1 00:00:00,480 --> 00:00:03,360 Speaker 1: Hey, everyone is Zaki. Today we're re airing one of 2 00:00:03,360 --> 00:00:06,880 Speaker 1: my favorite episodes from last year. It's about a woman 3 00:00:06,920 --> 00:00:10,119 Speaker 1: called c. C. Moore who's helping the police self homicide 4 00:00:10,119 --> 00:00:15,159 Speaker 1: cases using these databases of consumer DNA test results. A 5 00:00:15,240 --> 00:00:17,760 Speaker 1: lot has happened since then, so keep listening till the end, 6 00:00:18,079 --> 00:00:20,760 Speaker 1: when reporter Christen Brown will update us on the recent 7 00:00:20,800 --> 00:00:25,520 Speaker 1: developments and warning that the story includes some graphic descriptions 8 00:00:25,560 --> 00:00:37,000 Speaker 1: of a crime scene. Okay, here's the episode. In the 9 00:00:37,040 --> 00:00:41,160 Speaker 1: fall of seven, Tanya van Kileenberg and j Cook took 10 00:00:41,159 --> 00:00:44,440 Speaker 1: a ferry from their home in British Columbia to Washington State. 11 00:00:44,880 --> 00:00:47,000 Speaker 1: They were planning to run an errand the next morning 12 00:00:47,040 --> 00:00:52,159 Speaker 1: for Jay's father. A few days later, Tanya's body was 13 00:00:52,200 --> 00:00:55,440 Speaker 1: found in a ditch seventy miles north of Seattle. She's 14 00:00:55,480 --> 00:00:58,160 Speaker 1: been raped with her hands bound behind her, and there 15 00:00:58,200 --> 00:01:02,360 Speaker 1: was a bullet your head. Two days later, hunters found 16 00:01:02,440 --> 00:01:05,080 Speaker 1: j under a bridge one county over. He had been 17 00:01:05,120 --> 00:01:07,840 Speaker 1: strangled with a dog collar. A pack of cigarettes was 18 00:01:07,840 --> 00:01:12,520 Speaker 1: stuffed in his mouth. Police had a theory. They suspected 19 00:01:12,560 --> 00:01:14,600 Speaker 1: the couple had met the killer on the ferry and 20 00:01:14,680 --> 00:01:17,959 Speaker 1: offered him a ride, but the leads ran out and 21 00:01:18,000 --> 00:01:24,039 Speaker 1: the case went cold until a few months ago. Good morning, 22 00:01:24,040 --> 00:01:26,960 Speaker 1: and thank you all for being here. Yesterday we took 23 00:01:26,959 --> 00:01:29,840 Speaker 1: into custody of fifty five year old sea technic who 24 00:01:29,880 --> 00:01:33,680 Speaker 1: was suspected of the murders of jacob In Tanya and 25 00:01:33,840 --> 00:01:39,240 Speaker 1: Kylie Burke. William Earld Tabot the second has been booked 26 00:01:39,240 --> 00:01:42,479 Speaker 1: into Snowman County Jail on one count of first degree 27 00:01:42,560 --> 00:01:49,880 Speaker 1: murder on a war. Thirty one years after the murder, 28 00:01:50,000 --> 00:01:53,800 Speaker 1: police finally arrested a suspect. A woman named Cecy Moore 29 00:01:53,920 --> 00:01:57,440 Speaker 1: helped crack the case using a new and controversial technology. 30 00:01:58,040 --> 00:02:00,680 Speaker 1: At the time, CECI was known for solving the mysteries 31 00:02:00,680 --> 00:02:16,280 Speaker 1: of people's family histories. Today, c s hunt serial killers. Hi, 32 00:02:16,440 --> 00:02:19,959 Speaker 1: I'm Pia Gadkari and I'm Kristin Brown. And this week 33 00:02:20,000 --> 00:02:25,040 Speaker 1: on Decrypted, we're exploring the unintended consequences of consumer DNA tests. 34 00:02:26,120 --> 00:02:29,639 Speaker 1: These services are booming, with millions of people sending their 35 00:02:29,680 --> 00:02:33,800 Speaker 1: spit into companies like Ancestry and three met. They promised 36 00:02:33,800 --> 00:02:36,959 Speaker 1: to unite people with long lost family members, detect risk 37 00:02:37,000 --> 00:02:41,919 Speaker 1: of disease, and even suggests personalized dieting regimens, but critics 38 00:02:41,960 --> 00:02:44,160 Speaker 1: fear that our DNA could come to be used in 39 00:02:44,200 --> 00:02:48,040 Speaker 1: ways that would compromise our privacy and even potentially land 40 00:02:48,120 --> 00:03:01,200 Speaker 1: someone we're related to in jail. Stay with us, Okay. 41 00:03:02,000 --> 00:03:05,480 Speaker 1: It was a classically cold and gray Pacific Northwest day 42 00:03:05,520 --> 00:03:08,160 Speaker 1: when I picked CC More up at our hotel about 43 00:03:08,200 --> 00:03:12,280 Speaker 1: an hour and a half outside Seattle. Hey, do you 44 00:03:12,320 --> 00:03:16,440 Speaker 1: want to put that in the trunk? Yeah? There were 45 00:03:16,440 --> 00:03:18,519 Speaker 1: just a few miles from More the murder of Tanya 46 00:03:18,600 --> 00:03:22,280 Speaker 1: van Kilemberg and Jay Cook took place. So I was 47 00:03:22,360 --> 00:03:25,720 Speaker 1: just gonna say, I was just realizing this morning that 48 00:03:25,760 --> 00:03:28,080 Speaker 1: this We're in the county right now where you solved 49 00:03:28,120 --> 00:03:33,320 Speaker 1: your first case, right are we in Snahomas Cool? I 50 00:03:33,320 --> 00:03:36,080 Speaker 1: saw a sign that said this way, and I was 51 00:03:36,080 --> 00:03:38,960 Speaker 1: was going to ask somebody. Yeah, I realized Cecy was 52 00:03:39,000 --> 00:03:41,520 Speaker 1: here in rural Washington state to do what she has 53 00:03:41,520 --> 00:03:45,200 Speaker 1: done for years, help people piece together their family histories. 