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Would you like to inspect the original subtitles? These are the user uploaded subtitles that are being translated: 1 00:00:00,566 --> 00:00:02,769 (bright music) 2 00:00:04,770 --> 00:00:07,507 - A man checks his smartwatch. - Our modern, 3 00:00:07,540 --> 00:00:10,743 digital lives offer limitless convenience, community, 4 00:00:10,776 --> 00:00:14,080 and easy to access everything. 5 00:00:14,113 --> 00:00:16,783 - [Speaker] The internet opens unbelievable opportunities. 6 00:00:18,517 --> 00:00:21,621 - [Host] But there's a trade-off. Your personal data. 7 00:00:21,654 --> 00:00:23,256 - [Speaker] Pretty much everything you do on the web 8 00:00:23,289 --> 00:00:25,058 is being tracked and logged. 9 00:00:25,091 --> 00:00:26,826 - Who you are, what you're doing, and where you're going. 10 00:00:26,859 --> 00:00:28,394 - This is the mothership. 11 00:00:28,427 --> 00:00:31,597 Can you show me what I've inadvertently given up? 12 00:00:31,630 --> 00:00:34,834 And that personal data is worth a fortune. 13 00:00:34,867 --> 00:00:37,203 - People expect it to grow to $400 billion. 14 00:00:38,337 --> 00:00:40,440 - To completely avoid data collection 15 00:00:41,507 --> 00:00:45,078 requires you to go live in a cave. 16 00:00:45,111 --> 00:00:46,679 - [Host] Thankfully, there are tools 17 00:00:46,712 --> 00:00:50,450 to help maintain your privacy and security online. 18 00:00:50,483 --> 00:00:54,487 - Let's create some strong and unique passwords. 19 00:00:54,520 --> 00:00:56,522 - Everything has privacy settings. 20 00:00:56,555 --> 00:00:59,625 We can dial to whatever level we feel comfortable. 21 00:00:59,658 --> 00:01:03,162 - [Host] And some coders are rewriting the rules of the web. 22 00:01:03,195 --> 00:01:05,331 - The decentralized web is our antidote 23 00:01:05,364 --> 00:01:07,433 to the web as we now think of it. 24 00:01:07,466 --> 00:01:09,502 - New technologies can proliferate 25 00:01:09,535 --> 00:01:11,771 without centralized control. 26 00:01:11,804 --> 00:01:14,574 - This is about technological self-determination. 27 00:01:14,607 --> 00:01:19,345 - [Host] Secrets in your data right now on "NOVA." 28 00:01:19,378 --> 00:01:34,227 (triumphant upbeat music) 29 00:01:34,260 --> 00:01:35,328 ANNOUNCER: As an American-based supplier 30 00:01:35,361 --> 00:01:36,796 to the construction industry, 31 00:01:36,829 --> 00:01:40,066 Carlisle is committed to developing a diverse workplace 32 00:01:40,099 --> 00:01:41,434 that supports our employees' advancement 33 00:01:41,467 --> 00:01:43,436 into the next generation of leaders, 34 00:01:43,469 --> 00:01:45,671 from the manufacturing floor to the front office. 35 00:01:45,704 --> 00:01:47,574 Learn more at Carlisle.com. 36 00:01:55,214 --> 00:01:57,650 (phone camera clicking) 37 00:01:57,683 --> 00:02:00,086 PATEL: Our world runs on data. 38 00:02:00,119 --> 00:02:02,121 When you're shopping online, 39 00:02:02,154 --> 00:02:04,090 streaming your favorite shows... 40 00:02:04,123 --> 00:02:05,158 (mouse clicking) 41 00:02:05,191 --> 00:02:06,592 posting family pics-- 42 00:02:06,625 --> 00:02:08,127 that's all your personal data 43 00:02:08,160 --> 00:02:10,062 leaving your device. 44 00:02:10,095 --> 00:02:12,532 (on phone): What's up, everyone? 45 00:02:12,565 --> 00:02:13,733 I'm about to head to the hospital 46 00:02:13,766 --> 00:02:14,734 for a night shift... 47 00:02:14,767 --> 00:02:17,103 (voiceover): I'm Alok Patel, a pediatrician, 48 00:02:17,136 --> 00:02:17,970 medical journalist, 49 00:02:18,004 --> 00:02:21,207 and all-around social media enthusiast. 50 00:02:21,240 --> 00:02:22,508 (on phone): Just got here at the children's hospital... 51 00:02:22,541 --> 00:02:24,177 (voiceover): I kinda love our connected lives, 52 00:02:24,210 --> 00:02:26,078 and I haven't been shy at all 53 00:02:26,111 --> 00:02:29,282 about sharing mine pretty publicly. 54 00:02:29,315 --> 00:02:31,083 (on phone): 30 million children... 55 00:02:31,116 --> 00:02:33,152 (voiceover): And I know that sharing personal data 56 00:02:33,185 --> 00:02:34,187 can have major upsides. 57 00:02:34,220 --> 00:02:35,521 The media's reported 58 00:02:35,554 --> 00:02:37,190 on some of the most dramatic examples. 59 00:02:37,223 --> 00:02:40,526 NARRATOR (archival): ...is conducting several studies 60 00:02:40,559 --> 00:02:43,095 to see how far wearables can go in detecting disease. 61 00:02:43,128 --> 00:02:44,797 A California man, rescued yesterday 62 00:02:44,830 --> 00:02:46,832 after going missing credits a social media post 63 00:02:46,865 --> 00:02:48,367 for helping save his life. 64 00:02:48,400 --> 00:02:50,336 Six out of ten people with Alzheimer's or dementia 65 00:02:50,369 --> 00:02:51,604 will wander away from home, 66 00:02:51,637 --> 00:02:54,207 and that's where this little box comes in. 67 00:02:54,907 --> 00:02:57,677 PATEL: There's no doubt, our data is out there, 68 00:02:57,710 --> 00:03:00,179 but did you ever wonder where it goes 69 00:03:00,212 --> 00:03:02,148 and how it's used? 70 00:03:02,181 --> 00:03:03,216 I do. 71 00:03:03,249 --> 00:03:06,018 I want to know: what are the benefits of sharing 72 00:03:06,051 --> 00:03:07,587 and the risks? 73 00:03:07,620 --> 00:03:11,123 And what can we do to make our connected world safer 74 00:03:11,156 --> 00:03:14,060 and just generally better for everyone? 75 00:03:18,430 --> 00:03:20,633 First, the basics. 76 00:03:20,666 --> 00:03:22,134 I want to know: 77 00:03:22,167 --> 00:03:25,438 how much personal data have I been sharing? 78 00:03:25,471 --> 00:03:28,574 Meet Hayley Tsukayama, tech journalist 79 00:03:28,607 --> 00:03:30,409 and data privacy advocate. 80 00:03:30,442 --> 00:03:32,245 (chuckles) 81 00:03:30,442 --> 00:03:32,245 PATEL: You must be Hayley. 82 00:03:32,278 --> 00:03:33,579 Hi, nice to meet you. 83 00:03:33,612 --> 00:03:35,715 What is going on? 84 00:03:35,748 --> 00:03:38,084 (voiceover): Okay, hold on, wasn't expecting this. 85 00:03:38,117 --> 00:03:41,487 She's already got my whole life up on the screen. 86 00:03:41,520 --> 00:03:44,490 So this is a data report gathered about you 87 00:03:44,523 --> 00:03:46,726 from social media posts, 88 00:03:46,759 --> 00:03:48,628 from the images of you that may be on the internet, 89 00:03:48,661 --> 00:03:51,130 from publicly available information. 90 00:03:51,163 --> 00:03:53,132 This is like a family business. 91 00:03:53,165 --> 00:03:54,634 That's my dad's cell phone number. 92 00:03:54,667 --> 00:03:56,469 Why is this available? 93 00:03:56,502 --> 00:03:58,671 (groaning): Oh, this is my address! 94 00:03:58,704 --> 00:03:59,839 This is just available? 95 00:03:59,872 --> 00:04:00,773 Just available online. 96 00:04:00,806 --> 00:04:02,642 Okay, you guys are going to 97 00:04:02,675 --> 00:04:04,577 blur all this, right? Please? 98 00:04:04,610 --> 00:04:07,079 There's-- oh, okay, cool, there's my cell phone number. 99 00:04:07,112 --> 00:04:09,749 Oh, this is concerning. 100 00:04:09,782 --> 00:04:12,551 As a medical doctor, 101 00:04:12,584 --> 00:04:15,021 we all have license numbers 102 00:04:15,054 --> 00:04:17,256 and issue dates and expiration dates. 103 00:04:17,289 --> 00:04:19,091 (chuckling): And it's literally right here. 104 00:04:19,124 --> 00:04:20,793 This is so weird, 105 00:04:20,826 --> 00:04:22,428 these are the names of my neighbors 106 00:04:22,461 --> 00:04:23,997 from my childhood home. 107 00:04:24,931 --> 00:04:27,133 (whispering): Why do you have this information? 108 00:04:27,166 --> 00:04:29,535 Like, I haven't seen these names in... 109 00:04:29,568 --> 00:04:31,037 years. 110 00:04:31,070 --> 00:04:31,971 (voiceover): Not gonna lie, 111 00:04:32,005 --> 00:04:34,640 I expected some of my data to be out there, 112 00:04:34,673 --> 00:04:35,641 but this is... 113 00:04:35,674 --> 00:04:38,177 this is just creepy. 114 00:04:38,210 --> 00:04:39,111 How is there a report 115 00:04:39,145 --> 00:04:42,415 about who my neighbors were in the '80s? 116 00:04:42,448 --> 00:04:44,283 LEVY: You can be assured that pretty much 117 00:04:44,316 --> 00:04:45,551 everything you do on the web 118 00:04:45,584 --> 00:04:46,552 and with a browser 119 00:04:46,585 --> 00:04:48,220 is being tracked and logged. 120 00:04:48,253 --> 00:04:50,523 Where you go, what you look at, 121 00:04:50,556 --> 00:04:51,824 what apps you use. 122 00:04:51,857 --> 00:04:54,660 SAFIYA NOBLE: Modern life has been arranged 123 00:04:54,693 --> 00:04:57,096 so that every aspect of 124 00:04:57,129 --> 00:04:58,597 what we do and how we live can be captured. 125 00:04:58,631 --> 00:05:02,001 MEREDITH WHITTAKER: They pick up our faces as we walk down the street. 126 00:05:02,034 --> 00:05:06,238 They track our keystrokes while we're at work 127 00:05:06,271 --> 00:05:08,040 on behalf of our employer. 128 00:05:08,073 --> 00:05:08,941 (keys clacking) 129 00:05:08,974 --> 00:05:10,676 GALPERIN: And ad networks use a bunch of 130 00:05:10,709 --> 00:05:13,112 creepy and nefarious ways of figuring out 131 00:05:13,145 --> 00:05:14,747 who you are, what you're doing, and where you're going. 132 00:05:15,647 --> 00:05:18,150 PATEL: What happened to the web I grew up with? 133 00:05:18,183 --> 00:05:21,087 ♪ ♪ 134 00:05:21,120 --> 00:05:24,123 I came of age when the internet was a fun and weird party, 135 00:05:24,156 --> 00:05:25,157 and everyone was invited. 136 00:05:25,190 --> 00:05:27,226 Remember GeoCities, 137 00:05:27,259 --> 00:05:29,128 AOL Instant Messenger, 138 00:05:29,161 --> 00:05:32,031 or the dancing "ooga chacka, ooga chacka" baby? 139 00:05:32,064 --> 00:05:33,532 ♪ ♪ 140 00:05:33,565 --> 00:05:35,435 Today, it's clear that innocence is gone. 141 00:05:36,668 --> 00:05:37,704 Is the party over? 142 00:05:40,205 --> 00:05:44,643 To understand the present, I want a refresher on the past. 143 00:05:44,676 --> 00:05:46,112 (machinery whirring) 144 00:05:46,145 --> 00:05:48,581 So I'm visiting the Computer History Museum 145 00:05:48,614 --> 00:05:50,149 in Silicon Valley. 146 00:05:50,182 --> 00:05:51,684 (video game music, Patel chuckling) 147 00:05:51,717 --> 00:05:54,387 MARC WEBER: Okay, I'm headed straight for the sun... 148 00:05:54,420 --> 00:05:56,789 PATEL: I'm meeting computer historian Marc Weber. 149 00:05:56,822 --> 00:05:58,758 What a maneuver! There's a straight line 150 00:05:58,791 --> 00:06:00,292 of bullets coming right at you-- 151 00:06:00,325 --> 00:06:01,460 (exploding sound effect, Patel groans) 152 00:06:01,493 --> 00:06:02,695 (voiceover): ...Who just wasted me 153 00:06:02,728 --> 00:06:04,764 in the cosmic battlefield of "Space War," 154 00:06:04,797 --> 00:06:06,532 one of the first video games. 155 00:06:06,565 --> 00:06:09,001 (laughing) 156 00:06:06,565 --> 00:06:09,001 This is actually really fun. 157 00:06:09,034 --> 00:06:10,569 ♪ ♪ 158 00:06:10,602 --> 00:06:12,638 This is cool. 159 00:06:12,671 --> 00:06:16,108 ICBM computer from a nuclear missile. 160 00:06:16,141 --> 00:06:17,243 Woah. 161 00:06:17,276 --> 00:06:19,044 Human-computer interaction. 162 00:06:19,077 --> 00:06:21,447 PATEL: Now, this looks fascinating. 163 00:06:21,480 --> 00:06:22,615 I can't tell if this is like, 164 00:06:22,648 --> 00:06:25,518 this universal clock apparatus, 165 00:06:25,551 --> 00:06:27,052 or what's happening here? 166 00:06:27,085 --> 00:06:30,456 This is the first punch card machine. 167 00:06:30,489 --> 00:06:33,058 And this was an invention 168 00:06:33,091 --> 00:06:35,694 to make the U.S. census faster. 169 00:06:35,727 --> 00:06:36,728 PATEL (voiceover): It's kind of wild, 170 00:06:36,762 --> 00:06:40,132 but the dawn of automated personal data collection 171 00:06:40,165 --> 00:06:41,801 looks like this-- 172 00:06:41,834 --> 00:06:45,304 census info poked into humble little punch cards. 