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Speaker 1: You're listening to a Tenderfoot TV podcast.

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Speaker 2: Girls.

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Speaker 3: The views and opinions expressed in this podcast are solely

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Speaker 3: those of the authors and participants and do not necessarily

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Speaker 3: represent those of iHeartMedia, Tenderfoot TV, or their employees. This

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Speaker 3: series contains discussions of violence and sexual violence. Listener discretion

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Speaker 3: is advised. Previously on Algorithm, I spoke with a caller

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Speaker 3: who told me about Darren Vond's ruse and her theory

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Speaker 3: about his motivation.

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Speaker 1: His mom had to be everything about what he went

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Speaker 1: out and kieled.

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Speaker 3: And I asked Bond's lawyer, Guiko Kasich, what led Von

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Speaker 3: to change his mind about the death penalty.

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Speaker 2: From the very beginning is and when death I want death?

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Speaker 2: I want death. And then all of a sudden, about.

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Speaker 1: Three days, four days before we cut the play, he

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Speaker 1: changed his mind.

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Speaker 3: I hoped that Vond might now be open to confessing

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Speaker 3: to more murders, so I sent him a letter, and

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Speaker 3: months later I received a response from Vaughn where he

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Speaker 3: agreed to an interview. I, Darren D. Vaughn would like

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Speaker 3: to offer you a deal. You would have to write

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Speaker 3: a report of the corruption that's ongoing at the Wabash

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Speaker 3: Valley correctional facility, but when I contacted the Department of Corrections,

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Speaker 3: they told me he wasn't interested. From iHeartRadio and Tenderfoot TV,

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Speaker 3: this is algorithm. I'm ben Keebrick. I think beyond a

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Speaker 3: new confession from Vaughn, one of the best chances we

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Speaker 3: have of connecting him to additional crimes is DNA. Because

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Speaker 3: of backlogs in DNA testing across the country, I wondered

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Speaker 3: if police had ever checked for DNA evidence associated with

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Speaker 3: the cold cases Hargrove had identified, or with other unsolved

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Speaker 3: murderers or sexual assaults in the area. I came across

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Speaker 3: an article from the Northwest Indiana Times that in twenty eighteen,

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Speaker 3: Lake County, Indiana, had found over two hundred untested rape

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Speaker 3: kits and made plans to test them. I was curious

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Speaker 3: what came of that effort. The article mentioned one of

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Speaker 3: the people involved was Lake County Deputy Prosecutor Nadia Wardrop,

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Speaker 3: so I reached out to her for comment. Wardrop is

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Speaker 3: one of four female deputy prosecutors who in twenty eighteen

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Speaker 3: were brought in to reform the way crimes like sexual

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Speaker 3: assault were handled. When I emailed Wardrop, she told me

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Speaker 3: that she wanted to talk, but said she couldn't do

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Speaker 3: so without permission and forwarded my email to their PR person.

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Speaker 3: I looped back a week later and she told me

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Speaker 3: she still hadn't gotten to go ahead, but recommended I

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Speaker 3: contact the fair Haven Rape Crisis Center. It's a nonprofit

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Speaker 3: group that was also involved in Lake County's initiative to

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Speaker 3: test their untested rape kits. I called there and spoke

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Speaker 3: to Becca Emerson.

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Speaker 4: So, my name is Becca Emerson, and I am the

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Speaker 4: anti trafficking coordinator at fair Haven Rape Crisis Center.

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Speaker 3: It turned out that Becca was actually familiar with the podcast.

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Speaker 5: Can I ask what podcast this is? I'm a big

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Speaker 5: podcast listener, like to check out.

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Speaker 3: So it's called Algorithm.

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Speaker 5: Oh my god, I listened to your podcast.

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Speaker 4: I was just listening to the one.

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Speaker 5: Oh my god. I'm sorry. Now I'm like all Star starts.

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Speaker 3: So when I was looking into this stuff, it looked

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Speaker 3: like in twenty seventeen, there was this statewide initiative to

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Speaker 3: look into untested rape kids.

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Speaker 4: Yes, that is correct. So the statewide initiative was a

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Speaker 4: voluntary initiative put forward by our state to see how

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Speaker 4: many untested kits we had. Because back in twenty seventeen

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Speaker 4: was when the discussion at a nationwide level of the backlog.