54 00:03:45,640 --> 00:03:49,560 Speaker 1: She was speaking at the annual Northwest Genealogical Conference. The 55 00:03:49,640 --> 00:03:52,320 Speaker 1: day before, I had watched her give a very technical 56 00:03:52,360 --> 00:03:56,160 Speaker 1: talk about how to triangulate DNA relatives to fill stubborn 57 00:03:56,200 --> 00:04:00,480 Speaker 1: gaps and genealogies. Afterward, about two dozen people rushed the 58 00:04:00,480 --> 00:04:04,040 Speaker 1: stage to talk to her. One person, apparently a distant cousin, 59 00:04:04,440 --> 00:04:07,440 Speaker 1: even asked her to pose for a picture. In this world, 60 00:04:07,600 --> 00:04:10,080 Speaker 1: Cecy Moore is a star, but she fell into it 61 00:04:10,120 --> 00:04:13,400 Speaker 1: by accident because until about twenty years ago, Cecy was 62 00:04:13,440 --> 00:04:16,360 Speaker 1: an actress. Once she told me she had a gig 63 00:04:16,400 --> 00:04:18,599 Speaker 1: where she had to pretend to be a barbeam. She 64 00:04:18,680 --> 00:04:21,080 Speaker 1: had come to our copy date joining a suitcase with 65 00:04:21,279 --> 00:04:24,240 Speaker 1: multiple outfit options for the big banquet keynote she was 66 00:04:24,279 --> 00:04:27,600 Speaker 1: giving later at the local country club. Because it wasn't 67 00:04:27,640 --> 00:04:33,239 Speaker 1: acting that made CC famous, it was genealogy. About twenty 68 00:04:33,360 --> 00:04:36,760 Speaker 1: years ago, my niece was getting married and I was 69 00:04:36,800 --> 00:04:39,240 Speaker 1: trying to think of a good wedding gift, and I thought, oh, 70 00:04:39,320 --> 00:04:41,880 Speaker 1: a family tree would be a cool wedding gift. I 71 00:04:41,920 --> 00:04:44,520 Speaker 1: think I'll try to put one together for her, and 72 00:04:44,680 --> 00:04:47,839 Speaker 1: got online and found ancestry dot com and started trying 73 00:04:47,920 --> 00:04:55,360 Speaker 1: to figure that out and became obsessed with in genealogy. 74 00:04:55,560 --> 00:04:58,840 Speaker 1: Genealogists are like detectives, but for the family tree, they 75 00:04:58,920 --> 00:05:02,200 Speaker 1: used things like Mary Dge records and obituaries to piece 76 00:05:02,240 --> 00:05:05,640 Speaker 1: together how people are related, and these days some of them, 77 00:05:05,680 --> 00:05:09,920 Speaker 1: like Ceci, also used DNA. Cecy made her mark using 78 00:05:10,000 --> 00:05:13,240 Speaker 1: DNA to crack tough to solve mysteries like tracking down 79 00:05:13,240 --> 00:05:17,520 Speaker 1: the birth parents of adopted children. Then Ceci's life took 80 00:05:17,520 --> 00:05:21,240 Speaker 1: a turn. In April, police arrested a suspect in the 81 00:05:21,400 --> 00:05:25,080 Speaker 1: long cold case of the Golden State Killer, a notorious 82 00:05:25,120 --> 00:05:29,440 Speaker 1: serial killer who terrorized California in the nineteen seventies and eighties. 83 00:05:30,839 --> 00:05:35,159 Speaker 1: Huge break in a cold case terrorizing California for decades, 84 00:05:35,200 --> 00:05:38,640 Speaker 1: police say they now have a Golden State Killer in custody. 85 00:05:38,839 --> 00:05:42,080 Speaker 1: Joseph de'angelo is facing new charges this morning, four counts 86 00:05:42,120 --> 00:05:46,080 Speaker 1: of murder in Santa Barbara, twelve murder charges now in all. 87 00:05:46,920 --> 00:05:49,599 Speaker 1: Cecie was gearing up for attack at the genetic testing 88 00:05:49,640 --> 00:05:52,520 Speaker 1: company twenty three and me when news of the arrest happened. 89 00:05:52,960 --> 00:05:55,880 Speaker 1: I woke up in a hotel room in Mountain View 90 00:05:56,360 --> 00:05:59,760 Speaker 1: and saw the headline that the Golden State Killer had 91 00:05:59,760 --> 00:06:04,240 Speaker 1: been rested, and I knew immediately that it was through 92 00:06:04,440 --> 00:06:08,280 Speaker 1: genetic genealogy techniques. It didn't come out immediately, but I 93 00:06:08,360 --> 00:06:12,719 Speaker 1: knew that in the case of the Golden State Killer, 94 00:06:12,960 --> 00:06:16,559 Speaker 1: law enforcement had used a genealogy website called jet match 95 00:06:16,839 --> 00:06:19,760 Speaker 1: to find their suspect. Jet Match is sort of like 96 00:06:19,800 --> 00:06:24,280 Speaker 1: a big community repository for DNA data. For example, I 97 00:06:24,279 --> 00:06:26,840 Speaker 1: could upload my data from say twenty three and me 98 00:06:27,400 --> 00:06:29,640 Speaker 1: and find out whether I might be related to someone 99 00:06:29,680 --> 00:06:33,320 Speaker 1: else who uploaded data from a different service like ancestry. 100 00:06:33,880 --> 00:06:36,800 Speaker 1: What police did in this case is they uploaded data 101 00:06:36,920 --> 00:06:40,760 Speaker 1: from crime scene DNA and then looked for potential suspects 102 00:06:40,800 --> 00:06:43,120 Speaker 1: in the family trees of other people who showed up 103 00:06:43,160 --> 00:06:46,680 Speaker 1: as a genetic match, in other words, people who shared 104 00:06:46,720 --> 00:06:52,680 Speaker 1: the killer's DNA. We've reunited tens of thousands of people 105 00:06:52,720 --> 00:06:55,919 Speaker 1: with long lost family members, and it's exactly the same technique. 106 00:06:56,400 --> 00:06:59,400 Speaker 1: So if we can do it there for adoptees, there's 107 00:06:59,400 --> 00:07:01,200 Speaker 1: absolutely no reason we can't do it in these law 108 00:07:01,279 --> 00:07:05,320 Speaker 1: enforcement cases as well. In the past, Cecy had been 109 00:07:05,360 --> 00:07:08,960 Speaker 1: hesitant to go snooping through people's profiles for a purpose 110 00:07:09,000 --> 00:07:12,560 Speaker 1: they'd never intended, but once the Golden State killer case 111 00:07:12,720 --> 00:07:15,960 Speaker 1: was splashed across the headlines, she figured it was open season. 