173 00:06:45,337 --> 00:06:48,107 Marc, can you explain punch cards to me? 174 00:06:48,140 --> 00:06:49,141 Because when I think punch cards, 175 00:06:49,174 --> 00:06:51,544 I'm thinking lottery tickets, 176 00:06:51,577 --> 00:06:55,147 or "buy nine cups of coffee, and your tenth is free." 177 00:06:55,180 --> 00:07:00,019 Well, it was the first way to record machine-readable data. 178 00:07:00,052 --> 00:07:04,056 PATEL: Okay, let's make sense of the census. 179 00:07:04,089 --> 00:07:06,358 This kind of data collection 180 00:07:06,391 --> 00:07:08,060 has been going on for centuries. 181 00:07:08,093 --> 00:07:10,463 But starting in 1890, 182 00:07:10,496 --> 00:07:12,565 data was recorded in a pattern of holes 183 00:07:12,598 --> 00:07:14,733 "punched" into a census card. 184 00:07:14,766 --> 00:07:17,403 So the cards were used to collect census data. 185 00:07:17,436 --> 00:07:20,105 What exact questions were on there? 186 00:07:20,138 --> 00:07:23,976 So things like age, gender, number of children. 187 00:07:24,843 --> 00:07:27,146 PATEL: When a card passes through the machine, 188 00:07:27,179 --> 00:07:30,082 the holes allow pins to make electrical connections 189 00:07:30,115 --> 00:07:31,083 through the card. 190 00:07:31,116 --> 00:07:33,452 A counter keeps a running tally 191 00:07:33,485 --> 00:07:34,453 in each census category 192 00:07:34,486 --> 00:07:37,056 as more cards pass through. 193 00:07:37,089 --> 00:07:39,158 Census data is how the government 194 00:07:39,191 --> 00:07:41,560 allocates resources for schools and hospitals; 195 00:07:41,593 --> 00:07:44,096 draws the lines for districts; 196 00:07:44,129 --> 00:07:46,031 and decides how many representatives 197 00:07:46,064 --> 00:07:48,033 each state will send to congress. 198 00:07:48,066 --> 00:07:52,304 It's a reminder of the value of collecting data, 199 00:07:52,337 --> 00:07:53,706 but it's a far cry from 200 00:07:53,739 --> 00:07:55,441 having my every move tracked on the internet. 201 00:07:57,376 --> 00:07:59,044 To help connect the dots, 202 00:07:59,077 --> 00:08:00,980 Marc shows me the next surprising step 203 00:08:01,013 --> 00:08:03,482 in the evolution of data collection. 204 00:08:03,515 --> 00:08:05,751 ♪ ♪ 205 00:08:05,784 --> 00:08:07,419 I look at this and I'm almost like, 206 00:08:07,452 --> 00:08:09,588 "Oh, this looks like a modern office building to me." 207 00:08:09,621 --> 00:08:11,757 WEBER: Exactly. Each one of those 208 00:08:11,790 --> 00:08:14,627 is one of these giant terminals here. 209 00:08:14,660 --> 00:08:15,761 (static hissing) 210 00:08:15,794 --> 00:08:18,030 PATEL: During the Cold War, 211 00:08:18,063 --> 00:08:19,732 IBM figured out how to hook up computers 212 00:08:19,765 --> 00:08:21,767 from all across the country to monitor 213 00:08:21,800 --> 00:08:24,270 U.S. airspace in real-time. 214 00:08:24,303 --> 00:08:26,038 (rocket blasting off) 215 00:08:26,071 --> 00:08:30,342 So, this is a terminal from SAGE. 216 00:08:30,375 --> 00:08:34,146 (beeping, static) 217 00:08:35,347 --> 00:08:39,084 PATEL: It was the first real-time networked data system. 218 00:08:39,117 --> 00:08:41,287 Real-time is just that: 219 00:08:41,320 --> 00:08:42,521 instantaneous. 220 00:08:42,554 --> 00:08:45,791 And "networked" means connected. 221 00:08:45,824 --> 00:08:47,560 Computers from all across the country 222 00:08:47,593 --> 00:08:49,161 were hooked up to each other, 223 00:08:49,194 --> 00:08:51,063 so they could share data in real time, 224 00:08:51,096 --> 00:08:54,166 Sort of like the internet. 225 00:08:54,866 --> 00:08:59,204 WEBER: The whole point was to track incoming Soviet bombers, 226 00:08:59,237 --> 00:09:01,574 and they built, arguably, 227 00:09:01,607 --> 00:09:04,510 the first computer network in the world. 228 00:09:04,543 --> 00:09:06,011 PATEL: IBM soon realized 229 00:09:06,044 --> 00:09:08,547 that their aircraft-tracking computers 230 00:09:08,580 --> 00:09:10,382 could be used commercially. 231 00:09:10,415 --> 00:09:14,086 ♪ ♪ 232 00:09:14,119 --> 00:09:17,089 So In 1960, along came SABRE. 233 00:09:17,122 --> 00:09:19,625 (beeping, static) 234 00:09:19,658 --> 00:09:21,694 A real-time networked data system 235 00:09:21,727 --> 00:09:25,097 that shared personal data. 236 00:09:25,130 --> 00:09:27,266 WEBER: The story goes that 237 00:09:27,299 --> 00:09:30,736 the head of American Airlines met with IBM, 238 00:09:30,769 --> 00:09:33,105 and they decided to do a partnership, 239 00:09:33,138 --> 00:09:35,608 the key idea being real time. 240 00:09:35,641 --> 00:09:38,744 They could look at your age, your name, 241 00:09:38,777 --> 00:09:40,446 financial information, 242 00:09:40,479 --> 00:09:41,747 what flights you'd been on before, 243 00:09:41,780 --> 00:09:45,050 your dietary preferences for your meal, 244 00:09:45,083 --> 00:09:47,586 all of this right then in real time. 245 00:09:47,619 --> 00:09:50,589 PATEL: We went from tracking bombs to 246 00:09:50,622 --> 00:09:51,590 tracking butts on planes. 247 00:09:51,623 --> 00:09:52,692 WEBER: Exactly. 248 00:09:54,626 --> 00:09:56,662 PATEL (voiceover): Between "Pong," punch cards, 249 00:09:56,695 --> 00:09:58,130 and planes... 250 00:09:56,695 --> 00:09:58,130 Whoa, whoa, whoa! 251 00:09:58,163 --> 00:10:01,200 PATEL (voiceover): I could see how data started connecting the world-- 252 00:10:01,233 --> 00:10:03,335 the military to our airspace 253 00:10:03,368 --> 00:10:05,438 and companies to their customers. 254 00:10:06,305 --> 00:10:08,707 But what if those customers all over the world 255 00:10:08,740 --> 00:10:11,110 were linked up to each other? 256 00:10:11,143 --> 00:10:12,778 What would we even call that? 257 00:10:12,811 --> 00:10:16,248 Oh yeah, the World Wide Web. 258 00:10:16,281 --> 00:10:18,450 PRESENTER: The World Wide Web is a part of our lives 259 00:10:18,483 --> 00:10:20,719 and getting bigger every day. 260 00:10:20,752 --> 00:10:23,255 But what about the man who dreamt it all up? 261 00:10:23,288 --> 00:10:25,691 PATEL: News reports opened our eyes 262 00:10:25,724 --> 00:10:27,593 to this innovation and its creator, 263 00:10:27,626 --> 00:10:29,495 Tim Berners-Lee. 264 00:10:29,528 --> 00:10:30,763 PRESENTER: He simply wanted 265 00:10:30,796 --> 00:10:33,366 to give it away for the benefit of others. 266 00:10:34,133 --> 00:10:35,567 TIM BERNERS-LEE: When the web started, 267 00:10:35,600 --> 00:10:38,137 anybody could make a website. 268 00:10:38,170 --> 00:10:40,172 You could make your own style, 269 00:10:40,205 --> 00:10:42,174 your own poems, your own blogs, 270 00:10:42,207 --> 00:10:43,609 and you could link to other people. 271 00:10:43,642 --> 00:10:47,613 The feeling and the sense was of tremendous empowerment. 272 00:10:47,646 --> 00:10:49,181 (modem dialing up) 273 00:10:49,214 --> 00:10:51,350 NOBLE: Some of us remember the internet 274 00:10:51,383 --> 00:10:54,353 when it was managed and curated by people. 275 00:10:54,386 --> 00:10:55,788 Where it was, you know, 276 00:10:55,821 --> 00:10:57,656 bulletin board systems and chat rooms. 277 00:10:57,689 --> 00:11:00,092 ♪ ♪ 278 00:11:00,125 --> 00:11:01,627 PATEL: In the late '90s, small start-ups 279 00:11:01,660 --> 00:11:04,196 were maturing into big tech companies-- 280 00:11:04,229 --> 00:11:07,733 with lots of users and user data. 281 00:11:09,201 --> 00:11:10,803 KAHLE: As the web grew, 282 00:11:10,836 --> 00:11:12,471 we ended up with a very few companies 283 00:11:12,504 --> 00:11:14,139 going and doing all of the hosting. 284 00:11:14,172 --> 00:11:17,076 It wasn't your actual personal computer doing it. 285 00:11:17,109 --> 00:11:21,747 NOBLE: The large platforms that have emerged are dependent 286 00:11:21,780 --> 00:11:24,183 upon user-generated content 287 00:11:24,216 --> 00:11:25,751 and user engagement. 288 00:11:25,784 --> 00:11:30,355 The modern internet is a wholly commercial kind of internet. 289 00:11:30,388 --> 00:11:33,659 PATEL: And as web traffic started to flow more and more 290 00:11:33,692 --> 00:11:35,494 through just a few companies, 291 00:11:35,527 --> 00:11:38,530 they began to realize the value of all this personal data 292 00:11:38,563 --> 00:11:40,833 piling up on their servers. 293 00:11:40,866 --> 00:11:43,402 ALEKSANDRA KOROLOVA: Google started to understand 294 00:11:43,435 --> 00:11:46,172 the power of individual's data. 295 00:11:47,105 --> 00:11:49,174 They have information about 296 00:11:49,207 --> 00:11:50,309 not just how the websites 297 00:11:50,342 --> 00:11:51,577 are interconnected, 298 00:11:51,610 --> 00:11:55,147 but also information about the individuals. 299 00:11:55,180 --> 00:11:57,082 HILL: The big technology companies. 300 00:11:57,115 --> 00:11:59,218 They're looking at where you are, 301 00:11:59,251 --> 00:12:00,586 They're wanting to know what your gender is, 302 00:12:00,619 --> 00:12:01,720 what your age is, 303 00:12:01,753 --> 00:12:03,388 you know, how much you have to spend, 304 00:12:03,421 --> 00:12:05,791 what your political beliefs are. 305 00:12:05,824 --> 00:12:08,227 They have a lot of power to determine 306 00:12:08,260 --> 00:12:09,561 what our privacy is. 307 00:12:09,594 --> 00:12:12,030 RASKAR: That's trillions of dollars 308 00:12:12,063 --> 00:12:14,099 of economic value that's out there, 309 00:12:14,132 --> 00:12:15,467 and there's a constant struggle 310 00:12:15,500 --> 00:12:17,035 between who owns the data. 311 00:12:17,068 --> 00:12:18,036 We create the data, 312 00:12:18,069 --> 00:12:20,139 but somebody else monetizes it. 313 00:12:21,773 --> 00:12:23,575 PATEL: As big tech was maturing, 314 00:12:23,608 --> 00:12:26,378 early data collection on websites was pretty limited. 315 00:12:27,412 --> 00:12:29,348 So what happened to supercharge it? 316 00:12:29,381 --> 00:12:31,817 To create the vast tracking infrastructure 317 00:12:31,850 --> 00:12:35,053 that allowed Hayley to find out so much about me? 318 00:12:35,086 --> 00:12:37,556 It turns out things really got going 319 00:12:37,589 --> 00:12:39,725 when someone invented... 320 00:12:39,758 --> 00:12:41,093 Cookies? 321 00:12:41,993 --> 00:12:44,596 A cookie is not actually a tasty snack. 322 00:12:44,629 --> 00:12:46,732 When you go to a website, 323 00:12:46,765 --> 00:12:50,202 the website sends 324 00:12:50,235 --> 00:12:51,670 a small file to your browser. 325 00:12:51,703 --> 00:12:52,704 (keys clacking) 326 00:12:52,738 --> 00:12:54,840 PATEL: That small file allows the websites 327 00:12:54,873 --> 00:12:56,742 to collect information about your visit, 328 00:12:56,775 --> 00:12:59,711 and update it every time you come back. 329 00:12:59,744 --> 00:13:02,014 You might have heard of cookies 330 00:13:02,047 --> 00:13:03,248 because a lot of websites 331 00:13:03,281 --> 00:13:04,716 pop up with messages prompting you 332 00:13:04,749 --> 00:13:06,218 to accept theirs. 333 00:13:06,251 --> 00:13:10,222 But what happens after you hit "accept"? 334 00:13:10,255 --> 00:13:12,057 GALPERIN: It then uses cookies 335 00:13:12,090 --> 00:13:14,626 to track who you are and what you're doing, 336 00:13:14,659 --> 00:13:16,161 including in many cases, 337 00:13:16,194 --> 00:13:18,297 all of the other websites that you go to. 338 00:13:18,330 --> 00:13:21,200 RUMMAN CHOWDHURY: Cookies have the cutest name, 339 00:13:21,233 --> 00:13:23,735 but they're actually a really important 340 00:13:23,768 --> 00:13:26,471 piece of information about you. 341 00:13:26,504 --> 00:13:28,073 Every time you click on a menu, 342 00:13:28,106 --> 00:13:29,274 every time you look at an item 343 00:13:29,307 --> 00:13:30,609 or put it in your cart, 344 00:13:30,642 --> 00:13:33,111 every time you want to buy something 345 00:13:33,144 --> 00:13:35,614 and click out of the website and come back in. 346 00:13:35,647 --> 00:13:37,249 A cookie is what's enabling you to do that. 347 00:13:37,282 --> 00:13:39,117 It's a piece of tracking information. 