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Speaker 5: Was starting to happen. So this was a big hot topic,

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Speaker 5: and Indiana got on.

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Speaker 4: Board and said, we need to test our kids.

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Speaker 5: And we need to see how many we have to

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Speaker 5: do that.

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Speaker 4: So there was this initiative. It was not mandatory, and

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Speaker 4: I believe ninety one out of our ninety two counties

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Speaker 4: did participate.

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Speaker 5: In Lake County was one of them.

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Speaker 1: Yeah.

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Speaker 3: Then I think when I was looking through the report,

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Speaker 3: you know, they asked for all their jurisdictions to report,

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Speaker 3: and it looked like maybe not all of them had.

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Speaker 4: Yeah, Lake County did not have all of our jurisdiction's report.

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Speaker 5: I do know that some of them did.

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Speaker 4: And I do have those numbers, but not every jurisdiction

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Speaker 4: in Lake County participated.

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Speaker 1: Yeah.

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Speaker 3: Do you happen to know which ones didn't or not?

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Speaker 5: Off the top of my head. I do know that.

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Speaker 4: Hammond Police Department had a pretty high number, one of

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Speaker 4: our highest cities in our county.

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Speaker 5: But I mean, we have.

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Speaker 4: I think fourteen different municipalities in our county. We're the

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Speaker 4: second largest county in the state. So in twenty seventeen,

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Speaker 4: Lake County came together with our sexual assault Response team

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Speaker 4: with our Prosecutor's office and said, we need to test

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Speaker 4: every single kit. We need to test all of them

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Speaker 4: going back, and we need to test every kit going forward.

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Speaker 3: According to the audit, Lake County identified a total of

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Speaker 3: two hundred and fifty seven untested kits and they determine

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Speaker 3: that two hundred and thirty eight of those kits should

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Speaker 3: be tested. So out of this two hundred and thirty

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Speaker 3: eight kits, how many of those kits have been tested?

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Speaker 1: Now?

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Speaker 4: All of them we had, Like I said, I know

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Speaker 4: I can speak for ham And Police Department for sure

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Speaker 4: because I spoke to that detective directly a while ago

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Speaker 4: about it. They were taking ten kits every week to

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Speaker 4: be tested until their backlog was done. And within the

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Speaker 4: first year after rape kit reform was passed, ham And

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Speaker 4: Police Department had cleared their backlog. So all two hundred

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Speaker 4: and thirty eight have been tested as of now.

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Speaker 3: And when you say taking ten kits, is that they're

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Speaker 3: like driving them to the lab where they do the

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Speaker 3: testing or yes.

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Speaker 4: Sir, every person who has possession of that kit, it

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Speaker 4: needs to be documented who had it and when, so

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Speaker 4: they have to personally drive that kit to our state lab,

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Speaker 4: which is about forty five minutes away. So now what

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Speaker 4: happens when somebody reports in Lake County? The law enforcement

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Speaker 4: agency who is handling the case now has seventy two

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Speaker 4: hours to pick up that kit from the medical facility

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Speaker 4: where it was done, and then the lab tests all

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Speaker 4: kits that come in on a first come, first serve basis.

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Speaker 4: So sometimes it may take five to six seven weeks

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Speaker 4: for the kit to be tested, but every kit is

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Speaker 4: tested now. And now our entire state has adopted a

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Speaker 4: tracking system, so when a victim is in the hospital

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Speaker 4: and getting that exam done, they are given a pin

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Speaker 4: number so that anytime the victim can go into the

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Speaker 4: database and see where her kit is so they can

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Speaker 4: look and see, Okay, it was picked up by law enforcement. Okay,

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Speaker 4: now it was dropped off at the lab. Okay, now

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Speaker 4: the lab is testing it.

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Speaker 3: So I think I was reading online that the original

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Speaker 3: plan was to dispose of kits that were like older

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Speaker 3: than ten years old unless the victim came forward and

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Speaker 3: specifically requested that their kit got tested. Do you know

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Speaker 3: what happened with that?

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Speaker 4: As far as my understanding, all kits up through twenty

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Speaker 4: oh seven were tested.

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Speaker 5: But I do know that some of our.