112 00:07:17,040 --> 00:07:20,560 Speaker 1: I didn't want to do this until people knew that 113 00:07:20,680 --> 00:07:23,120 Speaker 1: it was possible and that it was happening that their 114 00:07:23,200 --> 00:07:31,720 Speaker 1: DNA could be used for this purpose. CC's work is 115 00:07:31,760 --> 00:07:35,119 Speaker 1: possible in part because of a small software company called 116 00:07:35,200 --> 00:07:39,200 Speaker 1: Parabond Nano Labs. A few years ago, Parabond created a 117 00:07:39,240 --> 00:07:42,600 Speaker 1: program called Snapshot that can use crime scene DNA to 118 00:07:42,640 --> 00:07:46,000 Speaker 1: do basically what a sketch artist does. It creates a 119 00:07:46,080 --> 00:07:48,800 Speaker 1: vague picture of what a suspect might look like. It 120 00:07:48,920 --> 00:07:52,560 Speaker 1: does this by processing crime scene DNA with the same 121 00:07:52,640 --> 00:07:55,320 Speaker 1: kind of technology that companies like twenty three and Me 122 00:07:55,800 --> 00:07:59,880 Speaker 1: and Ancestry use in the world of law enforcement. This 123 00:08:00,000 --> 00:08:03,720 Speaker 1: hadn't really been done before I actually visited Parabon along 124 00:08:03,720 --> 00:08:07,280 Speaker 1: with Business Week reporter Drake Bennett. Their technique provides a 125 00:08:07,320 --> 00:08:10,440 Speaker 1: lot more data than crime scene labs usually work with. 126 00:08:11,000 --> 00:08:13,760 Speaker 1: One standard test, for example, looks at just twenty three 127 00:08:13,760 --> 00:08:17,160 Speaker 1: markers on the Y chromosome. Markers are unique places on 128 00:08:17,160 --> 00:08:21,200 Speaker 1: a person's genome, but Parabon looks at thousands of markers, 129 00:08:21,920 --> 00:08:24,440 Speaker 1: and more data means you can get a lot more 130 00:08:24,520 --> 00:08:27,960 Speaker 1: detail about what your suspect might be like and compare 131 00:08:28,000 --> 00:08:30,800 Speaker 1: that data to the consumer DNA tests that millions of 132 00:08:30,840 --> 00:08:34,679 Speaker 1: people are doing right now. And that's where CC comes in. 133 00:08:35,280 --> 00:08:38,920 Speaker 1: The data that Parabond generates to create its DNA sketches 134 00:08:39,400 --> 00:08:42,160 Speaker 1: is similar to the data people upload to sites like 135 00:08:42,280 --> 00:08:45,920 Speaker 1: jet match when they're looking for relatives. Last year, cec 136 00:08:46,080 --> 00:08:48,680 Speaker 1: reached out to Parabon to see if they could work together, 137 00:08:48,880 --> 00:08:51,880 Speaker 1: and eventually the company hired her to head up a 138 00:08:51,920 --> 00:08:56,120 Speaker 1: new unit devoted to forensic genetic genealogy. One of the 139 00:08:56,200 --> 00:08:59,120 Speaker 1: first cases to come in was from Snowhomish County in 140 00:08:59,160 --> 00:09:02,040 Speaker 1: Washington State. It was the case of j Cook and 141 00:09:02,080 --> 00:09:04,520 Speaker 1: Tanya van Kuilemberg that we heard about at the start, 142 00:09:05,040 --> 00:09:07,360 Speaker 1: and it was right after the Golden State killer arrest, 143 00:09:07,400 --> 00:09:10,320 Speaker 1: so there was a lot of enthusiasm from law enforcement 144 00:09:10,320 --> 00:09:14,360 Speaker 1: around the country about using this same technique. Cecie got 145 00:09:14,360 --> 00:09:18,080 Speaker 1: to work and I kept waiting for matches to populate, 146 00:09:18,160 --> 00:09:20,400 Speaker 1: but they didn't populate. That Friday night, I went to 147 00:09:20,440 --> 00:09:23,800 Speaker 1: sleep and I woke up Saturday morning to a list 148 00:09:23,840 --> 00:09:27,640 Speaker 1: of DNA matches on JED match. She got really lucky. 149 00:09:27,760 --> 00:09:30,719 Speaker 1: There In the list of matches was the geneological equivalent 150 00:09:30,840 --> 00:09:34,280 Speaker 1: of winning the lottery. Two cousins who shared a lot 151 00:09:34,360 --> 00:09:36,760 Speaker 1: of DNA with the suspect, but who didn't seem to 152 00:09:36,800 --> 00:09:40,120 Speaker 1: be related to each other. So imagine a cousin on 153 00:09:40,160 --> 00:09:42,880 Speaker 1: your dad's side of the family and another cousin on 154 00:09:42,920 --> 00:09:45,920 Speaker 1: your mom's side of the family. Those two cousins aren't 155 00:09:45,920 --> 00:09:48,360 Speaker 1: related to each other, but they are related to you, 156 00:09:49,080 --> 00:09:52,440 Speaker 1: So that tells me I should be able to find 157 00:09:52,440 --> 00:09:56,120 Speaker 1: a triangulation between them, meaning a place where those two 158 00:09:56,160 --> 00:10:00,199 Speaker 1: family trees come together. From there, Cecie turned to all 159 00:10:00,240 --> 00:10:03,680 Speaker 1: the traditional tools of genealogy to build a family tree 160 00:10:03,840 --> 00:10:06,199 Speaker 1: for each of the people who showed up as a match. 