348 00:13:39,150 --> 00:13:42,354 You can impute data and information about you 349 00:13:42,387 --> 00:13:45,324 from the seemingly innocent behavior online 350 00:13:45,357 --> 00:13:47,092 that's tracked via cookies. 351 00:13:47,125 --> 00:13:49,528 Do you have certain lifestyle conditions? 352 00:13:49,561 --> 00:13:51,163 What age are you? 353 00:13:51,196 --> 00:13:52,331 What gender or race are you? 354 00:13:52,364 --> 00:13:54,300 Do you have children? 355 00:13:56,201 --> 00:13:57,836 PATEL: Okay, so I'm starting to get 356 00:13:57,869 --> 00:13:59,638 that these tech companies 357 00:13:59,671 --> 00:14:01,373 use things like cookies to keep track of 358 00:14:01,406 --> 00:14:03,008 what sites I'm on, what I'm shopping for, 359 00:14:03,041 --> 00:14:04,176 and what I'm watching. 360 00:14:04,209 --> 00:14:06,778 ♪ ♪ 361 00:14:06,811 --> 00:14:08,480 (doorbell chimes) 362 00:14:08,513 --> 00:14:09,648 But do they have other ways 363 00:14:09,681 --> 00:14:11,517 of learning the secrets in my data? 364 00:14:12,517 --> 00:14:14,119 To learn more, 365 00:14:14,152 --> 00:14:16,021 I'm tracking down a data security expert 366 00:14:16,054 --> 00:14:17,422 in his hacking high-tech superhero lair... 367 00:14:17,455 --> 00:14:19,725 naturally. 368 00:14:19,758 --> 00:14:23,028 (door rolling open) 369 00:14:23,061 --> 00:14:25,030 Are you Patrick Jackson? My name's Alok. 370 00:14:25,063 --> 00:14:26,031 Yes, I am. 371 00:14:26,064 --> 00:14:27,266 Awesome, I'm in the right place. 372 00:14:27,299 --> 00:14:29,668 (door rolls shut) 373 00:14:29,701 --> 00:14:31,270 Your phone is sending this extra data 374 00:14:31,303 --> 00:14:32,271 to these people that 375 00:14:32,304 --> 00:14:33,505 you don't know exist. 376 00:14:33,538 --> 00:14:35,107 PATEL: Patrick Jackson has been 377 00:14:35,140 --> 00:14:37,109 all over the news for his work as 378 00:14:37,142 --> 00:14:38,810 a former NSA research scientist, 379 00:14:38,843 --> 00:14:40,579 and is now chief tech officer 380 00:14:40,612 --> 00:14:43,148 for the internet security firm Disconnect. 381 00:14:43,181 --> 00:14:45,117 And if anyone can help me 382 00:14:45,150 --> 00:14:48,186 understand how my personal data is leaking, 383 00:14:48,219 --> 00:14:49,488 it's him. 384 00:14:49,521 --> 00:14:51,790 Patrick, when I think about 385 00:14:51,823 --> 00:14:56,395 the main control of my work, life, play, 386 00:14:56,428 --> 00:14:58,363 what I'm doing at home, when I'm on the road, 387 00:14:58,396 --> 00:14:59,631 this is the mothership. 388 00:14:59,664 --> 00:15:02,100 If I were to relinquish control 389 00:15:02,133 --> 00:15:04,069 of this precious device for a few moments, 390 00:15:04,102 --> 00:15:06,071 can you show me, like, 391 00:15:06,104 --> 00:15:07,306 what I've inadvertently given up? 392 00:15:07,339 --> 00:15:08,473 Yes, yeah. 393 00:15:08,506 --> 00:15:10,108 I can show you what these data companies 394 00:15:10,141 --> 00:15:12,044 know about you and what they're collecting. 395 00:15:12,844 --> 00:15:14,579 PATEL (voiceover): Using a hacking technique 396 00:15:14,612 --> 00:15:15,781 called a "man-in-the-middle attack," 397 00:15:15,814 --> 00:15:18,550 Patrick can intercept the personal data 398 00:15:18,583 --> 00:15:20,152 that's leaving my device, 399 00:15:20,185 --> 00:15:23,021 essentially eavesdropping on a conversation 400 00:15:23,054 --> 00:15:24,523 between me and the websites 401 00:15:24,556 --> 00:15:27,125 and applications I use. 402 00:15:27,158 --> 00:15:28,493 JACKSON: Contact information, 403 00:15:28,526 --> 00:15:30,395 name, phone number, email address. 404 00:15:30,428 --> 00:15:32,531 When you agree to allow them to have your location, 405 00:15:32,564 --> 00:15:36,034 I can see not only where you're at on a map, 406 00:15:36,067 --> 00:15:38,070 but also where you're at in your house, 407 00:15:38,103 --> 00:15:39,604 whether you're at the back of the house 408 00:15:39,637 --> 00:15:41,306 or the front of the house. 409 00:15:41,339 --> 00:15:43,442 When you look at the data 410 00:15:43,475 --> 00:15:45,644 leaving the phone, every time you open an app, 411 00:15:45,677 --> 00:15:48,113 you send about, maybe, 412 00:15:48,146 --> 00:15:50,315 500 kilobytes of data to their servers. 413 00:15:50,348 --> 00:15:54,386 That is equivalent to about 125 pages of text 414 00:15:54,419 --> 00:15:56,388 that you would print in a printer. 415 00:15:59,858 --> 00:16:03,428 PATEL (voiceover): It's one thing if the apps on my phone are collecting data, 416 00:16:03,461 --> 00:16:05,130 I chose to download them. 417 00:16:05,163 --> 00:16:07,766 But Patrick says that other companies 418 00:16:07,799 --> 00:16:10,168 have even sneakier ways to get my data. 419 00:16:10,201 --> 00:16:11,670 Like something as harmless 420 00:16:11,703 --> 00:16:13,305 as a marketing email. 421 00:16:13,338 --> 00:16:15,507 To demonstrate, Patrick sends me 422 00:16:15,540 --> 00:16:17,542 a mock promotional email. 423 00:16:17,575 --> 00:16:19,511 I have an email that says 424 00:16:19,544 --> 00:16:21,079 "Shoe Sale." 425 00:16:21,112 --> 00:16:23,181 It says "open to view the shoe sale," 426 00:16:23,214 --> 00:16:26,151 and I want to open it, so I'm going to. 427 00:16:26,184 --> 00:16:29,321 "Hi, Alok, get ready for upcoming shoe sale." 428 00:16:29,354 --> 00:16:31,390 I like this graphic, and there's like, 429 00:16:31,423 --> 00:16:33,558 social media icons. This looks legit. 430 00:16:33,591 --> 00:16:35,160 (voiceover): It turns out, 431 00:16:35,193 --> 00:16:37,529 emails can include a tracking pixel-- 432 00:16:37,562 --> 00:16:41,333 also known as a spy or invisible pixel. 433 00:16:41,366 --> 00:16:44,036 JACKSON: An invisible pixel is a type of image 434 00:16:44,069 --> 00:16:46,038 you're never intended to see, 435 00:16:46,071 --> 00:16:49,341 but it still initiates a handshake of data 436 00:16:49,374 --> 00:16:52,177 from your device to these data companies. 437 00:16:52,210 --> 00:16:53,545 (keys clacking) 438 00:16:53,578 --> 00:16:55,380 Most of the emails that you receive 439 00:16:55,413 --> 00:16:57,282 likely have these tracking pixels in them. 440 00:16:57,315 --> 00:17:00,052 Most? 441 00:16:57,315 --> 00:17:00,052 Most. 442 00:17:01,252 --> 00:17:02,988 This invisible pixel is actually 443 00:17:03,021 --> 00:17:04,523 disguised as the banner 444 00:17:04,556 --> 00:17:06,124 in that email. 445 00:17:06,157 --> 00:17:10,095 In other cases, the tracking pixel will be a one-pixel, 446 00:17:10,128 --> 00:17:11,530 very, very tiny image 447 00:17:11,563 --> 00:17:13,165 that you would never see with your eyes, 448 00:17:13,198 --> 00:17:15,067 and it's not meant to be seen. 449 00:17:15,100 --> 00:17:16,368 (zooming in) 450 00:17:16,401 --> 00:17:17,769 PATEL: That little pixel, that little spy. 451 00:17:17,802 --> 00:17:20,038 See it? Right there. 452 00:17:20,071 --> 00:17:22,507 It can hide in images embedded in an email, 453 00:17:22,540 --> 00:17:25,444 like a banner, or even an "unsubscribe" button. 454 00:17:25,477 --> 00:17:27,245 And when you open the email, 455 00:17:27,278 --> 00:17:31,016 it contacts a tracking website to collect data about you. 456 00:17:31,049 --> 00:17:33,051 It can suck up your device model, 457 00:17:33,084 --> 00:17:35,087 location, and even some browsing history. 458 00:17:35,987 --> 00:17:39,057 JACKSON: This is essentially a digital fingerprint 459 00:17:39,090 --> 00:17:41,193 of your device. 460 00:17:39,090 --> 00:17:41,193 PATEL: No! 461 00:17:41,226 --> 00:17:44,196 JACKSON: That fingerprint would identify you as who you are, 462 00:17:44,229 --> 00:17:45,664 and somebody else in the future 463 00:17:45,697 --> 00:17:46,798 could look at that fingerprint, 464 00:17:46,831 --> 00:17:49,134 make you do a new fingerprint, 465 00:17:49,167 --> 00:17:52,137 and they would know that this is the same person. 466 00:17:52,170 --> 00:17:54,806 PATEL: Companies are snatching copies of my digital fingerprints 467 00:17:54,839 --> 00:17:57,042 wherever I go online. 468 00:17:57,075 --> 00:17:59,111 And by following that trail... 469 00:17:59,144 --> 00:18:01,113 JACKSON: Companies are, over time, 470 00:18:01,146 --> 00:18:03,515 collecting everything about you. 471 00:18:03,548 --> 00:18:06,051 That's how they build up this, 472 00:18:06,084 --> 00:18:07,986 this digital profile about you. 473 00:18:10,021 --> 00:18:13,225 HILL: The internet is this data collection machine, 474 00:18:13,258 --> 00:18:15,260 and as we're moving through the internet, 475 00:18:15,293 --> 00:18:16,428 there are these companies 476 00:18:16,461 --> 00:18:17,596 whose whole job is 477 00:18:17,629 --> 00:18:19,198 to reassemble that trail. 478 00:18:20,232 --> 00:18:23,535 PATEL: So now I know how my digital profile is out there, 479 00:18:23,568 --> 00:18:25,103 but why? 480 00:18:25,136 --> 00:18:26,638 Who really cares that 481 00:18:26,671 --> 00:18:28,273 I take pictures doing handstands 482 00:18:28,306 --> 00:18:30,075 and own way too many sneakers? 483 00:18:32,076 --> 00:18:34,112 Turns out, there's a whole industry 484 00:18:34,145 --> 00:18:36,148 devoted to selling my data. 485 00:18:36,181 --> 00:18:38,283 It's the data brokers. 486 00:18:38,316 --> 00:18:40,418 ♪ ♪ 487 00:18:40,451 --> 00:18:42,554 Data brokers are companies that are set up to 488 00:18:42,587 --> 00:18:44,689 collect information, repackage it, 489 00:18:44,722 --> 00:18:46,258 and resell it or re-share it 490 00:18:46,291 --> 00:18:48,193 to other companies that may want to know 491 00:18:48,226 --> 00:18:50,128 information about you. 492 00:18:50,161 --> 00:18:53,498 So what do data brokers want with all our personal data? 493 00:18:53,531 --> 00:18:56,301 Why do they care that I love chicken mole 494 00:18:56,334 --> 00:18:57,569 and that "Cool Runnings" 495 00:18:57,602 --> 00:18:59,971 is in my top five movies of all-time? 496 00:19:00,004 --> 00:19:01,740 TSUKAYAMA: They collect all this information, 497 00:19:01,773 --> 00:19:03,675 and then they're really trying to slice and dice it 498 00:19:03,708 --> 00:19:05,410 in ways that are appealing to customers. 499 00:19:05,443 --> 00:19:07,112 You know, it could be an employer 500 00:19:07,145 --> 00:19:08,713 who's doing research on you, 501 00:19:08,746 --> 00:19:11,049 it could be a retailer who wants to know 502 00:19:11,082 --> 00:19:13,452 what kind of customers they can target with ads. 503 00:19:14,719 --> 00:19:16,087 That kind of information 504 00:19:16,120 --> 00:19:18,089 is really valuable for advertisers, 505 00:19:18,122 --> 00:19:19,191 because they want to target advertising 506 00:19:19,224 --> 00:19:20,559 to a certain type of person. 507 00:19:21,526 --> 00:19:24,262 PATEL: Our data ends up eventually getting compiled 508 00:19:24,295 --> 00:19:25,764 into reports like these, 509 00:19:25,797 --> 00:19:28,033 that are then sold to... 510 00:19:28,066 --> 00:19:29,434 whoever's interested? 511 00:19:29,467 --> 00:19:31,136 TSUKAYAMA: Data brokers are able to say, 512 00:19:31,169 --> 00:19:33,071 "Look, we have a group of people 513 00:19:33,104 --> 00:19:35,574 "that will fit the audience of your product. 514 00:19:35,607 --> 00:19:39,110 "We really are happy to serve this list of people to you," 515 00:19:39,143 --> 00:19:41,313 or to make a score about how likely they might be 516 00:19:41,346 --> 00:19:43,315 to purchase your product. 