0:00:01.015,0:00:04.008 This story starts with these two -- 0:00:04.032,0:00:05.290 my kids. 0:00:05.314,0:00:06.996 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. 0:00:11.647,0:00:13.309 She looked at me and said, 0:00:13.333,0:00:15.840 "Daddy? 0:00:15.864,0:00:17.514 That doesn't go there." 0:00:17.538,0:00:19.960 When she said that,[br]it reminded me of summer camp. 0:00:19.984,0:00:21.482 On the morning of visiting day, 0:00:21.506,0:00:25.169 right before they'd let our anxious[br]parents come barreling through the gates, 0:00:25.193,0:00:26.562 our camp director would say, 0:00:26.586,0:00:28.895 "Quick! Everyone pick up[br]five pieces of litter." 0:00:28.919,0:00:31.959 You get a couple hundred kids[br]each picking up five pieces, 0:00:31.983,0:00:34.556 and pretty soon, you've got[br]a much cleaner camp. 0:00:34.580,0:00:35.739 So I thought, 0:00:35.763,0:00:40.300 why not apply that crowdsourced[br]cleanup model to the entire planet? 0:00:40.324,0:00:43.275 And that was the inspiration[br]for Litterati. 0:00:43.299,0:00:46.648 The vision is to create[br]a litter-free world. 0:00:46.672,0:00:48.180 Let me show you how it started. 0:00:48.204,0:00:51.590 I took a picture of a cigarette[br]using Instagram. 0:00:52.222,0:00:54.089 Then I took another photo ... 0:00:54.113,0:00:55.670 and another photo ... 0:00:55.694,0:00:56.861 and another photo. 0:00:56.885,0:00:58.171 And I noticed two things: 0:00:58.195,0:01:01.667 one, litter became artistic[br]and approachable; 0:01:02.244,0:01:03.395 and two, 0:01:03.419,0:01:05.934 at the end of a few days,[br]I had 50 photos on my phone 0:01:05.958,0:01:07.545 and I had picked up each piece, 0:01:07.569,0:01:09.954 and I realized that I was keeping a record 0:01:09.978,0:01:13.129 of the positive impact[br]I was having on the planet. 0:01:13.153,0:01:15.341 That's 50 less things that you might see, 0:01:15.365,0:01:16.608 or you might step on, 0:01:16.632,0:01:18.090 or some bird might eat. 0:01:18.769,0:01:21.421 So I started telling people[br]what I was doing, 0:01:21.445,0:01:23.801 and they started participating. 0:01:24.831,0:01:26.524 One day, 0:01:26.548,0:01:29.076 this photo showed up from China. 0:01:30.039,0:01:31.310 And that's when I realized 0:01:31.334,0:01:34.600 that Litterati was more[br]than just pretty pictures; 0:01:34.624,0:01:37.993 we were becoming a community[br]that was collecting data. 0:01:38.869,0:01:40.759 Each photo tells a story. 0:01:41.279,0:01:43.472 It tells us who picked up what, 0:01:43.496,0:01:45.507 a geotag tells us where 0:01:45.531,0:01:47.561 and a time stamp tells us when. 0:01:48.006,0:01:50.435 So I built a Google map, 0:01:50.459,0:01:54.512 and started plotting the points[br]where pieces were being picked up. 0:01:54.536,0:01:58.454 And through that process,[br]the community grew 0:01:58.478,0:02:00.117 and the data grew. 0:02:00.806,0:02:04.267 My two kids go to school[br]right in that bullseye. 0:02:05.125,0:02:06.336 Litter: 0:02:06.360,0:02:09.064 it's blending into[br]the background of our lives. 0:02:09.088,0:02:11.187 But what if we brought it[br]to the forefront? 0:02:11.211,0:02:14.123 What if we understood exactly[br]what was on our streets, 0:02:14.147,0:02:15.536 our sidewalks 0:02:15.560,0:02:17.098 and our school yards? 0:02:17.122,0:02:20.369 How might we use that data[br]to make a difference? 0:02:21.189,0:02:22.387 Well, let me show you. 0:02:22.411,0:02:23.796 The first is with cities. 0:02:24.418,0:02:29.057 San Francisco wanted to understand[br]what percentage of litter was cigarettes. 0:02:29.081,0:02:30.243 Why? 0:02:30.267,0:02:31.476 To create a tax. 0:02:32.073,0:02:34.208 So they put a couple of people[br]in the streets 0:02:34.232,0:02:35.593 with pencils and clipboards, 0:02:35.617,0:02:37.680 who walked around collecting information 0:02:37.704,0:02:40.815 which led to a 20-cent tax[br]on all cigarette sales. 0:02:41.787,0:02:43.940 And then they got sued 0:02:43.964,0:02:45.140 by big tobacco, 0:02:45.164,0:02:48.380 who claimed that collecting information[br]with pencils and clipboards 0:02:48.404,0:02:50.735 is neither precise nor provable. 