161 00:10:06,640 --> 00:10:10,640 Speaker 1: That meant searching through Facebook, newspaper archives, and local records 162 00:10:10,880 --> 00:10:13,440 Speaker 1: to figure out who else these people were related to. 163 00:10:14,080 --> 00:10:16,720 Speaker 1: Since the two cousins of the suspect weren't related to 164 00:10:16,760 --> 00:10:19,520 Speaker 1: each other, ceci knew that somewhere there had to be 165 00:10:19,600 --> 00:10:23,000 Speaker 1: a marriage between the two families. Eventually, she found an 166 00:10:23,040 --> 00:10:26,720 Speaker 1: obituary for a woman from one family who was carrying 167 00:10:26,760 --> 00:10:29,600 Speaker 1: a last name from the other. Perhaps this was it, 168 00:10:38,000 --> 00:10:40,880 Speaker 1: Cecie told me. Marriage records are pretty good in Washington State, 169 00:10:41,000 --> 00:10:43,400 Speaker 1: so she was able to confirm that this was indeed 170 00:10:43,440 --> 00:10:47,120 Speaker 1: the marriage she'd been looking for. And this resulted in 171 00:10:47,679 --> 00:10:50,680 Speaker 1: four children, three of which were female, and so we 172 00:10:50,760 --> 00:10:56,360 Speaker 1: only had one male. That one male was the only 173 00:10:56,480 --> 00:11:01,199 Speaker 1: probable suspect. Within a few hours, cc found herself staring 174 00:11:01,240 --> 00:11:05,680 Speaker 1: at a name, William Earl Talbot. The second police collected 175 00:11:05,720 --> 00:11:09,160 Speaker 1: a new DNA sample from him and confirmed it matched 176 00:11:09,200 --> 00:11:13,119 Speaker 1: the DNA found at the crime scene. Then, on May seventeen, 177 00:11:13,600 --> 00:11:17,280 Speaker 1: police took William Earl Talbot into custody. Of course, he 178 00:11:17,280 --> 00:11:21,960 Speaker 1: hasn't been found guilty yet, but my work certainly points 179 00:11:22,040 --> 00:11:25,640 Speaker 1: right at him. William L. Talbot has been charged with 180 00:11:25,679 --> 00:11:29,680 Speaker 1: both murders, but he's pleaded not guilty. If he's convicted, 181 00:11:29,760 --> 00:11:37,560 Speaker 1: he could face the death penalty. The Snohomish case was 182 00:11:37,640 --> 00:11:40,960 Speaker 1: just the first murder case CCI tried to crack. To date, 183 00:11:41,280 --> 00:11:45,000 Speaker 1: Parabon and CC have solved more than a dozen cases, 184 00:11:45,200 --> 00:11:48,040 Speaker 1: and they have dozens more in the works. Parabon has 185 00:11:48,080 --> 00:11:51,640 Speaker 1: added three other full time genealogists to its staff, with 186 00:11:51,720 --> 00:11:54,840 Speaker 1: CC heading up that team. But when people ship their 187 00:11:54,960 --> 00:11:58,560 Speaker 1: DNA after me or ancestry to find out whether they're 188 00:11:58,559 --> 00:12:02,200 Speaker 1: Italian or what their g say about their taste for cilantro, 189 00:12:02,960 --> 00:12:07,479 Speaker 1: they probably don't imagine it being used for a criminal investigation. 190 00:12:08,000 --> 00:12:11,720 Speaker 1: The Golden State killer case bren already bubbling conversation about 191 00:12:11,800 --> 00:12:17,319 Speaker 1: DNA and privacy to a boil. When you send your 192 00:12:17,360 --> 00:12:20,680 Speaker 1: saliva off to a DNA testing company, you're handing over 193 00:12:21,080 --> 00:12:26,160 Speaker 1: extremely sensitive, extremely personal information, not just about yourself, but 194 00:12:26,240 --> 00:12:31,000 Speaker 1: about other people you're related to. Consumer genetic testing companies. 195 00:12:31,160 --> 00:12:34,360 Speaker 1: So companies like Ancestry and twenty three and me don't 196 00:12:34,400 --> 00:12:37,920 Speaker 1: in general share data with law enforcement unless they're legally 197 00:12:37,920 --> 00:12:41,400 Speaker 1: compelled to. But that data gets shared in lots of 198 00:12:41,440 --> 00:12:47,120 Speaker 1: other ways. For example, DNA testing companies are already using 199 00:12:47,120 --> 00:12:50,120 Speaker 1: the data for research over time. There could be other 200 00:12:50,240 --> 00:12:54,120 Speaker 1: uses for that data too. For example, what if advertisers 201 00:12:54,200 --> 00:12:57,520 Speaker 1: one day used it to Taylor adds to you. What 202 00:12:57,600 --> 00:13:01,559 Speaker 1: if authorities used it not just to down serial killers 203 00:13:01,559 --> 00:13:04,720 Speaker 1: but petty criminals. I got into some of this with 204 00:13:04,760 --> 00:13:08,319 Speaker 1: Aaron Murphy. She's a law professor, and yu, I mean 205 00:13:08,360 --> 00:13:11,800 Speaker 1: the police. You were able to use DNA to determine 206 00:13:11,840 --> 00:13:14,280 Speaker 1: something that probably people in the world do not know, 207 00:13:14,440 --> 00:13:17,679 Speaker 1: which is who is your six cousin? I mean, I 208 00:13:17,760 --> 00:13:20,920 Speaker 1: always say, now, I don't think people have fully internalized 209 00:13:20,960 --> 00:13:25,040 Speaker 1: that they may be the person who's the pivot. Aaron 210 00:13:25,120 --> 00:13:27,840 Speaker 1: thinks that if we fully grasped the scope of what 211 00:13:27,960 --> 00:13:30,520 Speaker 1: law enforcement could learn about any of us by using 212 00:13:30,559 --> 00:13:35,599 Speaker 1: these new DNA technologies, we'd be truly shocked. Sometimes I 213 00:13:35,679 --> 00:13:38,040 Speaker 1: say like, okay, we'll go on twenty three and me 214 00:13:38,640 --> 00:13:40,160 Speaker 1: and look at the list of things that they're going 215 00:13:40,200 --> 00:13:41,839 Speaker 1: to tell you about, and then tell me if you 216 00:13:41,840 --> 00:13:44,320 Speaker 1: want to march down to your local prestinct and give 217 00:13:44,360 --> 00:13:47,440 Speaker 1: that list of those things, so your sheariff with your 218 00:13:47,559 --> 00:13:50,520 Speaker 1: name and the answers to be clear. It is highly 219 00:13:50,600 --> 00:13:53,440 Speaker 1: unlikely that police would get hold of a whole vial 220 00:13:53,480 --> 00:13:56,000 Speaker 1: of saliva from a crime scene and send it into 221 00:13:56,000 --> 00:13:58,560 Speaker 1: a company like twenty three and me. Most of the 222 00:13:58,559 --> 00:14:01,360 Speaker 1: time there are just tiny bit of DNA left behind 223 00:14:01,400 --> 00:14:04,360 Speaker 