517 00:19:45,116 --> 00:19:47,219 Okay, I know people say 518 00:19:47,252 --> 00:19:48,787 "Oh, your phones aren't listening to you," 519 00:19:48,820 --> 00:19:51,756 but we were just talking about retro video games, 520 00:19:51,789 --> 00:19:53,792 and here is an ad for 521 00:19:53,825 --> 00:19:56,027 home mini-arcade machines-- 522 00:19:56,060 --> 00:19:57,362 which looks kind of cool-- but how did it know 523 00:19:57,395 --> 00:19:59,130 we were just talking about that? 524 00:19:59,163 --> 00:20:00,265 Is my phone listening? 525 00:20:00,298 --> 00:20:01,466 Is it a psychic? 526 00:20:01,499 --> 00:20:03,335 What's happening? 527 00:20:03,368 --> 00:20:04,502 People always say, 528 00:20:04,535 --> 00:20:05,570 "I was talking about this product, 529 00:20:05,603 --> 00:20:07,072 and then I saw an ad for it. 530 00:20:07,105 --> 00:20:09,774 "Matt, are they listening through my phone?" 531 00:20:09,807 --> 00:20:11,109 And I'm like, "Well, they didn't hear you, 532 00:20:11,142 --> 00:20:12,611 they didn't listen to anything." 533 00:20:12,644 --> 00:20:14,179 The truth is actually more frightening. 534 00:20:14,212 --> 00:20:16,181 You talked about that thing 535 00:20:16,214 --> 00:20:17,682 because they influenced you 536 00:20:17,715 --> 00:20:20,085 into having this conversation. 537 00:20:20,118 --> 00:20:23,188 It's because the algorithm took you to this place. 538 00:20:23,221 --> 00:20:24,723 And that's the situation with our data. 539 00:20:25,490 --> 00:20:28,126 PATEL: There have been some outlier examples 540 00:20:28,159 --> 00:20:30,328 of ad tech companies listening without consent, 541 00:20:30,361 --> 00:20:31,730 but that's against the law. 542 00:20:31,763 --> 00:20:34,666 For the most part, advertising algorithms 543 00:20:34,699 --> 00:20:36,801 know you so well that they can predict 544 00:20:36,834 --> 00:20:38,470 what you would find interesting. 545 00:20:38,503 --> 00:20:40,705 They are so good because they've studied 546 00:20:40,738 --> 00:20:42,607 all the data gathered about you-- 547 00:20:42,640 --> 00:20:44,343 from the data brokers. 548 00:20:46,144 --> 00:20:47,112 There's this kind of dossier 549 00:20:47,145 --> 00:20:48,580 that's being created about you 550 00:20:48,613 --> 00:20:50,215 as you're wandering around the internet, 551 00:20:50,248 --> 00:20:52,217 and it's being used to, 552 00:20:52,250 --> 00:20:54,353 you know, decide what ad you see. 553 00:20:56,220 --> 00:20:59,224 PATEL: Advertising fuels the economics of the internet. 554 00:20:59,257 --> 00:21:01,226 And advertising is fueled by 555 00:21:01,259 --> 00:21:03,261 you, me, us-- 556 00:21:03,294 --> 00:21:05,530 our personal data. 557 00:21:05,563 --> 00:21:09,567 So how do the algorithms actually work? 558 00:21:09,600 --> 00:21:11,469 You land on a webpage, 559 00:21:11,502 --> 00:21:13,505 and that webpage 560 00:21:13,538 --> 00:21:15,173 gets your I.P. address. 561 00:21:15,206 --> 00:21:17,575 A unique identifier is returned to a data broker. 562 00:21:17,608 --> 00:21:18,810 That data broker 563 00:21:18,843 --> 00:21:20,278 looks up all the facts 564 00:21:20,311 --> 00:21:21,646 that were ever gleaned about you. 565 00:21:21,679 --> 00:21:25,183 A dossier that describes you. 566 00:21:25,216 --> 00:21:27,686 PATEL: And then advertisers literally bid, 567 00:21:27,719 --> 00:21:30,121 they bid on you, in a real-time auction 568 00:21:30,154 --> 00:21:32,257 based on the only lesson I remember 569 00:21:32,290 --> 00:21:36,061 from Econ 101: supply and demand. 570 00:21:36,094 --> 00:21:37,029 DOCTOROW: The demand-side platform 571 00:21:37,062 --> 00:21:40,298 that the advertiser is on says, "I have here 572 00:21:40,331 --> 00:21:42,167 "an 18- to 34-year-old man-child 573 00:21:42,200 --> 00:21:43,735 "with an Xbox in Southern California. 574 00:21:43,768 --> 00:21:46,504 "Who wants to pay to cram something 575 00:21:46,537 --> 00:21:48,239 nonconsensually into his eyeballs?" 576 00:21:48,272 --> 00:21:51,142 And that takes place in a marketplace, 577 00:21:51,175 --> 00:21:52,844 and you have advertisers on the other side 578 00:21:52,877 --> 00:21:54,379 who have standing orders. 579 00:21:54,412 --> 00:21:56,214 They're like, "I want to advertise to 580 00:21:56,247 --> 00:21:58,283 "18- to 34-year-old man-children in Southern California 581 00:21:58,316 --> 00:21:59,584 who own Xboxes," 582 00:21:59,617 --> 00:22:02,320 and the marketplace conducts 583 00:22:02,353 --> 00:22:04,756 an automated high-speed auction where it's just like, 584 00:22:04,789 --> 00:22:07,258 "I'll pay so many fractions of a cent," 585 00:22:07,291 --> 00:22:08,760 "I'll pay that plus ten percent." 586 00:22:08,793 --> 00:22:10,195 (auction bell rings) 587 00:22:10,228 --> 00:22:12,097 The high bidder gets to show you an ad. 588 00:22:13,498 --> 00:22:15,533 PATEL: All of this happens nearly instantly. 589 00:22:15,566 --> 00:22:18,470 And it's possible because data brokers 590 00:22:18,503 --> 00:22:20,372 sort and cull personal data 591 00:22:20,405 --> 00:22:22,474 into super detailed consumer groups. 592 00:22:22,507 --> 00:22:25,243 This is the process that delivers 593 00:22:25,276 --> 00:22:27,178 relevant personalized ads 594 00:22:27,211 --> 00:22:28,780 for cute shoes 595 00:22:28,813 --> 00:22:30,115 or that new tea club-- 596 00:22:30,148 --> 00:22:31,750 if you're into that sort of thing-- 597 00:22:31,783 --> 00:22:33,618 which all the ads seem to know about you. 598 00:22:35,086 --> 00:22:36,688 TSUKAYAMA: Here we have, for example, Soccer Mom. 599 00:22:36,721 --> 00:22:38,089 PATEL: Okay. 600 00:22:38,122 --> 00:22:39,291 I might be able to identify with that. 601 00:22:40,325 --> 00:22:43,828 A sporting goods retailer could then go and check out a file 602 00:22:43,861 --> 00:22:46,731 on what a Soccer Mom's online activity is like. 603 00:22:46,764 --> 00:22:49,401 TSUKAYAMA: What are the things that they tend to spend money on, 604 00:22:49,434 --> 00:22:50,535 and do they like to save? 605 00:22:50,568 --> 00:22:51,669 Are there certain times of year 606 00:22:51,702 --> 00:22:53,471 where they might spend more or less? 607 00:22:53,504 --> 00:22:58,209 PATEL: With all this data about Soccer Mom's consumer habits, 608 00:22:58,242 --> 00:23:01,446 retailers can send personalized ads with uncanny timing. 609 00:23:02,313 --> 00:23:06,017 Some people like the results-- soccer moms get deals. 610 00:23:06,050 --> 00:23:09,020 Advertisers keep websites we love in business. 611 00:23:09,053 --> 00:23:10,321 But... 612 00:23:10,354 --> 00:23:12,791 some consumer categories can be more concerning. 613 00:23:12,824 --> 00:23:15,026 HILL: Sometimes they'll have categories 614 00:23:15,059 --> 00:23:16,127 that are like, 615 00:23:16,160 --> 00:23:19,063 "This person has erectile dysfunction, 616 00:23:19,096 --> 00:23:21,099 "this person has a gambling problem. 617 00:23:21,132 --> 00:23:23,368 "This is a list of, kind of, 618 00:23:23,401 --> 00:23:26,271 people that are likely to fall for frauds." 619 00:23:26,304 --> 00:23:29,141 So these can be really powerful and damaging lists. 620 00:23:30,675 --> 00:23:31,810 TSUKAYAMA: So this one, for example, 621 00:23:31,843 --> 00:23:34,112 diabetes. 622 00:23:31,843 --> 00:23:34,112 PATEL: Wow. 623 00:23:34,145 --> 00:23:36,147 Okay, healthcare demographic... 624 00:23:36,180 --> 00:23:38,616 The thing about that, right, is like, 625 00:23:38,649 --> 00:23:41,052 when you're thinking particularly about health data, 626 00:23:41,085 --> 00:23:42,187 that indicates that you're probably 627 00:23:42,220 --> 00:23:43,822 in a pretty sensitive situation. 628 00:23:43,855 --> 00:23:48,159 PATEL: I'm now thinking about all the patients I take care of. 629 00:23:48,192 --> 00:23:49,627 And I shudder to think 630 00:23:49,660 --> 00:23:51,329 at the targeted ads that are 631 00:23:51,362 --> 00:23:53,097 deliberately targeting these individuals. 632 00:23:53,130 --> 00:23:54,498 (keys clacking) 633 00:23:54,532 --> 00:23:57,068 TSUKAYAMA: Data brokers have lists about sexual assault victims, 634 00:23:57,101 --> 00:23:59,370 they have lists about dementia sufferers. 635 00:23:59,403 --> 00:24:01,272 Those are some really concerning types of categories, 636 00:24:01,305 --> 00:24:03,308 and you could definitely see how 637 00:24:03,341 --> 00:24:05,677 an advertising company could take advantage 638 00:24:05,710 --> 00:24:07,245 of people on those lists. 639 00:24:09,046 --> 00:24:11,015 So I think a lot of people's first reaction 640 00:24:11,048 --> 00:24:12,383 on seeing these data broker reports 641 00:24:12,416 --> 00:24:14,118 is like, where has all of this come from? 642 00:24:14,151 --> 00:24:17,689 There are a lot of places where data brokers get information. 643 00:24:17,722 --> 00:24:19,290 Most commonly apps that 644 00:24:19,323 --> 00:24:21,159 you download that have deals 645 00:24:21,192 --> 00:24:23,194 with data brokers to share information. 646 00:24:23,227 --> 00:24:26,164 PATEL: All right, I knew that apps were getting my data, 647 00:24:26,197 --> 00:24:29,300 but I had no idea some were sharing it with data brokers. 648 00:24:29,333 --> 00:24:32,170 How is that even legal? 649 00:24:32,203 --> 00:24:34,305 TSUKAYAMA: How often have you seen a terms and conditions screen 650 00:24:34,338 --> 00:24:36,174 just like this? 651 00:24:36,207 --> 00:24:37,675 All the time. Anytime I download 652 00:24:37,708 --> 00:24:40,378 anything, basically. 653 00:24:37,708 --> 00:24:40,378 (both chuckle) 654 00:24:40,411 --> 00:24:43,748 I download apps all the time 655 00:24:43,781 --> 00:24:46,050 for work, play, life, convenience. 656 00:24:46,083 --> 00:24:48,119 I just scroll all the way down and hit accept. 657 00:24:48,152 --> 00:24:49,187 because I'm over it. 658 00:24:48,152 --> 00:24:49,187 Right. 659 00:24:49,220 --> 00:24:50,321 And I think that's how 660 00:24:50,354 --> 00:24:52,123 most people feel about it. 661 00:24:52,156 --> 00:24:54,125 PATEL: "By accepting these terms, 662 00:24:54,158 --> 00:24:56,127 you allow the platform to freely..." 663 00:24:56,160 --> 00:24:57,195 "...content for demonstration, promotion, and..." 664 00:24:57,228 --> 00:24:58,730 TSUKAYAMA: Terms and conditions are really long. 665 00:24:58,763 --> 00:25:00,665 Cool, I'm in a commercial 666 00:25:00,698 --> 00:25:03,101 and don't even know about it. 667 00:25:03,134 --> 00:25:04,602 TSUKAYAMA: Carnegie Mellon once did a study that said it would take 668 00:25:04,635 --> 00:25:07,205 days for somebody to get through all of the terms and conditions. 669 00:25:07,238 --> 00:25:09,007 They actually use the word exploiting. 670 00:25:09,040 --> 00:25:11,142 "You represent and warrant..." 671 00:25:11,175 --> 00:25:13,578 TSUKAYAMA: That puts people in a really difficult position 672 00:25:13,611 --> 00:25:16,548 when we're supposed to manage our own privacy, 673 00:25:16,581 --> 00:25:18,650 but we're also supposed to use all these things 674 00:25:18,683 --> 00:25:21,152 that are products that will make our lives better. 675 00:25:21,185 --> 00:25:23,054 (papers rustling, teacup clatters) 676 00:25:25,590 --> 00:25:28,359 Data brokers are a big industry. 677 00:25:28,392 --> 00:25:31,029 It's about a $200 billion industry right now. 678 00:25:31,062 --> 00:25:33,131 I think a lot of people expect it to grow to, 679 00:25:33,164 --> 00:25:35,500 you know, $400 billion in the next few years. 680 00:25:37,201 --> 00:25:40,505 NOBLE: That level of data from our past, 681 00:25:40,538 --> 00:25:42,807 all the things we've done being used 682 00:25:42,840 --> 00:25:44,142 and put into systems 683 00:25:44,175 --> 00:25:45,176 to help predict our futures, 684 00:25:45,209 --> 00:25:47,045 that's unprecedented, 685 00:25:47,078 --> 00:25:51,416 and that's rife with the potential for discrimination, 686 00:25:51,449 --> 00:25:53,184 for harm, for exclusion. 