1 00:00:01,015 --> 00:00:04,008 This story starts with these two -- 2 00:00:04,032 --> 00:00:05,290 my kids. 3 00:00:05,314 --> 00:00:06,996 We were hiking in the Oakland woods 4 00:00:07,020 --> 00:00:11,154 when my daughter noticed a plastic tub of cat litter in a creek. 5 00:00:11,647 --> 00:00:13,309 She looked at me and said, 6 00:00:13,333 --> 00:00:15,840 "Daddy? 7 00:00:15,864 --> 00:00:17,514 That doesn't go there." 8 00:00:17,538 --> 00:00:19,960 When she said that, it reminded me of summer camp. 9 00:00:19,984 --> 00:00:21,482 On the morning of visiting day, 10 00:00:21,506 --> 00:00:25,169 right before they'd let our anxious parents come barreling through the gates, 11 00:00:25,193 --> 00:00:26,562 our camp director would say, 12 00:00:26,586 --> 00:00:28,895 "Quick! Everyone pick up five pieces of litter." 13 00:00:28,919 --> 00:00:31,959 You get a couple hundred kids each picking up five pieces, 14 00:00:31,983 --> 00:00:34,556 and pretty soon, you've got a much cleaner camp. 15 00:00:34,580 --> 00:00:35,739 So I thought, 16 00:00:35,763 --> 00:00:40,300 why not apply that crowdsourced cleanup model to the entire planet? 17 00:00:40,324 --> 00:00:43,275 And that was the inspiration for Litterati. 18 00:00:43,299 --> 00:00:46,648 The vision is to create a litter-free world. 19 00:00:46,672 --> 00:00:48,180 Let me show you how it started. 20 00:00:48,204 --> 00:00:51,590 I took a picture of a cigarette using Instagram. 21 00:00:52,222 --> 00:00:54,089 Then I took another photo ... 22 00:00:54,113 --> 00:00:55,670 and another photo ... 23 00:00:55,694 --> 00:00:56,861 and another photo. 24 00:00:56,885 --> 00:00:58,171 And I noticed two things: 25 00:00:58,195 --> 00:01:01,667 one, litter became artistic and approachable; 26 00:01:02,244 --> 00:01:03,395 and two, 27 00:01:03,419 --> 00:01:05,934 at the end of a few days, I had 50 photos on my phone 28 00:01:05,958 --> 00:01:07,545 and I had picked up each piece, 29 00:01:07,569 --> 00:01:09,954 and I realized that I was keeping a record 30 00:01:09,978 --> 00:01:13,129 of the positive impact I was having on the planet. 31 00:01:13,153 --> 00:01:15,341 That's 50 less things that you might see, 32 00:01:15,365 --> 00:01:16,608 or you might step on, 33 00:01:16,632 --> 00:01:18,090 or some bird might eat. 34 00:01:18,769 --> 00:01:21,421 So I started telling people what I was doing, 35 00:01:21,445 --> 00:01:23,801 and they started participating. 36 00:01:24,831 --> 00:01:26,524 One day, 37 00:01:26,548 --> 00:01:29,076 this photo showed up from China. 38 00:01:30,039 --> 00:01:31,310 And that's when I realized 39 00:01:31,334 --> 00:01:34,600 that Litterati was more than just pretty pictures; 40 00:01:34,624 --> 00:01:37,993 we were becoming a community that was collecting data. 41 00:01:38,869 --> 00:01:40,759 Each photo tells a story. 42 00:01:41,279 --> 00:01:43,472 It tells us who picked up what, 43 00:01:43,496 --> 00:01:45,507 a geotag tells us where 44 00:01:45,531 --> 00:01:47,561 and a time stamp tells us when. 45 00:01:48,006 --> 00:01:50,435 So I built a Google map, 46 00:01:50,459 --> 00:01:54,512 and started plotting the points where pieces were being picked up. 47 00:01:54,536 --> 00:01:58,454 And through that process, the community grew 48 00:01:58,478 --> 00:02:00,117 and the data grew. 49 00:02:00,806 --> 00:02:04,267 My two kids go to school right in that bullseye. 50 00:02:05,125 --> 00:02:06,336 Litter: 51 00:02:06,360 --> 00:02:09,064 it's blending into the background of our lives. 52 00:02:09,088 --> 00:02:11,187 But what if we brought it to the forefront? 53 00:02:11,211 --> 00:02:14,123 What if we understood exactly what was on our streets, 54 00:02:14,147 --> 00:02:15,536 our sidewalks 55 00:02:15,560 --> 00:02:17,098 and our school yards? 56 00:02:17,122 --> 00:02:20,369 How might we use that data to make a difference? 57 00:02:21,189 --> 00:02:22,387 Well, let me show you. 58 00:02:22,411 --> 00:02:23,796 The first is with cities. 59 00:02:24,418 --> 00:02:29,057 San Francisco wanted to understand what percentage of litter was cigarettes. 60 00:02:29,081 --> 00:02:30,243 Why? 61 00:02:30,267 --> 00:02:31,476 To create a tax. 62 00:02:32,073 --> 00:02:34,208 So they put a couple of people in the streets 63 00:02:34,232 --> 00:02:35,593 with pencils and clipboards, 64 00:02:35,617 --> 00:02:37,680 who walked around collecting information 65 00:02:37,704 --> 00:02:40,815 which led to a 20-cent tax on all cigarette sales. 66 00:02:41,787 --> 00:02:43,940 And then they got sued 67 00:02:43,964 --> 00:02:45,140 by big tobacco, 68 00:02:45,164 --> 00:02:48,380 who claimed that collecting information with pencils and clipboards 69 00:02:48,404 --> 00:02:50,735 is neither precise nor provable. 