1: at the scene of a crime. But the technology has 224 00:14:04,400 --> 00:14:07,200 Speaker 1: already advanced enough that these kinds of searchers are actually 225 00:14:07,200 --> 00:14:10,480 Speaker 1: possible through a pair bond nano labs and jet match, 226 00:14:10,960 --> 00:14:13,520 Speaker 1: and your information could be exposed even if you don't 227 00:14:13,559 --> 00:14:16,480 Speaker 1: take one of these spit tests yourself. The key thing 228 00:14:16,520 --> 00:14:18,200 Speaker 1: here is that it doesn't have to be you, you know, 229 00:14:18,280 --> 00:14:20,960 Speaker 1: if they can find that information out through a relative 230 00:14:21,000 --> 00:14:24,960 Speaker 1: of yours, because we're looking at you know, enough snips 231 00:14:24,960 --> 00:14:26,920 Speaker 1: that we could make a prediction about what you look 232 00:14:26,960 --> 00:14:29,160 Speaker 1: like based on your relative or whether your family has 233 00:14:29,200 --> 00:14:33,200 Speaker 1: certain dispositions. Then the whole families could be cut off 234 00:14:33,280 --> 00:14:36,960 Speaker 1: because of one person's you know, cavalier approached to another 235 00:14:37,000 --> 00:14:40,120 Speaker 1: private day. There actually is a precedent for what police 236 00:14:40,200 --> 00:14:43,120 Speaker 1: can and cannot do when it comes to locating criminal 237 00:14:43,160 --> 00:14:47,120 Speaker 1: suspects through their relatives. Police can upload crime scene data 238 00:14:47,280 --> 00:14:51,440 Speaker 1: to a government criminal DNA database called CODIS to see 239 00:14:51,440 --> 00:14:55,080 Speaker 1: if there's a match to anyone else. One major concern, though, 240 00:14:55,080 --> 00:14:58,160 Speaker 1: with using CODIS in this way, is that the database 241 00:14:58,280 --> 00:15:01,520 Speaker 1: excuse towards people of color, meaning that searching it for 242 00:15:01,560 --> 00:15:06,960 Speaker 1: family matches just continues to disproportionately imprisoned minority populations. But 243 00:15:07,040 --> 00:15:10,600 Speaker 1: privacy is a concern too, so in California, for example, 244 00:15:10,920 --> 00:15:14,200 Speaker 1: police can only use codeis after they've exhausted all other 245 00:15:14,280 --> 00:15:17,840 Speaker 1: search tools. It's called familial search. But some states have 246 00:15:17,960 --> 00:15:20,600 Speaker 1: strict laws governing when police are allowed to use it, 247 00:15:20,840 --> 00:15:23,560 Speaker 1: and at least one state has actually forbid it altogether. 248 00:15:24,440 --> 00:15:28,520 Speaker 1: Those rules, though, only govern that federal database. Big open 249 00:15:28,560 --> 00:15:32,480 Speaker 1: platforms where people can voluntarily upload their data, services like 250 00:15:32,560 --> 00:15:36,560 Speaker 1: judd match are private. That means CC's investigations are not 251 00:15:36,720 --> 00:15:40,080 Speaker 1: subject to those same strict rules that apply to government 252 00:15:40,160 --> 00:15:44,560 Speaker 1: DNA databases. In fact, she's already solved one case that 253 00:15:44,600 --> 00:15:48,040 Speaker 1: didn't meet California's rules for familial search. It was a 254 00:15:48,120 --> 00:15:55,440 Speaker 1: three month old rape case in Utah, but CC is 255 00:15:55,480 --> 00:15:59,680 Speaker 1: wary of her powers. She worries, for one, about genealogists 256 00:15:59,680 --> 00:16:02,080 Speaker 1: who don't know what they're doing, leading police to the 257 00:16:02,080 --> 00:16:05,560 Speaker 1: wrong suspect. That's actually already sort of happened once a 258 00:16:05,560 --> 00:16:11,120 Speaker 1: few years back, using a slightly different technology. You know, 259 00:16:11,200 --> 00:16:13,600 Speaker 1: I don't like the idea of this being the wild West, 260 00:16:14,160 --> 00:16:17,520 Speaker 1: where people that don't have any law enforcement experience are 261 00:16:17,520 --> 00:16:22,120 Speaker 1: out there offering services to law enforcement and there's no 262 00:16:22,320 --> 00:16:26,000 Speaker 1: quality control, you know, there's no checks and balances, And 263 00:16:26,080 --> 00:16:28,920 Speaker 1: I want to make sure that genetic genealogy is shown 264 00:16:28,920 --> 00:16:32,240 Speaker 1: in the best possible way through these cases with law 265 00:16:32,360 --> 00:16:37,560 Speaker 1: enforcement and if there aren't unnecessary missteps or negative outcomes. 266 00:16:38,320 --> 00:16:42,000 Speaker 1: But CC doesn't have the same concerns about people's privacy. 267 00:16:42,680 --> 00:16:44,800 Speaker 1: She said it would be hard for jed match users 268 00:16:44,840 --> 00:16:47,320 Speaker 1: at this point to not know that she's creeping around 269 00:16:47,320 --> 00:16:49,680 Speaker 1: in there, and she thinks her work might prevent some 270 00:16:49,760 --> 00:16:55,320 Speaker 1: innocent people from being wrongly suspected. Now, yes, some innocent 271 00:16:55,360 --> 00:17:00,120 Speaker 1: family members are going to get pulled into investigations, but 272 00:17:00,200 --> 00:17:05,040 Speaker 1: it's going to eliminate dozens or hundreds, or sometimes even 273 00:17:05,119 --> 00:17:08,760 Speaker 1: thousands of innocent people that are completely unrelated to the 274 00:17:08,800 --> 00:17:15,879 Speaker 1: crime or the criminal being looked at. Okay, so, PA, 275 00:17:16,280 --> 00:17:19,119 Speaker 1: after hearing about all of this, I have to know, 276 00:17:19,359 --> 00:17:25,080 Speaker 1: have you ever taken a DNA test? You know? I