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Speaker 4: Jurisdictions in our county went back even further and just

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Speaker 4: tested all of their kits, So there were some that

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Speaker 4: were tested from prior to ten years.

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Speaker 5: Prior to that.

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Speaker 3: So some places went back and tested older kids. But

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Speaker 3: you're not sure about the details of that.

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Speaker 5: Oh, I'm not okay.

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Speaker 3: You know, I'm kind of curious about that, specifically with

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Speaker 3: the algorithm stuff, because you know, there might have been

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Speaker 3: this this serial killer active and kind of like the

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Speaker 3: nineties to early two thousands. You know, just be interesting

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Speaker 3: if if there were any kits from that period that

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Speaker 3: we're getting tested.

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Speaker 5: Absolutely.

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Speaker 4: Unfortunately I don't know personally, but I mean, if you

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Speaker 4: find out, let me know, because I've been following algorithms,

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Speaker 4: so this case is very interesting to me as well.

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Speaker 3: I asked doctor Lovell, the researcher that was involved in

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Speaker 3: Cleveland's sexual Assault kid initiative, whether destroying rape kits was common.

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Speaker 3: They said they would only test the kits going back

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Speaker 3: ten years, and that they were going to like throw

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Speaker 3: away their old kits unless victims came forward and said

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Speaker 3: that they wanted them still tested. And you know it

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Speaker 3: seems like costant basically nothing to keep those kits and

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Speaker 3: kind of you never know even if you don't have

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Speaker 3: the resources to do it. Now you know that things

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Speaker 3: will get cheaper and stuff like that.

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Speaker 6: Yeah, I think, and we've seen that as well, and

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Speaker 6: there's been some I think political. Maybe it was CNN,

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Speaker 6: I can't remember. Anyway, they did a pretty extensive analysis

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Speaker 6: of destroying rape kits and destroying evidence.

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Speaker 3: I found the article level was referring to. CNN had

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Speaker 3: surveyed over two hundred police departments across all fifty states

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Speaker 3: and found that almost half of them had destroyed some

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Speaker 3: untested kits. Sometimes these kids had been destroyed improperly, and

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Speaker 3: other times they're destroyed in accordance with policy.

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Speaker 6: I think you see that quite a bit, that law enforcement.

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Speaker 6: They all make their their own policies around how long

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Speaker 6: they keep evidence. Some of them are mandated now by states,

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Speaker 6: so Ohio now has uh I think it's the thirty

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Speaker 6: years that they have to keep biological evidence. But you know,

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Speaker 6: if they're following their practices, which they have you know,

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Speaker 6: written out, and they say, oh, we only keep things

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Speaker 6: ten years, otherwise we destroy it, I think some of

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Speaker 6: those practices need to be re examined, and that means

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Speaker 6: that you know, tax payers have to fit the bill

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Speaker 6: to provide more storage facilities. But you know that to

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Speaker 6: me doesn't seem like an insurmountable problem. And I think

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Speaker 6: if the technology for DNA is telling us anything, it's

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Speaker 6: that it's growing so fast and exponentially getting so much

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Speaker 6: better that you know what, we couldn't get a DNA

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Speaker 6: profile from now ten years from now, who knows. I mean,

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Speaker 6: look at what genealogy testing has done, you know. So

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Speaker 6: the thought that jurisdictions would just throw away evidence would

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Speaker 6: suggest to me that they somehow think that what they're

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Speaker 6: doing now has reached the pinnacle of all technology and

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Speaker 6: that their investigative practices at the time were the best

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Speaker 6: that they could possibly ever be, two things that I

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Speaker 6: think you just can't assume. And it's a little disconcerting

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Speaker 6: to hear about sort of putting all of the onus

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Speaker 6: onto victims to reach out to the department and say, hey,

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Speaker 6: I know I had this kit. I thought you tested it.

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Speaker 6: How was I to know you didn't test it? And

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Speaker 6: the cost of testing, by the way, as I said,

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Speaker 6: has gone down quite dramatically, So just the testing is

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Speaker 6: about five hundred dollars in Ohio, and then to have

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Speaker 6: someone you know read the results and write a report

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Speaker 6: is about another five hundred dollars. So you know, you're

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Speaker 6: really talking about one thousand dollars per kit, which in

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Speaker 6: the criminal justice system isn't a huge cost, you know,

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Speaker 6: relative to the outcomes.

