How we can find ourselves in data | Giorgia Lupi

This is what my last week looked like.

What I did,

who I was with,

the main sensations I had for every waking hour ...

If the feeling came as I thought of my dad

who recently passed away,

or if I could have just definitely avoided the worries and anxieties.

And if you think I'm a little obsessive,

you're probably right.

But clearly, from this visualization,

you can learn much more about me than from this other one,

which are images you're probably more familiar with

and which you possibly even have on your phone right now.

Bar charts for the steps you walked,

pie charts for the quality of your sleep --

the path of your morning runs.

In my day job, I work with data.

I run a data visualization design company,

and we design and develop ways to make information accessible

through visual representations.

What my job has taught me over the years

is that to really understand data and their true potential,

sometimes we actually have to forget about them

and see through them instead.

Because data are always just a tool we use to represent reality.

They're always used as a placeholder for something else,

but they are never the real thing.

But let me step back for a moment

to when I first understood this personally.

In 1994, I was 13 years old.

I was a teenager in Italy.

I was too young to be interested in politics,

but I knew that a businessman, Silvio Berlusconi,

was running for president for the moderate right.

We lived in a very liberal town,

and my father was a politician for the Democratic Party.

And I remember that no one thought that Berlusconi could get elected --

that was totally not an option.

But it happened.

And I remember the feeling very vividly.

It was a complete surprise,

as my dad promised that in my town he knew nobody who voted for him.

This was the first time

when the data I had gave me a completely distorted image of reality.

My data sample was actually pretty limited and skewed,

so probably it was because of that, I thought, I lived in a bubble,

and I didn't have enough chances to see outside of it.

Now, fast-forward to November 8, 2016

in the United States.

The internet polls,

statistical models,

all the pundits agreeing on a possible outcome for the presidential election.

It looked like we had enough information this time,

and many more chances to see outside the closed circle we lived in --

but we clearly didn't.

The feeling felt very familiar.

I had been there before.

I think it's fair to say the data failed us this time --

and pretty spectacularly.

We believed in data,

but what happened,

even with the most respected newspaper,

is that the obsession to reduce everything to two simple percentage numbers

to make a powerful headline

made us focus on these two digits

and them alone.

In an effort to simplify the message

and draw a beautiful, inevitable red and blue map,

we lost the point completely.

We somehow forgot that there were stories --

stories of human beings behind these numbers.

In a different context,

but to a very similar point,

a peculiar challenge was presented to my team by this woman.

She came to us with a lot of data,

but ultimately she wanted to tell one of the most humane stories possible.

She's Samantha Cristoforetti.

She has been the first Italian woman astronaut,

and she contacted us before being launched

on a six-month-long expedition to the International Space Station.

She told us, "I'm going to space,

and I want to do something meaningful with the data of my mission

to reach out to people."

A mission to the International Space Station

comes with terabytes of data

about anything you can possibly imagine --

the orbits around Earth,

the speed and position of the ISS

and all of the other thousands of live streams from its sensors.

We had all of the hard data we could think of --

just like the pundits before the election --

but what is the point of all these numbers?

People are not interested in data for the sake of it,

because numbers are never the point.

They're always the means to an end.

The story we needed to tell

is that there is a human being in a teeny box

flying in space above your head,

and that you can actually see her with your naked eye on a clear night.

So we decided to use data to create a connection

between Samantha and all of the people looking at her from below.

We designed and developed what we called "Friends in Space,"

a web application that simply lets you say "hello" to Samantha

from where you are,

and "hello" to all the people who are online at the same time

from all over the world.

And all of these "hellos" left visible marks on the map

as Samantha was flying by

and as she was actually waving back every day at us

using Twitter from the ISS.

This made people see the mission's data from a very different perspective.

It all suddenly became much more about our human nature and our curiosity,

rather than technology.

So data powered the experience,

but stories of human beings were the drive.

The very positive response of its thousands of users

taught me a very important lesson --

that working with data means designing ways

to transform the abstract and the uncountable

into something that can be seen, felt and directly reconnected

to our lives and to our behaviors,

something that is hard to achieve

if we let the obsession for the numbers and the technology around them

lead us in the process.

But we can do even more to connect data to the stories they represent.

We can remove technology completely.

A few years ago, I met this other woman,

Stefanie Posavec --

a London-based designer who shares with me the passion and obsession about data.

We didn't know each other,

but we decided to run a very radical experiment,

starting a communication using only data,

no other language,

and we opted for using no technology whatsoever to share our data.

In fact, our only means of communication

would be through the old-fashioned post office.

For "Dear Data," every week for one year,

we used our personal data to get to know each other --

personal data around weekly shared mundane topics,

from our feelings

to the interactions with our partners,

from the compliments we received to the sounds of our surroundings.

Personal information that we would then manually hand draw

on a postcard-size sheet of paper

that we would every week send from London to New York,

where I live,

and from New York to London, where she lives.

The front of the postcard is the data drawing,

and the back of the card

contains the address of the other person, of course,

and the legend for how to interpret our drawing.

The very first week into the project,

we actually chose a pretty cold and impersonal topic.

How many times do we check the time in a week?

So here is the front of my card,

and you can see that every little symbol

represents all of the times that I checked the time,

positioned for days and different hours chronologically --

nothing really complicated here.

But then you see in the legend

how I added anecdotal details about these moments.

In fact, the different types of symbols indicate why I was checking the time --

what was I doing?

Was I bored? Was I hungry?

Was I late?

Did I check it on purpose or just casually glance at the clock?

And this is the key part --

representing the details of my days and my personality

through my data collection.

Using data as a lens or a filter to discover and reveal, for example,

my never-ending anxiety for being late,

even though I'm absolutely always on time.

Stefanie and I spent one year collecting our data manually

to force us to focus on the nuances that computers cannot gather --

or at least not yet --

using data also to explore our minds and the words we use,

and not only our activities.

Like at week number three,

where we tracked the "thank yous" we said and were received,

and when I realized that I thank mostly people that I don't know.

Apparently I'm a compulsive thanker to waitresses and waiters,

but I definitely don't thank enough the people who are close to me.

Over one year,

the process of actively noticing and counting these types of actions

became a ritual.

It actually changed ourselves.

We became much more in tune with ourselves,

much more aware of our behaviors and our surroundings.

Over one year, Stefanie and I connected at a very deep level

through our shared data diary,

but we could do this only because we put ourselves in these numbers,

adding the contexts of our very personal stories to them.

It was the only way to make them truly meaningful

and representative of ourselves.

I am not asking you to start drawing your personal data,

or to find a pen pal across the ocean.

But I'm asking you to consider data --

all kind of data --

as the beginning of the conversation

and not the end.

Because data alone will never give us a solution.

And this is why data failed us so badly --

because we failed to include the right amount of context

to represent reality --

a nuanced, complicated and intricate reality.

We kept looking at these two numbers,

obsessing with them

and pretending that our world could be reduced

to a couple digits and a horse race,

while the real stories,

the ones that really mattered,

were somewhere else.

What we missed looking at these stories only through models and algorithms

is what I call "data humanism."

In the Renaissance humanism,

European intellectuals

placed the human nature instead of God at the center of their view of the world.

I believe something similar needs to happen

with the universe of data.

Now data are apparently treated like a God --

keeper of infallible truth for our present and our future.

The experiences that I shared with you today

taught me that to make data faithfully representative of our human nature

and to make sure they will not mislead us anymore,

we need to start designing ways to include empathy, imperfection

and human qualities

in how we collect, process, analyze and display them.

I do see a place where, ultimately,

instead of using data only to become more efficient,

we will all use data to become more humane.

Thank you.

(Applause)