haven't, 277 00:17:25,240 --> 00:17:27,159 Speaker 1: and I guess at some level it's because I was 278 00:17:27,240 --> 00:17:30,600 Speaker 1: always a little creeped out about it. But actually quite 279 00:17:30,600 --> 00:17:33,000 Speaker 1: a few of my relatives have done these tests, and 280 00:17:33,040 --> 00:17:35,120 Speaker 1: so I know I'm exposed. I just don't know how much. 281 00:17:35,720 --> 00:17:39,680 Speaker 1: So there was actually a very interesting study that just 282 00:17:39,880 --> 00:17:44,320 Speaker 1: came out that answers that question. So this researcher from 283 00:17:44,320 --> 00:17:49,200 Speaker 1: Colombia and another DNA testing company called my Heritage found 284 00:17:49,440 --> 00:17:53,320 Speaker 1: that if you are an American of European descent, there 285 00:17:53,440 --> 00:17:56,879 Speaker 1: is a sixty percent chance that you have a relative 286 00:17:57,000 --> 00:17:59,240 Speaker 1: that has done a DNA test that could expose you. 287 00:18:00,040 --> 00:18:04,440 Speaker 1: So basically, we're approaching all of us being exposed. And 288 00:18:04,480 --> 00:18:06,760 Speaker 1: that's basically what happened in the case of the Golden 289 00:18:06,760 --> 00:18:09,439 Speaker 1: State killer. He didn't actually take one of these DNA 290 00:18:09,520 --> 00:18:13,159 Speaker 1: tests himself, but obviously someone he's related to did, and 291 00:18:13,200 --> 00:18:16,320 Speaker 1: not just that, they then took the second step of 292 00:18:16,520 --> 00:18:21,840 Speaker 1: uploading their results to jet match, this open source community platform, 293 00:18:21,880 --> 00:18:24,639 Speaker 1: and without that second step police would never have been 294 00:18:24,680 --> 00:18:27,200 Speaker 1: able to crack the case. I think when people take 295 00:18:27,240 --> 00:18:30,200 Speaker 1: these tests, even if they have, you know, maybe thought 296 00:18:30,640 --> 00:18:35,600 Speaker 1: about these consequences, it still seems unrealistic that anything really 297 00:18:35,680 --> 00:18:40,160 Speaker 1: bad would happen because of sharing their data. But actually, 298 00:18:40,640 --> 00:18:42,640 Speaker 1: you know, Aaron Murphy is one of the most cynical 299 00:18:43,040 --> 00:18:46,199 Speaker 1: people I've met when it comes to genetic privacy, and 300 00:18:46,240 --> 00:18:48,640 Speaker 1: she had a lot of thoughts about the kinds of 301 00:18:48,680 --> 00:18:53,040 Speaker 1: bad things that might happen. The whole purpose of insurers, 302 00:18:53,040 --> 00:18:56,040 Speaker 1: whether a health insurer or a life insure or a 303 00:18:56,160 --> 00:18:59,840 Speaker 1: long term disability insure, is to predict whether people are 304 00:19:00,000 --> 00:19:02,200 Speaker 1: in neither services or not, because the model was premised 305 00:19:02,240 --> 00:19:06,000 Speaker 1: on people not needing the services. And if an insurer 306 00:19:06,200 --> 00:19:08,680 Speaker 1: could find out through a Google search if they might 307 00:19:08,720 --> 00:19:11,000 Speaker 1: have to pay out an Alzheimer's claim on you, or 308 00:19:11,040 --> 00:19:12,720 Speaker 1: they have to pay out at Parkinson's claim on you, 309 00:19:12,800 --> 00:19:13,960 Speaker 1: or they're going to have to support you through the 310 00:19:14,080 --> 00:19:17,880 Speaker 1: stabilitating diseases or MS. Right, you know, don't you think 311 00:19:17,880 --> 00:19:20,720 Speaker 1: you're not going to get that protection? So there is 312 00:19:20,840 --> 00:19:24,480 Speaker 1: one law. It's called the Genetic Information Nondiscrimination Act. It 313 00:19:24,560 --> 00:19:27,159 Speaker 1: was passed in two tho eight, and it does offer 314 00:19:27,440 --> 00:19:32,719 Speaker 1: some limited protection of how your data can be used, 315 00:19:33,440 --> 00:19:36,960 Speaker 1: but it has a lot of loopholes, like, for example, 316 00:19:37,160 --> 00:19:39,880 Speaker 1: it does not apply to life insurance, so a life 317 00:19:39,960 --> 00:19:44,359 Speaker 1: ensure could potentially just ask you like, hey, have you 318 00:19:44,440 --> 00:19:47,159 Speaker 1: taken a DNA test? And if you have, you have 319 00:19:47,280 --> 00:19:50,640 Speaker 1: to give them that information and maybe they could decide 320 00:19:50,640 --> 00:19:53,040 Speaker 1: whether or not to give you life insurance coverage based 321 00:19:53,040 --> 00:19:55,600 Speaker 1: on it. I also think that because the Golden State 322 00:19:55,680 --> 00:19:59,200 Speaker 1: killer was such a brutal and violent case, there was 323 00:19:59,240 --> 00:20:01,960 Speaker 1: a lot of public septance behind the idea that finally 324 00:20:02,040 --> 00:20:05,840 Speaker 1: this technique had allowed us to identify a suspect. And 325 00:20:05,840 --> 00:20:07,800 Speaker 1: I think a lot of people think that because they 326 00:20:07,920 --> 00:20:11,520 Speaker 1: are not violent criminals, using this kind of technique to 327 00:20:11,600 --> 00:20:16,639 Speaker 1: hunt down very rare, very violent people won't affect them. 328 00:20:16,680 --> 00:20:20,239 Speaker 1: And the unintended consequences of this technology are only just 329 00:20:20,280 --> 00:20:23,440 Speaker 1: beginning to unfold. Denying someone life insurance is just one 330 00:20:23,440 --> 00:20:26,560 Speaker 1: example of how this technology might be used, and we 331 00:20:26,600 --> 00:20:28,800 Speaker 1: don't really know at this stage how far it could go. 332 00:20:29,880 --> 00:20:32,560 Speaker 1: And I think that's the scariest part of this, right. 