687 00:25:55,119 --> 00:25:56,220 PATEL: Okay, I know I said 688 00:25:56,253 --> 00:25:58,456 that I'm not the type to log in to... 689 00:25:58,489 --> 00:26:00,124 (voiceover): Look, I love being online. 690 00:26:00,157 --> 00:26:02,093 I like sharing what I'm up to on social media, 691 00:26:02,126 --> 00:26:04,495 and I'm not afraid to share my thoughts. 692 00:26:04,528 --> 00:26:07,031 Okay, bugs, I don't bite you, 693 00:26:07,064 --> 00:26:08,032 you don't bite me. 694 00:26:08,065 --> 00:26:09,133 It's that easy. 695 00:26:09,166 --> 00:26:11,436 But some of this personal data 696 00:26:11,469 --> 00:26:13,237 is, well, personal. 697 00:26:13,270 --> 00:26:14,739 So, now I need to know: 698 00:26:14,772 --> 00:26:17,008 What can I do to make my digital life 699 00:26:17,041 --> 00:26:19,010 more private and secure? 700 00:26:19,043 --> 00:26:23,281 GALPERIN: Privacy and security are not the same thing. 701 00:26:23,314 --> 00:26:24,682 For example, uh, 702 00:26:24,715 --> 00:26:26,751 Facebook is extremely interested 703 00:26:26,784 --> 00:26:28,319 in protecting your security. 704 00:26:28,352 --> 00:26:31,155 They want to make sure that it is always you 705 00:26:31,188 --> 00:26:32,590 logging in to your account. 706 00:26:32,623 --> 00:26:34,659 They will go through a great deal of trouble 707 00:26:34,692 --> 00:26:37,395 to keep your account secure. 708 00:26:38,195 --> 00:26:41,299 But you enter all kinds of data into that account. 709 00:26:41,332 --> 00:26:43,034 You tell it where you are located. 710 00:26:43,067 --> 00:26:44,435 You send it all of your pictures. 711 00:26:44,468 --> 00:26:46,137 You send messages 712 00:26:46,170 --> 00:26:49,107 and Facebook collects all of that data. 713 00:26:49,140 --> 00:26:51,042 They don't want you to keep it private. 714 00:26:51,075 --> 00:26:54,479 They want you to hand it to them so that they can use it in order 715 00:26:54,512 --> 00:26:57,515 to serve you targeted ads and make them money. 716 00:26:57,548 --> 00:26:59,550 PATEL (voiceover): My accounts are mostly secure 717 00:26:59,583 --> 00:27:01,653 when I control access to them. 718 00:27:01,686 --> 00:27:04,522 But that doesn't mean the data I put in them 719 00:27:04,555 --> 00:27:07,392 stays private, far from it. 720 00:27:07,425 --> 00:27:10,762 Privacy and security are not the same. 721 00:27:10,795 --> 00:27:13,598 But they are two sides of the same coin, 722 00:27:13,631 --> 00:27:15,166 and I have to understand both 723 00:27:15,199 --> 00:27:16,467 if I'm gonna protect 724 00:27:16,500 --> 00:27:18,002 my personal data. 725 00:27:18,035 --> 00:27:20,471 MITCHELL: When your privacy is taken from you, 726 00:27:20,504 --> 00:27:22,373 your agency is taken from you. 727 00:27:22,406 --> 00:27:25,009 Privacy is that whisper. 728 00:27:25,042 --> 00:27:27,679 When you think you're whispering to your friend, 729 00:27:27,712 --> 00:27:30,114 but you're shouting in a crowded elevator, 730 00:27:30,147 --> 00:27:32,016 you're robbed of something. 731 00:27:32,049 --> 00:27:34,753 And that's why privacy is so important. 732 00:27:35,720 --> 00:27:39,023 PATEL: What can I do right now to protect my privacy 733 00:27:39,056 --> 00:27:40,158 and my security? 734 00:27:41,325 --> 00:27:44,696 To learn tips and tools to preserve my data on both fronts, 735 00:27:44,729 --> 00:27:48,132 I'm chatting with hacker and educator Matt Mitchell 736 00:27:48,165 --> 00:27:52,170 and cybersecurity expert Eva Galperin. 737 00:27:52,203 --> 00:27:55,039 First up: privacy. 738 00:27:55,072 --> 00:27:56,240 Sorry. 739 00:27:56,273 --> 00:27:58,142 (whispering): Privacy. 740 00:27:58,175 --> 00:28:00,311 Matt is a privacy advocate 741 00:28:00,344 --> 00:28:02,547 at CryptoHarlem, as in cryptography, 742 00:28:02,580 --> 00:28:06,551 the process of hiding or coding information. 743 00:28:06,584 --> 00:28:09,287 Hey. I'm Matt. Thanks for coming to CryptoHarlem. 744 00:28:09,320 --> 00:28:13,524 MITCHELL (voiceover): CryptoHarlem is anti-surveillance workshops 745 00:28:13,557 --> 00:28:15,259 for the Black community 746 00:28:15,292 --> 00:28:17,328 and all marginalized communities around the world. 747 00:28:18,128 --> 00:28:21,399 And our mission is to develop people's digital skills 748 00:28:21,432 --> 00:28:23,034 so they can actually help us in the fight 749 00:28:23,067 --> 00:28:25,403 to push back on digital harms. 750 00:28:25,436 --> 00:28:28,039 MITCHELL: Privacy is not secrecy. 751 00:28:28,072 --> 00:28:28,773 Privacy is just a door. 752 00:28:28,806 --> 00:28:31,008 A door in your home. 753 00:28:31,041 --> 00:28:32,143 There's a sense of, like, 754 00:28:32,176 --> 00:28:34,245 I want to control what can be seen, 755 00:28:34,278 --> 00:28:35,747 what can't be seen just for me. 756 00:28:36,547 --> 00:28:38,683 PATEL (voiceover): And I want to close that door. 757 00:28:38,716 --> 00:28:40,151 So how do I do this? 758 00:28:40,184 --> 00:28:41,552 Even just a little? 759 00:28:41,585 --> 00:28:43,020 PATEL: Okay, what do I do 760 00:28:43,053 --> 00:28:45,490 to make all this safer for me? 761 00:28:45,523 --> 00:28:48,059 What do I do, who do I talk to, how do I start? 762 00:28:48,092 --> 00:28:49,260 You have to ask yourself, 763 00:28:49,293 --> 00:28:51,229 "Is this a problem that needs to be fixed?" 764 00:28:51,262 --> 00:28:53,030 Privacy isn't a switch. 765 00:28:53,063 --> 00:28:54,332 It's a dial. 766 00:28:54,365 --> 00:28:56,567 You get to control how much you share 767 00:28:56,600 --> 00:28:58,102 with who and with what. 768 00:28:58,135 --> 00:29:00,438 PATEL (voiceover): Let's start with a big one, 769 00:29:00,471 --> 00:29:03,007 something I use all the time, every day, 770 00:29:03,040 --> 00:29:05,076 and I bet you do, too. 771 00:29:05,109 --> 00:29:08,146 Have you ever used this website called Google? 772 00:29:08,179 --> 00:29:09,413 I've heard of it. 773 00:29:08,179 --> 00:29:09,413 Yeah. 774 00:29:09,446 --> 00:29:10,648 Well, let's check this out. 775 00:29:10,681 --> 00:29:11,983 Well, if we go here 776 00:29:12,016 --> 00:29:17,322 to myactivity.google.com... 777 00:29:19,123 --> 00:29:22,260 ...it'll show us all the things that you've been doing. 778 00:29:22,293 --> 00:29:23,461 So for example, 779 00:29:23,494 --> 00:29:25,029 when we go here, 780 00:29:25,062 --> 00:29:28,633 we see all the different Google services that you use. 781 00:29:28,666 --> 00:29:30,702 I don't think they make a service you don't use. 782 00:29:31,502 --> 00:29:34,539 PATEL (voiceover): These platforms are so deeply embedded in many of our lives 783 00:29:34,572 --> 00:29:36,040 and for good reason. 784 00:29:36,073 --> 00:29:39,043 They make products that can be really useful. 785 00:29:39,076 --> 00:29:40,478 It's hard for me to imagine 786 00:29:40,511 --> 00:29:42,213 going a single day without searching the web 787 00:29:42,246 --> 00:29:44,382 or using a navigation app. 788 00:29:44,415 --> 00:29:47,118 But they also suck up a lot of our data. 789 00:29:47,151 --> 00:29:49,387 It's a trade-off that I'm comfortable making, 790 00:29:49,420 --> 00:29:51,022 within reason. 791 00:29:51,055 --> 00:29:55,259 I've used literally everything Google has ever offered. 792 00:29:55,292 --> 00:29:57,562 And it knows what you've used. 793 00:29:57,595 --> 00:29:59,630 And it records everything you've ever used 794 00:29:59,663 --> 00:30:01,098 and how you've used it. 795 00:30:01,131 --> 00:30:02,533 Every search term you've used, 796 00:30:02,566 --> 00:30:06,037 every, uh, you know, shopping item you've used. 797 00:30:06,070 --> 00:30:10,808 But this is the dashboard to delete it. 798 00:30:10,841 --> 00:30:13,044 PATEL (voiceover): I didn't know this, but I can literally just delete 799 00:30:13,077 --> 00:30:16,047 huge amounts of data that Google is storing about me. 800 00:30:16,080 --> 00:30:19,350 And the same is true for a lot of other services. 801 00:30:19,383 --> 00:30:22,053 We can dial to whatever level we feel comfortable. 802 00:30:22,086 --> 00:30:23,588 For example, on LinkedIn, 803 00:30:23,621 --> 00:30:25,056 you would just click on me, 804 00:30:25,089 --> 00:30:29,293 and then you would go to your settings and privacy. 805 00:30:29,326 --> 00:30:30,828 Here, when we go to manage your activity, 806 00:30:30,861 --> 00:30:33,231 it tells you that, you know, 807 00:30:33,264 --> 00:30:34,498 you started sharing your LinkedIn data 808 00:30:34,531 --> 00:30:36,534 with a permitted application. 809 00:30:36,567 --> 00:30:40,838 PATEL (voiceover): Treating privacy like a dial means it's not all or nothing. 810 00:30:40,871 --> 00:30:45,176 You can have your data cake and eat it, too. 811 00:30:45,209 --> 00:30:47,445 Like now I'm thinking I want to log into everything-- 812 00:30:47,478 --> 00:30:50,481 all my social media, my email, my LinkedIn, everything-- 813 00:30:50,514 --> 00:30:54,118 regularly and look to see who is using these. 814 00:30:54,151 --> 00:30:56,554 Exactly, it is about awareness. 815 00:30:56,587 --> 00:30:58,723 Furthermore, the companies, 816 00:30:58,756 --> 00:31:01,425 they know how many people actually use 817 00:31:01,458 --> 00:31:02,426 the privacy controls. 818 00:31:02,459 --> 00:31:04,061 And by you even peeking in it, 819 00:31:04,094 --> 00:31:08,099 you're saying I believe privacy matters. 820 00:31:08,132 --> 00:31:11,335 At the Electronic Frontier Foundation, 821 00:31:11,368 --> 00:31:14,138 Eva shows me how I can take my privacy game 822 00:31:14,171 --> 00:31:15,373 to the next level... 823 00:31:15,406 --> 00:31:19,143 learning some Surveillance Self-Defense. 824 00:31:20,010 --> 00:31:25,283 Although, apparently not that kind of self-defense. 825 00:31:25,316 --> 00:31:27,218 GALPERIN: So, the next step in your privacy journey 826 00:31:27,251 --> 00:31:29,320 is fighting back against 827 00:31:29,353 --> 00:31:31,122 types of corporate surveillance. 828 00:31:31,155 --> 00:31:33,057 I-- and one of the things 829 00:31:33,090 --> 00:31:35,660 that websites really like to do when, uh, 830 00:31:35,693 --> 00:31:38,296 is not just to track what you are doing on their website, 831 00:31:38,329 --> 00:31:40,698 but to track all the other websites that you go to. 832 00:31:40,731 --> 00:31:42,433 And they do this using cookies. 833 00:31:42,466 --> 00:31:43,734 There's some companies I trust, 834 00:31:43,767 --> 00:31:45,636 and I'm like, fine, you have these cookies. 835 00:31:45,669 --> 00:31:47,538 They're chocolate chip. I know where they were made. 836 00:31:47,571 --> 00:31:48,773 I know what you're doing with them. 837 00:31:48,806 --> 00:31:49,840 But then there's these third party companies, 838 00:31:49,873 --> 00:31:52,143 I don't want them around me. 839 00:31:52,176 --> 00:31:54,145 You can use a browser extension 840 00:31:54,178 --> 00:31:56,547 to eat these cookies, uh, 841 00:31:56,580 --> 00:31:57,815 and fight back against this kind of tracking 842 00:31:57,848 --> 00:32:00,451 and keep those websites from seeing where else you're going. 843 00:32:00,484 --> 00:32:04,088 PATEL (voiceover): Browser extensions are add-ons for your web browser 844 00:32:04,121 --> 00:32:07,191 that give it extra features and functionality, 845 00:32:07,224 --> 00:32:09,260 like eating cookies. 846 00:32:09,293 --> 00:32:10,494 I'm imagining this, 847 00:32:10,527 --> 00:32:14,165 like, digital Cookie Monster that's eating up 848 00:32:14,198 --> 00:32:17,168 all these pieces of my online activity 849 00:32:17,201 --> 00:32:20,071 so that companies don't know what I'm doing online. 850 00:32:20,104 --> 00:32:22,139 And it reduces the amount of privacy tracking. 851 00:32:22,172 --> 00:32:23,507 Am I understanding that? 852 00:32:23,540 --> 00:32:25,309 What these browser extensions 853 00:32:25,342 --> 00:32:30,281 do is they get rid of, uh, the tracking cookies 854 00:32:30,314 --> 00:32:32,116 that these websites use to see 855 00:32:32,149 --> 00:32:33,818 all the other sites that you're going to, 856 00:32:33,851 --> 00:32:35,052 which is none of their business. 