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Speaker 3: I followed up with the Wake County Prosecutor's office to

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Speaker 3: see if they had more information about what had happened

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Speaker 3: to their older kids. I also wanted to know which

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Speaker 3: jurisdictions within Lake County had participated in the audit. And

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Speaker 3: I've been trying to get answers to these questions since

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Speaker 3: the first.

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Speaker 1: Week of July.

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Speaker 3: It's now the last week of August and I've still

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Speaker 3: heard nothing. And it's important to get answers to these questions.

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Speaker 3: When you claim you've solved your rape kit backlog, there's

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Speaker 3: a big difference between doing a proper accounting of all

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Speaker 3: backlog kits and testing them and doing a partial accounting

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Speaker 3: and then throwing away a substantial number of kits. After

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Speaker 3: radio silence from the Lake County Prosecutor's Office, I continued digging.

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Speaker 3: I came across another article about the initiative from the

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Speaker 3: Chicago Tribune. It mentions that out of the two hundred

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Speaker 3: and fifty seven kits found in the audit, one hundred

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Speaker 3: and ninety four were found in Hammond, thirty one in

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Speaker 3: East Chicago, and twenty two in Maryville. So if you

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Speaker 3: add up those numbers, two hundred and forty seven of

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Speaker 3: the kits were found from those jurisdictions alone. That leaves

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Speaker 3: a maximum of ten kits that could have been found

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Speaker 3: in Gary, despite the fact that Hammond found one hundred

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Speaker 3: and ninety four kits and they have an almost identical

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Speaker 3: population to Gary. I think the most parsimonious explanation here

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Speaker 3: is that Gary didn't participate in the audit, and it's

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Speaker 3: unclear to what extent they've kept backlog kits or tested them.

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Speaker 3: I was also curious about why Lake County had chosen

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Speaker 3: to destroy kits more than ten years old. That would

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Speaker 3: mean they would not include kids from two thousand and

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Speaker 3: seven or before. Interestingly, two thousand and seven is the

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Speaker 3: last year that Hargrove's algorithm observed an increase in unsolved strangulations,

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Speaker 3: and Vaughan was arrested the very next year. I wondered

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Speaker 3: at first whether ten years might be the statute of

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Speaker 3: limitations for rape in Indiana, but when I looked into it,

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Speaker 3: type one felony rape has no statute of limitations in Indiana,

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Speaker 3: So it's unclear to me why those kits would not

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Speaker 3: be preserved. But even if Lake County had retained and

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Speaker 3: tested all their kits, it wouldn't necessarily be able to

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Speaker 3: link Darren Vaughn to a homicide only to a sexual

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Speaker 3: assault because the twenty seventeen initiative in Indiana and most

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Speaker 3: of the initiatives to address rape kit backlogs don't include

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Speaker 3: DNA from homicide victims.

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Speaker 5: I do believe that.

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Speaker 4: This statewide audit was only for kits taken from a

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Speaker 4: victim in a hospital.

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Speaker 5: I don't know if any.

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Speaker 4: Of them were taken from homicide victims.

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Speaker 6: In Kyga County, if there was a murder rape, it

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Speaker 6: went to the homicide unit as compared to the sex

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Speaker 6: crimes unit. So if there was a rape, no homicide it,

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Speaker 6: it was investigated differently and went to different units. So

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Speaker 6: for the rape kits that we look at, there wasn't

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Speaker 6: murders as part of that. There were rape homicides, but

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Speaker 6: those were sort of in a different category.

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Speaker 3: Yeah, and so you guys didn't go back and look

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Speaker 3: at those homicide associated ones as well.

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Speaker 6: Not as part of the sexual salt kit initiative, but

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Speaker 6: I know that Kyga County Prosecutor's office might also be

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Speaker 6: looking at some of the rape homicides because there's funding

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Speaker 6: now at the federal level to do some of that doing.

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Speaker 6: I think what you're talking about here sort of expanding

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Speaker 6: out the scope of it.