70 00:02:51,454 --> 00:02:55,134 The city called me and asked if our technology could help. 71 00:02:55,158 --> 00:02:56,407 I'm not sure they realized 72 00:02:56,431 --> 00:02:58,679 that our technology was my Instagram account -- 73 00:02:58,703 --> 00:02:59,742 (Laughter) 74 00:02:59,766 --> 00:03:01,032 But I said, "Yes, we can." 75 00:03:01,056 --> 00:03:02,072 (Laughter) 76 00:03:02,096 --> 00:03:06,004 "And we can tell you if that's a Parliament or a Pall Mall. 77 00:03:06,028 --> 00:03:09,453 Plus, every photograph is geotagged and time-stamped, 78 00:03:09,477 --> 00:03:10,858 providing you with proof." 79 00:03:11,839 --> 00:03:15,059 Four days and 5,000 pieces later, 80 00:03:15,083 --> 00:03:20,021 our data was used in court to not only defend but double the tax, 81 00:03:20,045 --> 00:03:24,368 generating an annual recurring revenue of four million dollars 82 00:03:24,392 --> 00:03:26,687 for San Francisco to clean itself up. 83 00:03:28,001 --> 00:03:30,236 Now, during that process I learned two things: 84 00:03:30,260 --> 00:03:32,814 one, Instagram is not the right tool -- 85 00:03:32,838 --> 00:03:33,869 (Laughter) 86 00:03:33,893 --> 00:03:35,396 so we built an app. 87 00:03:35,420 --> 00:03:37,053 And two, if you think about it, 88 00:03:37,077 --> 00:03:40,694 every city in the world has a unique litter fingerprint, 89 00:03:40,718 --> 00:03:44,554 and that fingerprint provides both the source of the problem 90 00:03:44,578 --> 00:03:46,499 and the path to the solution. 91 00:03:47,646 --> 00:03:50,024 If you could generate a revenue stream 92 00:03:50,048 --> 00:03:52,511 just by understanding the percentage of cigarettes, 93 00:03:52,535 --> 00:03:54,631 well, what about coffee cups 94 00:03:54,655 --> 00:03:56,361 or soda cans 95 00:03:56,385 --> 00:03:57,799 or plastic bottles? 96 00:03:58,501 --> 00:04:01,702 If you could fingerprint San Francisco, well, how about Oakland 97 00:04:01,726 --> 00:04:03,422 or Amsterdam 98 00:04:03,446 --> 00:04:06,416 or somewhere much closer to home? 99 00:04:07,408 --> 00:04:08,642 And what about brands? 100 00:04:08,666 --> 00:04:10,567 How might they use this data 101 00:04:10,591 --> 00:04:14,803 to align their environmental and economic interests? 102 00:04:15,646 --> 00:04:18,858 There's a block in downtown Oakland that's covered in blight. 103 00:04:19,325 --> 00:04:23,429 The Litterati community got together and picked up 1,500 pieces. 104 00:04:23,812 --> 00:04:25,152 And here's what we learned: 105 00:04:25,176 --> 00:04:28,386 most of that litter came from a very well-known taco brand. 106 00:04:29,738 --> 00:04:33,315 Most of that brand's litter were their own hot sauce packets, 107 00:04:34,438 --> 00:04:38,064 and most of those hot sauce packets hadn't even been opened. 108 00:04:39,965 --> 00:04:42,680 The problem and the path to the solution -- 109 00:04:42,704 --> 00:04:46,665 well, maybe that brand only gives out hot sauce upon request 110 00:04:46,689 --> 00:04:48,698 or installs bulk dispensers 111 00:04:48,722 --> 00:04:51,274 or comes up with more sustainable packaging. 112 00:04:51,298 --> 00:04:54,267 How does a brand take an environmental hazard, 113 00:04:54,291 --> 00:04:56,297 turn it into an economic engine 114 00:04:56,321 --> 00:04:58,089 and become an industry hero? 115 00:04:59,292 --> 00:05:01,494 If you really want to create change, 116 00:05:01,518 --> 00:05:04,392 there's no better place to start than with our kids. 117 00:05:04,416 --> 00:05:07,819 A group of fifth graders picked up 1,247 pieces of litter 118 00:05:07,843 --> 00:05:09,691 just on their school yard. 119 00:05:09,715 --> 00:05:12,247 And they learned that the most common type of litter 120 00:05:12,271 --> 00:05:15,505 were the plastic straw wrappers from their own cafeteria. 121 00:05:15,947 --> 00:05:18,476 So these kids went to their principal and asked, 122 00:05:18,500 --> 00:05:20,160 "Why are we still buying straws?" 123 00:05:21,166 --> 00:05:22,921 And they stopped. 124 00:05:22,945 --> 00:05:26,599 And they learned that individually they could each make a difference, 125 00:05:26,623 --> 00:05:28,961 but together they created an impact. 126 00:05:29,503 --> 00:05:33,515 It doesn't matter if you're a student or a scientist, 127 00:05:33,539 --> 00:05:36,674 whether you live in Honolulu or Hanoi, 128 00:05:36,698 --> 00:05:39,139 this is a community for everyone. 129 00:05:39,974 --> 00:05:44,653 It started because of two little kids in the Northern California woods, 130 00:05:44,677 --> 00:05:47,491 and today it's spread across the world. 131 00:05:47,938 --> 00:05:49,721 And you know how we're getting there? 132 00:05:50,067 --> 00:05:51,945 One piece at a time. 133 00:05:52,508 --> 00:05:53,723 Thank you. 134 00:05:53,747 --> 00:05:57,365 (Applause)