857 00:32:35,085 --> 00:32:37,121 (knuckles crack) 858 00:32:37,154 --> 00:32:39,056 PATEL (voiceover): My personal digital world is starting to feel 859 00:32:39,089 --> 00:32:42,026 comfy, controlled and a lot more private. 860 00:32:42,993 --> 00:32:45,596 I've learned how to close the doors and blinds. 861 00:32:45,629 --> 00:32:49,133 But still, someone could open them right back up. 862 00:32:49,166 --> 00:32:50,701 I could get hacked. 863 00:32:50,734 --> 00:32:53,104 How do I lock my doors? 864 00:32:53,137 --> 00:32:55,439 Time to talk about security. 865 00:32:55,472 --> 00:32:56,807 MITCHELL: The tragedy of 866 00:32:56,840 --> 00:32:58,242 this recent pandemic teaches us 867 00:32:58,275 --> 00:33:01,112 that we're all pretty vulnerable. 868 00:33:01,145 --> 00:33:03,014 And without that herd immunity, 869 00:33:03,047 --> 00:33:05,182 without that community response, 870 00:33:05,215 --> 00:33:07,485 you can't just say, "I'm okay, 871 00:33:07,518 --> 00:33:10,788 and therefore I don't have to worry about this." 872 00:33:10,821 --> 00:33:13,224 This is the first time that I've ever heard 873 00:33:13,257 --> 00:33:16,027 someone compare data privacy 874 00:33:16,060 --> 00:33:19,797 to epidemiology and herd immunity. 875 00:33:19,830 --> 00:33:23,601 All you need is one person to make a mistake 876 00:33:23,634 --> 00:33:25,302 and it's game over. 877 00:33:25,335 --> 00:33:29,640 That's what happens to so many other corporations, businesses, 878 00:33:29,673 --> 00:33:31,709 even hospitals during a ransomware attack 879 00:33:31,742 --> 00:33:34,245 that'll freeze all machines and stop them from working 880 00:33:34,278 --> 00:33:36,547 until someone pays a bunch of hackers. 881 00:33:36,580 --> 00:33:39,050 My one error could compromise the security 882 00:33:39,083 --> 00:33:41,218 of my entire institution. 883 00:33:41,251 --> 00:33:42,486 MITCHELL: Human beings will make mistakes. 884 00:33:42,519 --> 00:33:45,156 Folks won't wash their hands sometimes, right? 885 00:33:45,189 --> 00:33:49,260 But we try to teach best practices to prevent the worst. 886 00:33:49,293 --> 00:33:50,728 Okay, Matt, you have my wheels spinning. 887 00:33:50,761 --> 00:33:53,431 I do not want to be patient zero 888 00:33:53,464 --> 00:33:56,267 in this, like, massive infectious data leak. 889 00:33:56,300 --> 00:33:58,636 What can I do to start pulling it back 890 00:33:58,669 --> 00:34:00,438 and better protecting my information? 891 00:34:00,471 --> 00:34:02,573 Well, I got something for that, okay? 892 00:34:02,606 --> 00:34:04,642 Oh, you have, like, a bag of tricks. 893 00:34:02,606 --> 00:34:04,642 I've got a bag. 894 00:34:04,675 --> 00:34:06,510 I thought you were just gonna say, like, change your password. 895 00:34:06,543 --> 00:34:08,446 We got to go all the way. 896 00:34:08,479 --> 00:34:10,114 This is a privacy screen. 897 00:34:10,147 --> 00:34:12,650 And this will keep people from being able 898 00:34:12,683 --> 00:34:14,085 to look over your shoulder. 899 00:34:14,118 --> 00:34:15,319 Shoulder surfers beware. 900 00:34:15,352 --> 00:34:16,487 Can't look through that. 901 00:34:16,520 --> 00:34:17,655 This is for like, using my computer 902 00:34:17,688 --> 00:34:19,223 in a public space, the airplane. 903 00:34:19,256 --> 00:34:21,392 Everywhere. 904 00:34:21,425 --> 00:34:23,160 This is a Faraday bag. 905 00:34:23,193 --> 00:34:24,728 You got to keep your phone in here. 906 00:34:24,761 --> 00:34:26,430 This blocks RF signals. 907 00:34:26,463 --> 00:34:27,765 It's basically aluminum foil... 908 00:34:26,463 --> 00:34:27,765 PATEL (voiceover): Yo, Matt? 909 00:34:27,798 --> 00:34:29,767 Can we slow this down a little bit? 910 00:34:29,800 --> 00:34:31,635 You can't get hacked when you're not attached to anything. 911 00:34:31,668 --> 00:34:34,138 Is this really necessary, a Faraday bag? 912 00:34:34,171 --> 00:34:37,141 PATEL (voiceover): Okay, this looks a little more complicated than I expected. 913 00:34:37,174 --> 00:34:39,343 I guess I just have to become Dr. 007. 914 00:34:39,376 --> 00:34:41,612 We also have a Wi-Fi pineapple. 915 00:34:41,645 --> 00:34:44,148 This is a portable access point. 916 00:34:44,181 --> 00:34:45,783 And we also could use it to detect 917 00:34:45,816 --> 00:34:48,152 and stop access points from going bad. 918 00:34:48,185 --> 00:34:50,354 PATEL (voiceover): Okay, Matt, now you've just gone rogue. 919 00:34:50,387 --> 00:34:52,356 MITCHELL: Let's say you have a hard drive 920 00:34:52,389 --> 00:34:54,258 with some important files from work in it. 921 00:34:54,291 --> 00:34:55,459 What happens if you lose it? 922 00:34:55,492 --> 00:34:56,794 Someone can plug that in and have access 923 00:34:56,827 --> 00:34:58,195 to all your stuff. 924 00:34:58,228 --> 00:35:00,064 Not if it's an encrypted hard drive. 925 00:35:00,097 --> 00:35:02,366 I understand-- 926 00:35:00,097 --> 00:35:02,366 There's more. 927 00:35:02,399 --> 00:35:04,135 How do you know that you're not being bugged? 928 00:35:04,168 --> 00:35:05,503 This is nuts. 929 00:35:05,536 --> 00:35:07,304 This is something I could use to find out 930 00:35:07,337 --> 00:35:10,341 if there is a audio bug in the room. 931 00:35:07,337 --> 00:35:10,341 (beeping) 932 00:35:10,374 --> 00:35:12,009 I can find Wi-Fi signals... 933 00:35:10,374 --> 00:35:12,009 (device beeps) 934 00:35:12,042 --> 00:35:13,678 Oops, something's here, right? 935 00:35:14,512 --> 00:35:17,648 PATEL (voiceover): Honestly, I thought being a spy would be more fun. 936 00:35:17,681 --> 00:35:20,351 But I'm starting to feel shaken, not stirred. 937 00:35:20,384 --> 00:35:23,220 How am I supposed to keep track of all this stuff? 938 00:35:23,253 --> 00:35:26,324 I'm no hacker genius like Matt. 939 00:35:27,158 --> 00:35:31,162 What if I just left all of this behind and just quit. 940 00:35:31,195 --> 00:35:33,397 Goodbye, digital world. 941 00:35:38,101 --> 00:35:43,141 (clock ticking) 942 00:35:46,376 --> 00:35:48,112 (yawning) 943 00:35:51,515 --> 00:35:52,616 Do you know if there's breaking news? 944 00:35:51,515 --> 00:35:52,616 (cat meows) 945 00:35:52,649 --> 00:35:53,684 Look in my eyes and tell me. 946 00:35:53,717 --> 00:35:55,119 What are we doing here? 947 00:35:55,152 --> 00:35:56,353 What are we doing? 948 00:35:56,386 --> 00:35:57,354 Like, I don't even know 949 00:35:57,387 --> 00:35:58,622 how many steps I've taken today. 950 00:35:58,655 --> 00:36:00,491 Because my step counter is not on my hand. 951 00:36:00,524 --> 00:36:03,360 I'm technically disconnected, this isn't cheating, 952 00:36:03,393 --> 00:36:05,462 but can someone tell me what the Suns score is? 953 00:36:05,495 --> 00:36:07,164 CREW MEMBER: Uh, down by 11 at the half. 954 00:36:07,197 --> 00:36:08,165 (groans) 955 00:36:08,198 --> 00:36:10,067 (cat purring) 956 00:36:10,100 --> 00:36:12,303 Oh, I am supposed to pick up my daughter. 957 00:36:12,336 --> 00:36:15,306 How long do I have to do this for? 958 00:36:16,106 --> 00:36:18,275 (voiceover): All right, maybe it's not that easy. 959 00:36:18,308 --> 00:36:19,777 But there's got to be some middle ground 960 00:36:19,810 --> 00:36:22,446 between Inspector Gadget and Fred Flintstone 961 00:36:22,479 --> 00:36:24,615 that's right for me. 962 00:36:24,648 --> 00:36:27,451 Instead of going completely off the grid, 963 00:36:27,484 --> 00:36:29,687 I'm checking back in with Eva 964 00:36:29,720 --> 00:36:32,089 for some more surveillance self-defense. 965 00:36:32,122 --> 00:36:37,428 And the best place to start is with the basics: passwords. 966 00:36:37,461 --> 00:36:39,463 I'll be honest, 967 00:36:39,496 --> 00:36:40,731 my current password 968 00:36:40,764 --> 00:36:41,799 is basically a combination 969 00:36:41,832 --> 00:36:44,501 of my first pet's name plus my birthday 970 00:36:44,534 --> 00:36:47,171 or a favorite video game or song. 971 00:36:47,204 --> 00:36:48,806 I don't think any hacker's really gonna guess that. 972 00:36:48,839 --> 00:36:52,142 But you're telling me that there is still a vulnerability there. 973 00:36:52,175 --> 00:36:54,078 Yes. 974 00:36:54,111 --> 00:36:55,679 Hackers can go find out information 975 00:36:55,712 --> 00:36:56,880 about you from data brokers, 976 00:36:56,913 --> 00:37:00,184 including, you know, the name of the street you grew up on 977 00:37:00,217 --> 00:37:03,220 or the city where you went to college. 978 00:37:03,253 --> 00:37:07,124 So you wouldn't want a password like the name of your pet. 979 00:37:07,157 --> 00:37:08,659 Or password123. 980 00:37:08,692 --> 00:37:13,197 Well, I did have a pet fish, and his name was Password123. 981 00:37:13,230 --> 00:37:14,765 So, I guess that kind of, like, 982 00:37:14,798 --> 00:37:17,334 hits both boxes and makes me more vulnerable. 983 00:37:17,367 --> 00:37:22,606 Let's start by, uh, creating some strong and unique passwords 984 00:37:22,639 --> 00:37:24,708 for all of your, uh, your different accounts. 985 00:37:24,741 --> 00:37:26,744 And that will make them much more hacker-proof. 986 00:37:26,777 --> 00:37:28,545 I'm all ears. 987 00:37:26,777 --> 00:37:28,545 Fantastic. 988 00:37:28,578 --> 00:37:34,051 Well, we're going to start by rolling these five dice. 989 00:37:35,352 --> 00:37:38,055 GALPERIN (voiceover): There are easy ways to create passwords 990 00:37:38,088 --> 00:37:40,491 that are long and strong 991 00:37:40,524 --> 00:37:43,027 and easy to remember that are not based on information 992 00:37:43,060 --> 00:37:46,196 that attackers can easily find about you. 993 00:37:46,229 --> 00:37:49,333 And the way that we do that is we use word lists and dice. 994 00:37:50,233 --> 00:37:54,038 The word list is essentially just a long list 995 00:37:54,071 --> 00:37:58,042 of dictionary words with numbers attached. 996 00:37:58,075 --> 00:38:00,010 So what we're going to do is we're going 997 00:38:00,043 --> 00:38:01,979 to write down the numbers on this dice. 998 00:38:02,012 --> 00:38:04,715 45263, my new lucky numbers. 999 00:38:02,012 --> 00:38:04,715 Okay. 1000 00:38:04,748 --> 00:38:07,618 And now we are going to look up 1001 00:38:07,651 --> 00:38:11,488 45263 in this book. 1002 00:38:11,521 --> 00:38:13,991 So there are words that correlate to the numbers 1003 00:38:14,024 --> 00:38:15,592 that I just randomly rolled. 1004 00:38:14,024 --> 00:38:15,592 Yes. 1005 00:38:15,625 --> 00:38:17,761 Okay. I want a cool word like "tiger." 1006 00:38:17,794 --> 00:38:20,431 The word is "presoak." 1007 00:38:20,464 --> 00:38:21,966 "Presoak?" 1008 00:38:20,464 --> 00:38:21,966 "Presoak." 1009 00:38:23,100 --> 00:38:27,304 34115. 1010 00:38:27,337 --> 00:38:28,572 "Henna." 1011 00:38:28,605 --> 00:38:30,240 Okay, I like this. 1012 00:38:30,273 --> 00:38:32,109 PATEL (voiceover): The idea behind this dice game 1013 00:38:32,142 --> 00:38:35,045 is that it's both random and long. 1014 00:38:35,078 --> 00:38:38,048 Hackers using fast, powerful computers 1015 00:38:38,081 --> 00:38:40,284 and sophisticated password-cracking software 1016 00:38:40,317 --> 00:38:43,620 are able to try many, many passwords a second. 1017 00:38:43,653 --> 00:38:45,789 A recent study by a security firm 1018 00:38:45,822 --> 00:38:48,525 showed that a seven-character password can be cracked 1019 00:38:48,558 --> 00:38:50,627 in just a few seconds. 1020 00:38:50,660 --> 00:38:52,196 But a 12-character password 1021 00:38:52,229 --> 00:38:54,031 with uppercase letters and symbols 1022 00:38:54,064 --> 00:38:56,433 is much more difficult to break. 1023 00:38:56,466 --> 00:38:58,035 Studies show it could take hackers 1024 00:38:58,068 --> 00:39:00,304 well over 100 years to crack. 