
to support people doing this very subjective
and contextual sense-making of their data,
rather than designing data as some sort of
objective truth that might be powerful in and of itself.
And again, there's a paper talking a little bit more
about that, but what's clear is that
this is a very distinctive approach
to how we might design these tools
compared to self-tracking tools that focus on
self-optimization or health and wellness.
I'm just gonna finish up, I guess,
with the pleasure of hindsight.
I think a couple of things that
I think are still interesting, and things
that I think I have reflected on since
if I was to do the thesis again now.
The first is that my work was ultimately
quite focused on individuals or at least couples,
and very much that kind of individual experience
of remembering, and my methods were all
tailored around that.
But I think there's some really interesting
space around the sort of quantified past
and the more social history and what kinds of
social and collective remembering might
be afforded by the quantified records
that we were inevitably creating and collecting now.
We could argue, question what kinds of history
are being written in an increasingly data-driven society.
And how are those different from the other kinds
of archives that we might have collected before.
And then finally, and perhaps most critically,
like many of us I'm becoming more aware and concerned
around the sort of surveillance,
and obviously quantified self and surveillance
have been intimately linked for a long time,
but I think this particularly now this
seems more relevant than ever,
and I sort of recognize that if we were to sort of
be hugely successful and loads of companies went
"Hey, we need to make some documentary informatics."
and followed all of our wonderful design considerations,
the data they produced wouldn't be locked
in a bedside cabinet,
it wouldn't be in a photo album in the attic.
Instead, simultaneously, whatever experiences
they gave the users that they would value
and we think would be interesting,
and they'd also support new opportunities to
capitalize upon those experiences.
So I think that sort of illustrates the way
in which we're aware more and more that
our work has consequences beyond
the immediate interaction interface,
and I think that's why CHI can be a very good venue
for these types of discussions that
cross a whole range of fields.
And that's part of the reason that I'm sort of, again,
so thankful and honored to get this award.
So, thank you very very much.
(applause)
- [Moderator] So we have time for a
couple of questions?
Yes?
- [Audience Member] Um, hi Chris.
I'm kind of continuing
your thesis in my own work, it's very
kind of impressive and inspiring
looking at how kids are,
teenagers are pulling a sense of their own identity
through these self-tracking data representations.
And one way in which I'm seeing it is that
self-tracking tools are a kind of
way to play for adults and the thing which
I like about them, both in a meta-dating situation
and the wedding situation is, it's sort of
we're in on the fact that it's all kind of
playing around and it's not really
gonna have this kind of meaning and
though that, just through the process
where you get to a sense of meaning,
I wondered to what extent your participants
took it seriously.
Because I hear a lot of Quantified Self
is saying, "No, it has to be accurate.
We need to know accuracy,
whether your participants shared the spirit of,
this is a kind of creative, playful process,
or they were more towards "Let's have accuracy
on knowing how many..."
- Yeah, there's...
- What was your name?
- [Audience Member] Keiron.
- There's two quick points on that
that are quite interesting.
One is in terms of the methods
that we were playing with that,
of trying to make it an enjoyable and playful experience,
but also one that was consequential for them,
so when people are engaging in speculation,
part of the speculative enactment's work was
like, if you can make their engagement
more consequential in some way,
like I've got to be impressive to this person
on a date, or I've got to not embarrass myself
in the next five minutes,
you get more interesting and richer data
than when people are just mucking around.
So that's one balance that's always a challenge.
I would argue that I guess the perspective
that came through was that the meaning or the value
of that data was not necessarily only related
to the quality of the data itself.
Like obviously the data shouldn't be junk,
but actually, particularly in the wedding context,
what became valuable was like,
if the couple had done a lot of equatorial work
around that data or picked certain kinds of data out.
Now, in a data science way that's a very selective,
unscientific thing to do to just choose
some parts and ignore others,
but that could become very meaningful
to someone to say:
"Did you know her heart-rate
was this at this point in the day?".
So I think actually with that,
the meanings coming from the investment
that they're able to make in it.
And I'd say that a lot of tools at the moment
don't really let us do that very much,
like we just get it and we just have to look at it,
consume it, and then feel better or worse
about ourselves about it.