0:02:51.454,0:02:55.134 The city called me and asked[br]if our technology could help. 0:02:55.158,0:02:56.407 I'm not sure they realized 0:02:56.431,0:02:58.679 that our technology[br]was my Instagram account -- 0:02:58.703,0:02:59.742 (Laughter) 0:02:59.766,0:03:01.032 But I said, "Yes, we can." 0:03:01.056,0:03:02.072 (Laughter) 0:03:02.096,0:03:06.004 "And we can tell you[br]if that's a Parliament or a Pall Mall. 0:03:06.028,0:03:09.453 Plus, every photograph[br]is geotagged and time-stamped, 0:03:09.477,0:03:10.858 providing you with proof." 0:03:11.839,0:03:15.059 Four days and 5,000 pieces later, 0:03:15.083,0:03:20.021 our data was used in court[br]to not only defend but double the tax, 0:03:20.045,0:03:24.368 generating an annual recurring revenue[br]of four million dollars 0:03:24.392,0:03:26.687 for San Francisco to clean itself up. 0:03:28.001,0:03:30.236 Now, during that process[br]I learned two things: 0:03:30.260,0:03:32.814 one, Instagram is not the right tool -- 0:03:32.838,0:03:33.869 (Laughter) 0:03:33.893,0:03:35.396 so we built an app. 0:03:35.420,0:03:37.053 And two, if you think about it, 0:03:37.077,0:03:40.694 every city in the world[br]has a unique litter fingerprint, 0:03:40.718,0:03:44.554 and that fingerprint provides[br]both the source of the problem 0:03:44.578,0:03:46.499 and the path to the solution. 0:03:47.646,0:03:50.024 If you could generate a revenue stream 0:03:50.048,0:03:52.511 just by understanding[br]the percentage of cigarettes, 0:03:52.535,0:03:54.631 well, what about coffee cups 0:03:54.655,0:03:56.361 or soda cans 0:03:56.385,0:03:57.799 or plastic bottles? 0:03:58.501,0:04:01.702 If you could fingerprint San Francisco,[br]well, how about Oakland 0:04:01.726,0:04:03.422 or Amsterdam 0:04:03.446,0:04:06.416 or somewhere much closer to home? 0:04:07.408,0:04:08.642 And what about brands? 0:04:08.666,0:04:10.567 How might they use this data 0:04:10.591,0:04:14.803 to align their environmental[br]and economic interests? 0:04:15.646,0:04:18.858 There's a block in downtown Oakland[br]that's covered in blight. 0:04:19.325,0:04:23.429 The Litterati community got together[br]and picked up 1,500 pieces. 0:04:23.812,0:04:25.152 And here's what we learned: 0:04:25.176,0:04:28.386 most of that litter came[br]from a very well-known taco brand. 0:04:29.738,0:04:33.315 Most of that brand's litter[br]were their own hot sauce packets, 0:04:34.438,0:04:38.064 and most of those hot sauce packets[br]hadn't even been opened. 0:04:39.965,0:04:42.680 The problem and the path[br]to the solution -- 0:04:42.704,0:04:46.665 well, maybe that brand only[br]gives out hot sauce upon request 0:04:46.689,0:04:48.698 or installs bulk dispensers 0:04:48.722,0:04:51.274 or comes up with more[br]sustainable packaging. 0:04:51.298,0:04:54.267 How does a brand take[br]an environmental hazard, 0:04:54.291,0:04:56.297 turn it into an economic engine 0:04:56.321,0:04:58.089 and become an industry hero? 0:04:59.292,0:05:01.494 If you really want to create change, 0:05:01.518,0:05:04.392 there's no better place to start[br]than with our kids. 0:05:04.416,0:05:07.819 A group of fifth graders picked up[br]1,247 pieces of litter 0:05:07.843,0:05:09.691 just on their school yard. 0:05:09.715,0:05:12.247 And they learned that the most[br]common type of litter 0:05:12.271,0:05:15.505 were the plastic straw wrappers[br]from their own cafeteria. 0:05:15.947,0:05:18.476 So these kids went[br]to their principal and asked, 0:05:18.500,0:05:20.160 "Why are we still buying straws?" 0:05:21.166,0:05:22.921 And they stopped. 0:05:22.945,0:05:26.599 And they learned that individually[br]they could each make a difference, 0:05:26.623,0:05:28.961 but together they created an impact. 0:05:29.503,0:05:33.515 It doesn't matter[br]if you're a student or a scientist, 0:05:33.539,0:05:36.674 whether you live in Honolulu or Hanoi, 0:05:36.698,0:05:39.139 this is a community for everyone. 0:05:39.974,0:05:44.653 It started because of two little kids[br]in the Northern California woods, 0:05:44.677,0:05:47.491 and today it's spread across the world. 0:05:47.938,0:05:49.721 And you know how we're getting there? 0:05:50.067,0:05:51.945 One piece at a time. 0:05:52.508,0:05:53.723 Thank you. 0:05:53.747,0:05:57.365 (Applause)