1025 00:39:00,337 --> 00:39:02,072 That's safe. 1026 00:39:02,105 --> 00:39:05,075 But also more difficult to type or remember. 1027 00:39:05,108 --> 00:39:06,610 Eva's six-word random passphrase 1028 00:39:06,643 --> 00:39:09,747 is easier to remember than a random string of 12 characters 1029 00:39:09,780 --> 00:39:12,349 and practically impossible to break. 1030 00:39:12,382 --> 00:39:13,384 "Stinging." 1031 00:39:13,417 --> 00:39:14,618 "Ignition." 1032 00:39:17,087 --> 00:39:19,223 Six is "Clutch." 1033 00:39:17,087 --> 00:39:19,223 "Clutch," okay. 1034 00:39:19,256 --> 00:39:24,128 "Presoak Henna Stinging Ignition Clutch Handbrake." 1035 00:39:24,161 --> 00:39:25,195 (bell dings) 1036 00:39:24,161 --> 00:39:25,195 Fantastic. 1037 00:39:25,228 --> 00:39:26,397 Now you have a passphrase. 1038 00:39:26,430 --> 00:39:27,398 These six words. 1039 00:39:27,431 --> 00:39:29,433 It is long. It's unique. 1040 00:39:29,466 --> 00:39:31,168 It's difficult to guess. 1041 00:39:31,201 --> 00:39:32,736 And it's relatively easy to remember, 1042 00:39:32,769 --> 00:39:35,072 considering how long it is. 1043 00:39:35,105 --> 00:39:37,174 It is a very good way of creating random passwords, 1044 00:39:37,207 --> 00:39:40,644 but a lot of password managers will automatically 1045 00:39:40,677 --> 00:39:42,479 do this for you. 1046 00:39:42,512 --> 00:39:45,516 PATEL (voiceover): Once you have a passphrase, you can use this 1047 00:39:45,549 --> 00:39:48,719 to unlock a password manager that generates 1048 00:39:48,752 --> 00:39:53,023 strong random passwords and stores them securely. 1049 00:39:53,056 --> 00:39:57,161 Now I have this beautiful random password or passphrase, 1050 00:39:57,194 --> 00:39:59,430 but what happens if someone steals this? 1051 00:39:59,463 --> 00:40:01,632 Is it just game over, efforts are gone? 1052 00:40:01,665 --> 00:40:02,766 No, it is not. 1053 00:40:02,800 --> 00:40:06,036 Uh, that leads us to the next step on your surveillance 1054 00:40:06,069 --> 00:40:09,373 self-defense journey, and that is two-factor authentication. 1055 00:40:10,374 --> 00:40:13,744 PATEL (voiceover): This may sound like a hacker ninja term, 1056 00:40:13,777 --> 00:40:16,046 but it's just an added layer of security, 1057 00:40:16,079 --> 00:40:20,184 requiring an additional method of confirming your identity. 1058 00:40:20,217 --> 00:40:22,386 Most of the time, it's just a simple text message. 1059 00:40:22,419 --> 00:40:23,587 GALPERIN: Because it requires 1060 00:40:23,620 --> 00:40:25,189 that you have two things 1061 00:40:25,222 --> 00:40:26,557 in order to log into your account. 1062 00:40:26,590 --> 00:40:30,160 You will need both your password and also this code, 1063 00:40:30,193 --> 00:40:33,764 so the site will send you a text message. 1064 00:40:33,797 --> 00:40:36,567 There is also an authenticator app. 1065 00:40:36,600 --> 00:40:41,138 The site will ask you to take a photo of and then go to 1066 00:40:41,171 --> 00:40:43,540 the site in a QR code. 1067 00:40:43,573 --> 00:40:46,143 The best way to be a security superhero 1068 00:40:46,176 --> 00:40:49,079 is to find the stuff that works for you 1069 00:40:49,112 --> 00:40:51,215 and implement it as sort of smoothly 1070 00:40:51,248 --> 00:40:53,451 and seamlessly as you can. 1071 00:40:54,518 --> 00:40:56,787 PATEL (voiceover): These data self-defense tweaks are great 1072 00:40:56,820 --> 00:40:58,822 for me and my own data. 1073 00:40:58,855 --> 00:41:01,058 But what about everyone else? 1074 00:41:01,091 --> 00:41:05,028 I'm wondering, is there a way for all of us to share data 1075 00:41:05,061 --> 00:41:07,164 and get all the sweet benefits, 1076 00:41:07,197 --> 00:41:08,699 without sacrificing privacy and security? 1077 00:41:11,067 --> 00:41:12,536 At M.I.T.'s Media Lab, 1078 00:41:12,569 --> 00:41:15,239 I'm meeting up with Ramesh Raskar, 1079 00:41:15,272 --> 00:41:17,808 who is working on a way to access the benefits 1080 00:41:17,841 --> 00:41:19,476 of personal health data-- 1081 00:41:19,509 --> 00:41:21,478 finally, a topic I understand-- 1082 00:41:21,511 --> 00:41:24,248 without compromising our private information. 1083 00:41:25,382 --> 00:41:27,384 At Ramesh's Camera Culture Lab, 1084 00:41:27,417 --> 00:41:29,453 they're building some data collecting tools 1085 00:41:29,486 --> 00:41:32,189 that seem straight out of a science fiction movie. 1086 00:41:32,222 --> 00:41:35,292 PATEL: Love when a sign says "Danger: Laser." 1087 00:41:35,325 --> 00:41:37,227 You know important things are happening in here. 1088 00:41:37,260 --> 00:41:41,732 (voiceover): They've got cameras that can literally see around corners. 1089 00:41:41,765 --> 00:41:43,534 PATEL: Get out! 1090 00:41:41,765 --> 00:41:43,534 (both laughing) 1091 00:41:43,567 --> 00:41:46,036 RASKAR: We are not violating the laws of physics. 1092 00:41:46,903 --> 00:41:50,207 PATEL (voiceover): And cameras that can see inside our own bodies. 1093 00:41:50,240 --> 00:41:53,110 That's about as personal as it gets. 1094 00:41:53,143 --> 00:41:57,548 For Ramesh, protecting patient privacy is paramount. 1095 00:41:57,581 --> 00:41:59,850 But he's found a drawback in how we do that. 1096 00:41:59,883 --> 00:42:02,185 Since data is locked up for privacy, 1097 00:42:02,218 --> 00:42:06,056 advancement in medical science is not as fast as it could be. 1098 00:42:06,089 --> 00:42:09,393 Because, think about it, access to tons of personal health data 1099 00:42:09,426 --> 00:42:12,162 could help researchers make major medical breakthroughs. 1100 00:42:12,195 --> 00:42:16,099 But today, researchers have to ask for your consent 1101 00:42:16,132 --> 00:42:19,069 to peek at your data in order to learn from it. 1102 00:42:19,102 --> 00:42:20,504 RASKAR: When we talk about consent, 1103 00:42:20,537 --> 00:42:22,806 someone's still peeking into your data. 1104 00:42:22,839 --> 00:42:25,375 A no-peek privacy, on the other hand, 1105 00:42:25,408 --> 00:42:27,111 is where nobody can peek at your data. 1106 00:42:27,911 --> 00:42:29,580 PATEL (voiceover): No-peek privacy? 1107 00:42:29,613 --> 00:42:31,415 But how could researchers learn anything? 1108 00:42:31,448 --> 00:42:33,183 RASKAR: There are many ways 1109 00:42:33,216 --> 00:42:35,452 to create no-peek privacy. 1110 00:42:35,485 --> 00:42:39,290 First one is the notion of smashing information. 1111 00:42:42,726 --> 00:42:45,162 PATEL (voiceover): No, not literally smashing your phone. 1112 00:42:45,195 --> 00:42:47,131 But I'm not gonna lie... 1113 00:42:48,698 --> 00:42:50,801 ...that was really fun. 1114 00:42:50,834 --> 00:42:53,337 Smashing is basically the idea of taking raw data 1115 00:42:53,370 --> 00:42:55,673 and smashing it into just the wisdom. 1116 00:42:56,740 --> 00:42:58,842 PATEL (voiceover): According to Ramesh, smashing data 1117 00:42:58,875 --> 00:43:00,243 is simply the process 1118 00:43:00,276 --> 00:43:02,446 of extracting the useful information, 1119 00:43:02,479 --> 00:43:04,147 which he calls the "wisdom," 1120 00:43:04,180 --> 00:43:06,383 while obscuring the private data. 1121 00:43:06,416 --> 00:43:10,153 In other words, a collection of private health records 1122 00:43:10,186 --> 00:43:12,055 contains two kinds of data. 1123 00:43:12,088 --> 00:43:14,625 One kind is the personal data-- 1124 00:43:14,658 --> 00:43:17,160 the names, conditions, and histories, 1125 00:43:17,193 --> 00:43:19,730 the stuff we absolutely want to protect. 1126 00:43:19,763 --> 00:43:25,068 But collectively, the records may contain valuable information 1127 00:43:25,101 --> 00:43:26,103 about patterns in health care. 1128 00:43:26,136 --> 00:43:28,472 The wisdom. 1129 00:43:28,505 --> 00:43:30,674 I'm thinking about examples in health care, 1130 00:43:30,707 --> 00:43:34,244 and the individual data, the patient data 1131 00:43:34,277 --> 00:43:37,080 is protected, and you can't reverse engineer it. 1132 00:43:37,113 --> 00:43:39,650 Let's take a concrete example of COVID. 1133 00:43:41,184 --> 00:43:43,620 Imagine during the early days of the pandemic, 1134 00:43:43,653 --> 00:43:45,222 we could have sent medical experts 1135 00:43:45,255 --> 00:43:48,425 from here in Boston to China, to Korea, to Italy, 1136 00:43:48,458 --> 00:43:51,294 and embedded them in those hospitals to understand 1137 00:43:51,327 --> 00:43:54,665 what COVID pneumonia looks like on a chest X-ray. 1138 00:43:54,698 --> 00:43:56,400 And they could have come back to Boston, 1139 00:43:56,433 --> 00:43:57,834 all those medical experts, 1140 00:43:57,867 --> 00:44:01,705 and said, "Hey, together, we can figure out what this is." 1141 00:44:02,605 --> 00:44:06,209 PATEL (voiceover): So, the experts would return back with just the wisdom, 1142 00:44:06,242 --> 00:44:07,778 an understanding of COVID 1143 00:44:07,811 --> 00:44:10,614 derived from being exposed to large data sets. 1144 00:44:10,647 --> 00:44:14,017 But they wouldn't come back with specific patient info. 1145 00:44:14,050 --> 00:44:18,088 None of the raw, sensitive, and private data. 1146 00:44:18,121 --> 00:44:20,057 But of course, that would require 1147 00:44:20,090 --> 00:44:22,626 initially sharing patient data; 1148 00:44:22,659 --> 00:44:25,095 a non-starter. 1149 00:44:25,128 --> 00:44:27,097 Because of privacy, because of regulations, 1150 00:44:27,130 --> 00:44:29,233 because of national security issues, they couldn't. 1151 00:44:30,400 --> 00:44:33,370 PATEL (voiceover): This is where A.I., Artificial Intelligence, 1152 00:44:33,403 --> 00:44:34,604 comes in. 1153 00:44:34,637 --> 00:44:37,040 Instead of sending experts to each hospital, 1154 00:44:37,073 --> 00:44:40,377 Ramesh is working on a way to send A.I. to learn instead. 1155 00:44:41,177 --> 00:44:44,114 An A.I. model could be trained on patients' lung X-rays 1156 00:44:44,147 --> 00:44:46,216 to learn what signs of COVID look like. 1157 00:44:46,249 --> 00:44:50,120 The private health data would never be copied 1158 00:44:50,153 --> 00:44:52,622 and would never leave the hospital or the patient's file. 1159 00:44:52,655 --> 00:44:55,325 The A.I. would only transmit its conclusions, 1160 00:44:55,358 --> 00:44:57,828 the wisdom, the smashed data. 1161 00:44:57,861 --> 00:44:59,262 RASKAR: It's not enough to just 1162 00:44:59,295 --> 00:45:02,099 remove the name from the chest X-ray, 1163 00:45:02,132 --> 00:45:04,034 but make sure that you don't send 1164 00:45:04,067 --> 00:45:06,003 any of the pixels of the chest X-ray at all. 1165 00:45:06,937 --> 00:45:09,773 PATEL (voiceover): The A.I. can learn patterns and gain knowledge 1166 00:45:09,806 --> 00:45:12,109 without having to keep hold of everyone's data. 1167 00:45:12,142 --> 00:45:15,112 So the "wisdom" from one hospital 1168 00:45:15,145 --> 00:45:17,614 can be combined with the "wisdom" of others. 1169 00:45:17,647 --> 00:45:22,219 RASKAR: Achieving privacy and benefits of the data simultaneously, 1170 00:45:22,252 --> 00:45:25,422 it's like having a cake and eating it, too; it's available. 1171 00:45:25,455 --> 00:45:28,158 And it's just a matter of convincing large companies 1172 00:45:28,191 --> 00:45:30,494 to play along those rules. 1173 00:45:30,527 --> 00:45:34,297 PATEL: Smashed data is one way we can learn to stop worrying 1174 00:45:34,330 --> 00:45:37,033 and love sharing our personal data. 1175 00:45:37,066 --> 00:45:39,803 But every corporate network would have to agree 1176 00:45:39,836 --> 00:45:42,639 to smash our raw data. 1177 00:45:43,840 --> 00:45:46,042 I'm not convinced we should wait around 1178 00:45:46,075 --> 00:45:48,378 for big tech companies to do this. 1179 00:45:49,178 --> 00:45:50,781 HILL: The big technology companies, 1180 00:45:50,814 --> 00:45:53,750 they have built the infrastructure 1181 00:45:53,783 --> 00:45:54,784 of the whole internet. 