333 00:20:32,680 --> 00:20:35,800 Speaker 1: This is a technology that is kind of in its infancy. 334 00:20:35,840 --> 00:20:38,360 Speaker 1: You know, when cell phones first starting to be a thing, 335 00:20:38,600 --> 00:20:41,439 Speaker 1: I don't think anybody ever imagined that we would be 336 00:20:41,520 --> 00:20:46,040 Speaker 1: using them for everything besides actually making phone calls. And 337 00:20:46,160 --> 00:20:48,679 Speaker 1: you know, now I carry my iPhone around with me 338 00:20:48,840 --> 00:20:52,719 Speaker 1: all the time and it tracks my location. And to 339 00:20:52,760 --> 00:20:55,640 Speaker 1: your point, cell phone data is only one type of 340 00:20:55,680 --> 00:20:58,880 Speaker 1: personal data that we're entrusting to a third party company. 341 00:20:58,960 --> 00:21:01,359 Speaker 1: So that repository of data is sitting in one place 342 00:21:01,400 --> 00:21:04,639 Speaker 1: with your provider like Apple or Google um, which is 343 00:21:04,680 --> 00:21:07,480 Speaker 1: separate from the data that a company like twenty three 344 00:21:07,480 --> 00:21:09,320 Speaker 1: and me would have on you if you complete one 345 00:21:09,359 --> 00:21:12,879 Speaker 1: of these DNA tests, right. I think a really important 346 00:21:13,080 --> 00:21:16,240 Speaker 1: part of this story is you know that it's not 347 00:21:16,359 --> 00:21:19,960 Speaker 1: just the DNA data that CC is using to solve 348 00:21:20,000 --> 00:21:22,480 Speaker 1: these crimes. She's getting that data and then she's going 349 00:21:22,480 --> 00:21:25,199 Speaker 1: on Facebook and looking at all the information people have 350 00:21:25,320 --> 00:21:28,520 Speaker 1: shared there. And we're just sharing all of this data 351 00:21:28,680 --> 00:21:32,840 Speaker 1: and not thinking about the consequences, and it's really hard 352 00:21:32,840 --> 00:21:35,240 Speaker 1: to know where that will leave us in the future. 353 00:21:41,920 --> 00:21:44,120 Speaker 1: So it makes me think that as a society, we're 354 00:21:44,119 --> 00:21:46,920 Speaker 1: really just at the very beginning of understanding how much 355 00:21:46,920 --> 00:21:49,080 Speaker 1: our data is worth and how to take care of 356 00:21:49,119 --> 00:21:52,000 Speaker 1: it properly. Perhaps in the coming years, regulators will have 357 00:21:52,080 --> 00:21:54,080 Speaker 1: to step in and tell us what they think is 358 00:21:54,119 --> 00:22:04,160 Speaker 1: a responsible way for companies to use our genetic information. Hey, 359 00:22:04,240 --> 00:22:07,680 Speaker 1: Kersten's going good. So we're now in the present day. 360 00:22:07,840 --> 00:22:12,960 Speaker 1: It's October, almost exactly a year after we first published 361 00:22:13,000 --> 00:22:17,840 Speaker 1: your story. A lot's happened since then. Give us the lowdown. Yeah, 362 00:22:17,920 --> 00:22:21,120 Speaker 1: so a lot has happened. I think the biggest thing 363 00:22:22,000 --> 00:22:24,960 Speaker 1: for me is that it's become very clear that forensic 364 00:22:25,080 --> 00:22:29,800 Speaker 1: genetic genealogy it's a tool, a technology that is not 365 00:22:29,920 --> 00:22:33,560 Speaker 1: going away anytime soon. This has now been used to 366 00:22:33,680 --> 00:22:37,600 Speaker 1: solve dozens and dozens and dozens of cold cases and 367 00:22:37,680 --> 00:22:41,240 Speaker 1: now also a lot of active cases. The Department of 368 00:22:41,320 --> 00:22:46,639 Speaker 1: Justice actually issued this really interesting preliminary policy report on 369 00:22:46,800 --> 00:22:50,080 Speaker 1: it as an investigative tool. But it was interesting because 370 00:22:50,080 --> 00:22:53,679 Speaker 1: there was also a cautionary note in that policy report. 371 00:22:53,720 --> 00:22:57,119 Speaker 1: They said this tool should be used as a last 372 00:22:57,119 --> 00:23:01,919 Speaker 1: resort because it is invasive, and they recognize that. Interesting. 373 00:23:02,160 --> 00:23:04,720 Speaker 1: What else is new? Yeah, so, I think one of 374 00:23:04,760 --> 00:23:08,040 Speaker 1: the most interesting things that has happened is we've started 375 00:23:08,080 --> 00:23:11,720 Speaker 1: to see this technology used for different kinds of cases. 376 00:23:12,040 --> 00:23:15,880 Speaker 1: There was one really controversial case just this year in 377 00:23:15,920 --> 00:23:20,240 Speaker 1: which jed match allowed police in Utah to use it 378 00:23:20,320 --> 00:23:23,920 Speaker 1: for a violent assault. Previously, it had mainly been used 379 00:23:23,960 --> 00:23:27,600 Speaker 1: for murders. I think there had been a few rapes 380 00:23:27,680 --> 00:23:32,280 Speaker 1: even but for some reason, this really upset users. They 381 00:23:32,320 --> 00:23:35,440 Speaker 1: felt like this was a violation of their privacy. They 382 00:23:35,480 --> 00:23:40,120 Speaker 1: had not consented to their information being used for this 383 00:23:40,320 --> 00:23:43,440 Speaker 1: kind of criminal investigation. That it was just too far 384 00:23:43,800 --> 00:23:47,320 Speaker 1: down the slippery slope. You know what's next using it 385 00:23:47,400 --> 00:23:51,560 Speaker 1: to prosecute shoplifters. And because of that backlash, jed match 386 00:23:51,600 --> 00:23:55,520 Speaker 1: actually had to make their site opt in instead of 387 00:23:55,560 --> 00:23:59,680 Speaker 1: opt out, which means that overnight it went from every 388 00:23:59,760 --> 00:24:03,439 