0:00:01.015,0:00:04.097
This story starts with these two --

0:00:04.097,0:00:05.123
my kids.

0:00:05.314,0:00:07.020
We were hiking in the Oakland woods

0:00:07.020,0:00:11.154
when my daughter noticed[br]a plastic tub of cat litter in a creek.

0:00:11.647,0:00:13.333
She looked at me and said,

0:00:13.333,0:00:15.976
"Daddy ...

0:00:15.976,0:00:17.538
that doesn't go there."

0:00:17.538,0:00:18.538
When she said that,

0:00:18.538,0:00:20.024
it reminded me of summer camp.

0:00:20.024,0:00:21.505
On the morning of visiting day,

0:00:21.505,0:00:25.117
right before they'd let our anxious[br]parents come barreling through the gates,

0:00:25.117,0:00:26.471
our camp director would say,

0:00:26.471,0:00:28.858
"Quick! Everyone go pick up[br]five pieces of litter."

0:00:29.013,0:00:32.130
You get a couple hundred kids[br]each picking up five pieces,

0:00:32.130,0:00:34.738
and pretty soon you've got[br]a much cleaner camp.

0:00:34.738,0:00:35.790
So I thought,

0:00:35.790,0:00:40.143
why not apply that crowdsourced[br]cleanup model to the entire planet?

0:00:40.350,0:00:43.133
And that was the inspiration[br]for Litterati.

0:00:43.434,0:00:46.509
The vision is to create[br]a litter-free world.

0:00:46.806,0:00:48.321
Let me show you how it started.

0:00:48.321,0:00:51.707
I took a picture of a cigarette[br]using Instagram.

0:00:52.302,0:00:54.295
Then I took another photo ...

0:00:54.295,0:00:55.919
and another photo ...

0:00:55.919,0:00:56.993
and another photo ...

0:00:56.993,0:00:58.242
and I noticed two things.

0:00:58.242,0:01:02.049
One: litter became artistic[br]and approachable.

0:01:02.350,0:01:03.347
And two:

0:01:03.347,0:01:04.554
at the end of a few days,

0:01:04.554,0:01:05.860
I had 50 photos on my phone

0:01:05.860,0:01:07.569
and I had picked up each piece,

0:01:07.569,0:01:09.978
and I realized that I was keeping a record

0:01:09.978,0:01:13.217
of the positive impact[br]I was having on the planet.

0:01:13.217,0:01:15.166
That's 50 less things that you might see,

0:01:15.166,0:01:16.460
or you might step on,

0:01:16.460,0:01:18.507
or some bird might eat.

0:01:18.769,0:01:21.556
So I started telling people[br]what I was doing,

0:01:21.556,0:01:24.159
and they started participating.

0:01:24.967,0:01:26.960
One day,

0:01:26.960,0:01:30.295
this photo showed up from China,

0:01:30.295,0:01:34.928
and that's when I realized that Litterati[br]was more than just pretty pictures;

0:01:34.928,0:01:38.441
we were becoming a community[br]that was collecting data.

0:01:38.917,0:01:40.807
Each photo tells a story.

0:01:41.447,0:01:43.663
It tells us who picked up what,

0:01:43.663,0:01:45.785
a geotag tells us where

0:01:45.785,0:01:47.869
and a [time stamp] tells us when.

0:01:48.062,0:01:50.714
So I built a Google map,

0:01:50.714,0:01:54.680
and started plotting the points[br]where pieces were being picked up.

0:01:54.680,0:01:56.375
And through that process,

0:01:56.375,0:01:58.657
the community grew,

0:01:58.657,0:02:00.296
and the data grew.

0:02:00.854,0:02:04.463
My two kids go to school[br]right in that bullseye.

0:02:05.125,0:02:06.424
Litter.

0:02:06.424,0:02:08.675
It's blending into[br]the background of our lives,

0:02:08.675,0:02:11.120
but what if we brought it[br]to the forefront?

0:02:11.360,0:02:14.295
What if we understood exactly[br]what was on our streets,

0:02:14.295,0:02:15.631
our sidewalks

0:02:15.631,0:02:17.160
and our schoolyards?

0:02:17.160,0:02:20.369
How might we use that data[br]to make a difference?

0:02:21.276,0:02:22.497
Well, let me show you.

0:02:22.497,0:02:23.882
The first is with cities.

0:02:24.577,0:02:29.207
San Francisco wanted to understand[br]what percentage of litter was cigarettes.

0:02:29.207,0:02:30.361
Why?

0:02:30.361,0:02:31.786
To create a tax.

0:02:32.098,0:02:35.554
So they put a couple of people[br]in the streets with pencils and clipboards

0:02:35.554,0:02:37.919
who walked around collecting information

0:02:37.919,0:02:41.030
which led to a 20-cent tax[br]on all cigarette sales.

0:02:41.899,0:02:44.075
And then they got sued ...

0:02:44.075,0:02:45.182
by big tobacco,

0:02:45.182,0:02:48.321
who claimed that collecting information[br]with pencils and clipboards

0:02:48.321,0:02:51.166
is neither precise nor provable.