1182 00:45:54,818 --> 00:45:57,287 You're not just interacting with these companies 1183 00:45:57,320 --> 00:45:59,022 when you know you're interacting with them. 1184 00:46:00,256 --> 00:46:02,092 PATEL: Even if it seems like you're on 1185 00:46:02,125 --> 00:46:05,762 a totally independent website, big tech still sees you. 1186 00:46:05,795 --> 00:46:08,999 For example, tons of websites, 1187 00:46:09,032 --> 00:46:12,135 like some of the ones owned by NASA, Pfizer, BMW, 1188 00:46:12,168 --> 00:46:15,372 even PBS, use Amazon Web Services, 1189 00:46:15,405 --> 00:46:19,543 which means Amazon gets some data when you visit them. 1190 00:46:19,576 --> 00:46:22,145 Or when you visit any app on your iPhone, 1191 00:46:22,178 --> 00:46:24,014 Apple knows. 1192 00:46:24,047 --> 00:46:26,149 Also, every time you've been to a webpage 1193 00:46:26,182 --> 00:46:28,385 that has a Facebook "like" button, 1194 00:46:28,418 --> 00:46:31,521 Facebook gets to gobble up your personal data. 1195 00:46:31,554 --> 00:46:33,089 KAHLE: So it may seem 1196 00:46:33,122 --> 00:46:34,324 like the web is decentralized 1197 00:46:34,357 --> 00:46:35,759 because it comes from many different places. 1198 00:46:35,792 --> 00:46:37,160 But in fact, 1199 00:46:37,193 --> 00:46:39,429 there's centralized points of control. 1200 00:46:40,229 --> 00:46:43,600 CHOWDHURY: Right now, for example, when you are in a social media app, 1201 00:46:43,633 --> 00:46:44,768 you're sort of locked in, right? 1202 00:46:44,801 --> 00:46:46,436 All your information is on there. 1203 00:46:46,469 --> 00:46:48,138 It's hard to leave a social media app 1204 00:46:48,171 --> 00:46:49,239 because you're like, "All my friends are there, 1205 00:46:49,272 --> 00:46:50,640 all my photos are there. 1206 00:46:50,673 --> 00:46:52,342 "If I move to another app, 1207 00:46:52,375 --> 00:46:53,710 I have to rebuild that community." 1208 00:46:54,644 --> 00:46:57,814 GALPERIN: Those social media websites are controlled 1209 00:46:57,847 --> 00:46:59,516 by a very small number of companies. 1210 00:46:59,549 --> 00:47:02,052 And the rules about using those websites, 1211 00:47:02,085 --> 00:47:06,456 who has access to them and what kind of behavior is acceptable 1212 00:47:06,489 --> 00:47:10,027 on them, are set by the websites themselves. 1213 00:47:11,161 --> 00:47:16,166 PATEL: This centralized data monopoly, how do we start to dismantle it? 1214 00:47:16,199 --> 00:47:18,468 That's exactly what proponents of an idea 1215 00:47:18,501 --> 00:47:22,272 called the decentralized web want to do. 1216 00:47:23,139 --> 00:47:26,142 GALPERIN: The decentralized web is sort of our antidote, 1217 00:47:26,175 --> 00:47:30,080 the antithesis of the web as we now think of it. 1218 00:47:30,113 --> 00:47:32,449 CHRISTINE LEMMER-WEBBER: The decentralized web can be seen in contrast 1219 00:47:32,482 --> 00:47:34,618 to the centralized web, of course. 1220 00:47:34,651 --> 00:47:37,354 Instead of what has become, 1221 00:47:37,387 --> 00:47:41,157 on the internet, of a few big players kind of controlling 1222 00:47:41,190 --> 00:47:42,659 a lot of the web and the internet space, 1223 00:47:42,692 --> 00:47:44,661 we're really kind of rolling things back 1224 00:47:44,694 --> 00:47:46,463 to kind of what the vision of the internet was. 1225 00:47:47,464 --> 00:47:50,066 PATEL: I'm wondering what a decentralized web 1226 00:47:50,099 --> 00:47:52,235 would look and feel like? 1227 00:47:52,268 --> 00:47:55,672 So I'm meeting up with coder Christine Lemmer-Webber, 1228 00:47:55,705 --> 00:47:57,440 who is working on writing the standards and rules 1229 00:47:57,473 --> 00:48:01,578 for how social media could work on a decentralized web. 1230 00:48:01,611 --> 00:48:03,246 LEMMER-WEBBER: Most people are familiar 1231 00:48:03,279 --> 00:48:05,248 with social networks: you know, they've used, 1232 00:48:05,281 --> 00:48:07,150 you know, X-slash-Twitter; 1233 00:48:07,183 --> 00:48:09,219 they've used Facebook; they've used Instagram. 1234 00:48:09,252 --> 00:48:11,988 The decentralized social web is 1235 00:48:12,021 --> 00:48:14,758 like that, but no one company, 1236 00:48:14,791 --> 00:48:17,127 no one gatekeeper controls the thing. 1237 00:48:17,160 --> 00:48:18,995 We want to be able to have 1238 00:48:19,028 --> 00:48:20,764 all of our different social media sites, 1239 00:48:20,797 --> 00:48:23,199 all of our different online communication tools 1240 00:48:23,232 --> 00:48:25,302 be able to talk to each other. 1241 00:48:25,335 --> 00:48:26,536 DOCTOROW: A decentralized web 1242 00:48:26,569 --> 00:48:29,105 is one that is focused on 1243 00:48:29,138 --> 00:48:31,074 the self-determination of users. 1244 00:48:31,107 --> 00:48:32,242 You're not locked in. 1245 00:48:33,476 --> 00:48:36,179 So you find a service, and you like it. 1246 00:48:36,212 --> 00:48:37,480 (duck quacks) 1247 00:48:37,513 --> 00:48:39,283 And then you and they start to part ways. 1248 00:48:40,083 --> 00:48:43,753 The art you made, the stories you told are there. 1249 00:48:43,786 --> 00:48:47,057 In a decentralized web, you go somewhere else. 1250 00:48:47,090 --> 00:48:49,726 You go somewhere else, and you don't lose any of that. 1251 00:48:53,629 --> 00:48:57,100 PATEL (voiceover): But imagine, instead of having one Facebook-type company, 1252 00:48:57,133 --> 00:49:00,036 we each had our own data live on our own devices, 1253 00:49:00,069 --> 00:49:02,639 and it was easy to join or merge with others, 1254 00:49:02,672 --> 00:49:04,374 or disconnect from them. 1255 00:49:04,407 --> 00:49:06,576 Leaving one group and joining another 1256 00:49:06,609 --> 00:49:09,112 wouldn't mean rebuilding everything from scratch 1257 00:49:09,145 --> 00:49:12,015 because your data moves with you. 1258 00:49:13,116 --> 00:49:14,751 It sounds like a tech fantasy. 1259 00:49:14,784 --> 00:49:17,020 But it's actually something we've already proven 1260 00:49:17,053 --> 00:49:18,321 works online. 1261 00:49:18,354 --> 00:49:21,758 Consider something you may use every day, 1262 00:49:21,791 --> 00:49:24,995 or if you're like me, every minute: email. 1263 00:49:25,028 --> 00:49:26,763 LEMMER-WEBBER: So what a lot of people don't realize 1264 00:49:26,796 --> 00:49:29,132 is that they use decentralized networks every day. 1265 00:49:29,165 --> 00:49:30,734 It doesn't matter if somebody's on Gmail, 1266 00:49:30,767 --> 00:49:32,268 or if they're on Hotmail, 1267 00:49:32,301 --> 00:49:34,004 they're on their university email. 1268 00:49:34,037 --> 00:49:35,238 They don't even have to think about it. 1269 00:49:35,271 --> 00:49:37,040 They type an email to their friend, 1270 00:49:37,073 --> 00:49:39,175 and they send it off, and it gets there, right? 1271 00:49:39,208 --> 00:49:41,111 At the heart of it, that's kind of the basics 1272 00:49:41,144 --> 00:49:42,179 of what we're doing. 1273 00:49:43,480 --> 00:49:47,083 PATEL: In other words, you can get an email sent from Hotmail 1274 00:49:47,116 --> 00:49:48,685 even if you have a Gmail account. 1275 00:49:48,718 --> 00:49:52,389 Or you can create your own email server, for that matter. 1276 00:49:52,422 --> 00:49:55,492 It doesn't matter what email service you use 1277 00:49:55,525 --> 00:49:58,161 because the protocol, the rules, are written 1278 00:49:58,194 --> 00:50:01,631 to allow the email servers to talk to one another. 1279 00:50:02,465 --> 00:50:04,667 LEMMER-WEBBER: That's because there's a shared protocol that says, 1280 00:50:04,700 --> 00:50:07,270 here's how we get the messages from place to place. 1281 00:50:07,303 --> 00:50:09,740 Social networks could just work like email. 1282 00:50:10,540 --> 00:50:12,809 PATEL: And in fact, there are plenty of decentralized projects 1283 00:50:12,842 --> 00:50:14,644 out there like Mastodon 1284 00:50:14,677 --> 00:50:15,745 and Blue Sky 1285 00:50:15,778 --> 00:50:17,647 putting the user's profile and data 1286 00:50:17,680 --> 00:50:19,049 back into the users' hands. 1287 00:50:19,949 --> 00:50:21,618 LEMMER-WEBBER: In the systems we're moving towards 1288 00:50:21,651 --> 00:50:23,319 that will be much more the case 1289 00:50:23,352 --> 00:50:25,588 where private communication is much more private. 1290 00:50:25,621 --> 00:50:28,625 They're, by default, secure in that type of way. 1291 00:50:28,658 --> 00:50:31,661 We're building new foundations 1292 00:50:31,694 --> 00:50:34,130 for the internet that allow for healthier, 1293 00:50:34,163 --> 00:50:38,368 safer, more decentralized systems, gatekeeper-free. 1294 00:50:38,401 --> 00:50:41,405 That's the vision and the future we're trying to build. 1295 00:50:42,839 --> 00:50:46,342 PATEL: No doubt, there are secrets in your data. 1296 00:50:46,375 --> 00:50:49,679 NOBLE: Everything we touch is increasingly datafied, 1297 00:50:49,712 --> 00:50:51,848 every dimension of our lives. 1298 00:50:51,881 --> 00:50:55,185 CHOWDHURY: All of this data goes into feed algorithms. 1299 00:50:55,218 --> 00:50:57,654 And algorithms make predictions 1300 00:50:57,687 --> 00:50:59,122 about how long you will live, 1301 00:50:59,155 --> 00:51:01,224 or your health, or your lifestyle. 1302 00:51:02,058 --> 00:51:04,160 PATEL (voiceover): And while I learned how to protect 1303 00:51:04,193 --> 00:51:06,229 my personal privacy and security, 1304 00:51:06,262 --> 00:51:09,065 there's only so much I can do myself. 1305 00:51:09,098 --> 00:51:10,467 HILL: There are things that individuals 1306 00:51:10,500 --> 00:51:12,402 can do to protect their privacy. 1307 00:51:12,435 --> 00:51:14,204 Ultimately, in order to 1308 00:51:14,237 --> 00:51:18,175 avoid a huge crisis, it requires systemic change. 1309 00:51:18,875 --> 00:51:23,046 GALPERIN: There are limits to what we can do as individuals. 1310 00:51:23,079 --> 00:51:25,281 There are also things that need to be addressed 1311 00:51:25,314 --> 00:51:27,650 through regulation, through litigation, 1312 00:51:27,683 --> 00:51:32,288 and through legislation in order to make all of us safer. 1313 00:51:32,321 --> 00:51:35,525 PATEL: It's comforting to know there are techies out there 1314 00:51:35,558 --> 00:51:38,428 trying to protect us and our data, 1315 00:51:38,461 --> 00:51:41,064 designing new ways to enjoy the fun and convenience 1316 00:51:41,097 --> 00:51:44,300 of the digital world without being exploited. 1317 00:51:44,333 --> 00:51:48,104 KAHLE: New technologies, new games can proliferate 1318 00:51:48,137 --> 00:51:50,206 without centralized points of control. 1319 00:51:50,239 --> 00:51:53,176 That's the excitement of the decentralized web. 1320 00:51:53,209 --> 00:51:56,546 LEMMER-WEBBER: I can't wait for people to see this vision 1321 00:51:56,579 --> 00:52:00,016 we're building for collaborative, more consensual, 1322 00:52:00,049 --> 00:52:01,684 decentralized social networks. 1323 00:52:01,717 --> 00:52:04,621 That's going to be really exciting. 1324 00:52:05,421 --> 00:52:07,657 PATEL: The future we're building might not look too different 1325 00:52:07,690 --> 00:52:10,493 from the internet of today. 1326 00:52:10,526 --> 00:52:13,062 But it could be much more private and secure, 1327 00:52:13,095 --> 00:52:16,199 if we get it right. 1328 00:52:16,232 --> 00:52:19,169 DOCTOROW: This is about how technological self-determination 1329 00:52:19,202 --> 00:52:21,437 and regulation work together 1330 00:52:21,470 --> 00:52:25,041 to make a world that is more safe for human habitation. 1331 00:52:37,853 --> 00:52:41,124 ♪ ♪ 1332 00:52:41,857 --> 00:52:49,399 ♪ ♪ 1333 00:52:53,236 --> 00:53:00,977 ♪ ♪ 1334 00:53:04,614 --> 00:53:12,155 ♪ ♪ 1335 00:53:13,789 --> 00:53:21,331 ♪ ♪ 1336 00:53:23,165 --> 00:53:30,507 ♪ ♪ 95747

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