Speaker 1: jed match user being automatically available to the police to 389 00:24:03,520 --> 00:24:05,760 Speaker 1: search unless they said they didn't want to do that, 390 00:24:06,080 --> 00:24:09,320 Speaker 1: to the opposite. And so their database went from having 391 00:24:09,840 --> 00:24:14,000 Speaker 1: more than a million people whose profiles the police could 392 00:24:14,440 --> 00:24:19,240 Speaker 1: access in order to do these investigations to having last 393 00:24:19,320 --> 00:24:20,959 Speaker 1: Night checked in with them. A few weeks ago, they 394 00:24:21,000 --> 00:24:24,480 Speaker 1: had just a hundred and thirty thousand people in their database, 395 00:24:24,520 --> 00:24:28,480 Speaker 1: which makes it almost useless to investigators. So what are 396 00:24:28,520 --> 00:24:31,959 Speaker 1: investigators using now? So there's one of their site, family 397 00:24:32,000 --> 00:24:35,520 Speaker 1: tree DNA, that has opened itself up to these kinds 398 00:24:35,520 --> 00:24:40,360 Speaker 1: of investigations. I think that jud match has been adding users. 399 00:24:40,560 --> 00:24:43,080 Speaker 1: They told me seven or eight hundred every week, so 400 00:24:43,160 --> 00:24:45,960 Speaker 1: they're hoping they get those numbers back up. But yeah, 401 00:24:46,000 --> 00:24:49,639 Speaker 1: it's definitely this technology took a hit when that happened. 402 00:24:50,119 --> 00:24:53,080 Speaker 1: And it's still the case that the major DNA testing 403 00:24:53,080 --> 00:24:57,480 Speaker 1: companies like twenty three and me don't cooperate with law enforcement, 404 00:24:57,560 --> 00:25:01,560 Speaker 1: right right, and ME and S three have made very 405 00:25:01,560 --> 00:25:05,600 Speaker 1: clear that unless they are subpoenat, unless they are legally compelled, 406 00:25:05,640 --> 00:25:07,880 Speaker 1: if they are not going to let law enforcement look 407 00:25:07,880 --> 00:25:11,840 Speaker 1: at their records. Now that you know, we've known about 408 00:25:11,880 --> 00:25:16,480 Speaker 1: this use of DNA testing for I guess a little 409 00:25:16,560 --> 00:25:18,840 Speaker 1: over a year, do you get the sense that people 410 00:25:18,880 --> 00:25:22,959 Speaker 1: are more accepting of this technology. I think people are 411 00:25:22,960 --> 00:25:26,920 Speaker 1: actually less accepting of it. You know, people are really 412 00:25:26,960 --> 00:25:30,879 Speaker 1: conscious now of the ways their data is used, you know, 413 00:25:30,960 --> 00:25:35,480 Speaker 1: not just by DNA testing companies, but by Facebook, by Instagram. Right. 414 00:25:35,760 --> 00:25:41,040 Speaker 1: So we see this increasing sensitivity to violations of people's privacy, 415 00:25:41,320 --> 00:25:44,880 Speaker 1: including in this space. But I think that that might 416 00:25:45,040 --> 00:25:48,960 Speaker 1: change as we see different use cases of this technology. 417 00:25:49,119 --> 00:25:52,680 Speaker 1: There was one recent instance that really started to change 418 00:25:52,720 --> 00:25:56,119 Speaker 1: my mind about this. Maybe. There was this rape case, 419 00:25:56,320 --> 00:26:02,000 Speaker 1: Angie Dodd rape case. For a long time, the wrong 420 00:26:02,080 --> 00:26:05,280 Speaker 1: person was in prison for her rape and murder. This 421 00:26:05,320 --> 00:26:10,359 Speaker 1: guy named Christopher Tap and the victim's mother pushed to 422 00:26:10,520 --> 00:26:14,000 Speaker 1: use genealogy to try and figure out who actually did this, 423 00:26:14,080 --> 00:26:17,440 Speaker 1: and they found another potential suspect, and Christopher Tap was 424 00:26:17,480 --> 00:26:21,920 Speaker 1: exonerated after being wrongfully imprisoned for more than two decades. 425 00:26:22,080 --> 00:26:26,639 Speaker 1: So I think that showed me that there's all different 426 00:26:26,720 --> 00:26:29,840 Speaker 1: kinds of powers this technology has, and it makes me 427 00:26:29,920 --> 00:26:33,159 Speaker 1: wonder what other ways this technology will be used that 428 00:26:33,200 --> 00:26:36,520 Speaker 1: we haven't thought about yet. Maybe. And what's our protagonist 429 00:26:36,760 --> 00:26:39,400 Speaker 1: cc More up to these days? Oh my gosh, cecy More. 430 00:26:40,280 --> 00:26:42,760 Speaker 1: She's so busy. Usually I have to email her like 431 00:26:42,800 --> 00:26:46,760 Speaker 1: seven times before she emails you back. Now, CC has 432 00:26:46,760 --> 00:26:49,640 Speaker 1: solved more of these cases than anybody else. She now 433 00:26:49,680 --> 00:26:53,560 Speaker 1: has this whole team that works with her solving these crimes. 434 00:26:53,560 --> 00:26:56,719 Speaker 1: She's definitely solved more than fifty of these cases. At 435 00:26:56,720 --> 00:27:00,040 Speaker 1: this point. She's just you know, working away, sitting on 436 00:27:00,119 --> 00:27:07,439 Speaker 1: our couch doing her DNA sleeping. Well, thanks for this 437 00:27:07,520 --> 00:27:23,199 Speaker 1: update today, You're welcome. This episode was originally produced by 438 00:27:23,200 --> 00:27:26,040 Speaker 1: p I get Cary and Liz Smith. The update was 439 00:27:26,080 --> 00:27:28,720 Speaker 1: produced by me Aki Ito and Ethan Brooks with help 440 00:27:28,720 --> 00:27:32,200 Speaker 1: from Toe for Foreheads. Our story editors are Anne vander May. 441 00:27:32,280 --> 00:27:36,320 Speaker 1: And Emily Busso. Francesca Levi is ahead of Bloomberg Podcasts. 442 00:27:36,560 --> 00:28:00,480 Speaker 1: We'll see you next week.