0:02:51.629,0:02:55.332
The city called me and asked[br]if our technology could help ...

0:02:55.332,0:02:59.059
not sure they realized that our[br]technology was my Instagram account --

0:02:59.059,0:03:00.059
(Laughter)

0:03:00.059,0:03:01.554
But I said, "Yes we can."

0:03:01.554,0:03:02.550
(Laughter)

0:03:02.550,0:03:06.109
And we can tell you if that's[br]a Parliament or a Pall Mall.

0:03:06.109,0:03:09.673
Plus, every photograph[br]is geotagged and [time stamped],

0:03:09.673,0:03:11.385
providing you with proof.

0:03:11.839,0:03:15.314
Four days and 5,000 pieces later,

0:03:15.314,0:03:20.275
our data was used in court to not[br]only defend but double the tax,

0:03:20.275,0:03:24.621
generating an annual recurring[br]revenue of four million dollars

0:03:24.621,0:03:26.916
for San Francisco to clean itself up.

0:03:28.014,0:03:30.168
Now, during that process[br]I learned two things.

0:03:30.168,0:03:33.039
One: Instagram is not the right tool --

0:03:33.039,0:03:34.044
(Laughter)

0:03:34.044,0:03:35.420
so we built an app.

0:03:35.420,0:03:36.422
And two:

0:03:36.422,0:03:37.487
if you think about it,

0:03:37.487,0:03:40.941
every city in the world[br]has a unique litter fingerprint,

0:03:40.941,0:03:44.800
and that fingerprint provides[br]both the source of the problem

0:03:44.800,0:03:46.987
and the path to the solution.

0:03:47.646,0:03:50.048
If you could generate a revenue stream

0:03:50.048,0:03:52.454
just by understanding[br]the percentage of cigarettes,

0:03:52.454,0:03:54.953
well, what about coffee cups ...

0:03:54.953,0:03:56.682
or soda cans ...

0:03:56.682,0:03:58.357
or plastic bottles?

0:03:58.501,0:04:00.367
If you could fingerprint San Francisco,

0:04:00.367,0:04:02.022
well, how about Oakland ...

0:04:02.022,0:04:03.542
or Amsterdam ...

0:04:03.542,0:04:07.092
or somewhere much closer to home?

0:04:07.408,0:04:08.891
And what about brands?

0:04:08.891,0:04:10.815
How might they use this data

0:04:10.815,0:04:15.027
to align their environmental[br]and economic interests?

0:04:15.734,0:04:19.043
There's a block in downtown Oakland[br]that's covered in blight.

0:04:19.421,0:04:23.525
The Litterati community got together[br]and picked up 1500 pieces.

0:04:23.939,0:04:25.353
And here's what we learned.

0:04:25.353,0:04:28.405
Most of that litter came from[br]a very well know taco brand.

0:04:29.810,0:04:34.605
Most of that brand's litter[br]were their own hot sauce packets,

0:04:34.605,0:04:39.021
and most of those hot sauce packets[br]hadn't even been opened.

0:04:40.132,0:04:42.870
The problem and the path[br]to the solution --

0:04:42.870,0:04:46.992
well, maybe that brand only[br]gives out hot sauce upon request,

0:04:46.992,0:04:49.024
or installs bulk dispensers,

0:04:49.024,0:04:51.441
or comes up with more[br]sustainable packaging.

0:04:51.441,0:04:54.433
How does a brand take[br]an environmental hazard,

0:04:54.433,0:04:56.462
turn it into an economic engine,

0:04:56.462,0:04:59.015
and become an industry hero?

0:04:59.475,0:05:01.606
If you really want to create change,

0:05:01.606,0:05:04.222
there's no better place to start[br]than with our kids.

0:05:04.558,0:05:07.907
A group of fifth graders picked up[br]1247 pieces of litter

0:05:07.907,0:05:09.778
just in their schoolyard.

0:05:09.778,0:05:12.333
And they learned that the most[br]common type of litter

0:05:12.333,0:05:15.567
were the plastic straw wrappers[br]from their own cafeteria.

0:05:16.090,0:05:18.642
So these kids went to their[br]principal and asked,

0:05:18.642,0:05:20.890
"Why are we still buying straws?"

0:05:21.286,0:05:22.824
And they stopped.

0:05:23.064,0:05:26.664
And they learned that individually[br]they could each make a difference,

0:05:26.664,0:05:29.389
but together they created an impact.

0:05:29.702,0:05:33.626
It doesn't matter if you're[br]a student or a scientist,

0:05:33.626,0:05:36.881
whether you live in Honolulu or Hanoi,

0:05:36.881,0:05:39.634
this is a community for everyone.

0:05:39.974,0:05:44.792
It started because of two little kids[br]in the Northern California woods,

0:05:44.792,0:05:47.606
and today it's spread across the world.

0:05:48.026,0:05:49.797
And you know how we're getting there?

0:05:50.179,0:05:52.211
One piece at a time.

0:05:52.556,0:05:53.794
Thank you.

0:05:53.794,0:05:55.367
(Applause)