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Speaker 3: In fact, last October, the Cuyahoga Prosecutor's Office announced that

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Speaker 3: it had received a million dollar grant from the US

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Speaker 3: Department of Justice to continue their sexual assault kit testing program,

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Speaker 3: and part of that grant includes a pilot project to

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Speaker 3: do forensic genealogy on thirty two samples from sexually motivated homicides.

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Speaker 3: Forensic genealogy is the technique that was used to catch

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Speaker 3: the Golden State killer. It doesn't just look for complete

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Speaker 3: matches with someone on the CODIS database, but looks for

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Speaker 3: partial matches and CODIS and public DNA databases to find

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Speaker 3: relatives of the perpetrator. Then genealogical techniques and further investigation

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Speaker 3: can be used to identify the offender. Other grants from

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Speaker 3: the Department of Justice or funding similar efforts to help

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Speaker 3: solve cold case homicides. It appears, though, that the emphasis

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Speaker 3: is on going back to cold cases where a DNA

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Speaker 3: profile of the perpetrator had already been generated, but that

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Speaker 3: they had never matched it to a suspect, and the

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Speaker 3: grants give money to use forensic genealogy to try to

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Speaker 3: find that match. I couldn't find any grants funding going

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Speaker 3: back and doing an accounting of all the cold case evidence.

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Speaker 3: Doctor Lovell wonders if an approach similar to Cuyahoga County's

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Speaker 3: sexual assault kit initiative might benefit homicide investigations as well.

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Speaker 6: Sachi, you know, as successful as it has been, I

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Speaker 6: think it shows that there's great value in going to

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Speaker 6: the cold cases in cold case homicides as well and

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Speaker 6: really trying to see is there evidence that could be tested.

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Speaker 6: Is there something in terms of genealogy that could be

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Speaker 6: done where all the evidence tested, you know, was it

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Speaker 6: tested using current techniques or was it only tested for zerology?

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Speaker 6: You know, things like that that they're starting to ask

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Speaker 6: those questions.

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Speaker 3: Last July, over a year ago now, I'd reached out

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Speaker 3: to the Lake County corners to try to find out

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Speaker 3: more information about the victims Hargrove had identified. I was

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Speaker 3: curious if DNA evidence was collected and if it was

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Speaker 3: ever tested and submitted to CODIS, the federal DNA database.

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Speaker 3: I was unable to get answers from the coroner's department

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Speaker 3: about these cases, perhaps because they were unsolved and therefore

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Speaker 3: still open. I'm not sure, but I wonder to what

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Speaker 3: extent older samples from cold cases have gone untested the

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Speaker 3: way rape kits were. I hope that DNA evidence from

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Speaker 3: old homicides like this have been preserved, and I hope

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Speaker 3: if they haven't been tested yet, one day they will

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Speaker 3: be investigating the algorithm and then Darren Vaughan has been

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Speaker 3: a roller coaster. It wasn't at all what I imagined

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Speaker 3: when I first began working on this project. And sometimes

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Speaker 3: I feel I've gotten so far off my original path

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Speaker 3: that I worry that I've gotten lost, that I'm missing

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Speaker 3: something big, or maybe missing the forest for the trees.

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Speaker 3: And sometimes I find myself wondering what's the point of

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Speaker 3: solving these cold cases in the first place. Of course,

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Speaker 3: they could potentially lead to the arrest of a violent criminal,

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Speaker 3: a perpetrator who might kill again. But if we're looking

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Speaker 3: specifically for a connection to Vaughan, then what's the point

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Speaker 3: if he's already serving life in prison. I was hoping

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Speaker 3: to find a connection to previous crimes to prove that

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Speaker 3: Hargrove's algorithm had predictive value, that it was able to

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Speaker 3: identify an active serial killer before the police did, and

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Speaker 3: therefore that it would be a valuable tool for law enforcement.

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Speaker 3: I think there's no doubt that the algorithm identified that

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Speaker 3: something very unusual was going on in Gary with its

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Speaker 3: identification of fifteen unsolved strangulations over a sixteen year period.

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Speaker 3: I think it's very possible that some of these murders

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Speaker 3: were the work of Vaughan or another serial killer. On

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Speaker 3: the other hand, Gary is a very unusual city where

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Speaker 3: many murders go unsolved, and it's a city full of

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Speaker 3: abandoned buildings where bodies can be hidden or even dumped

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Speaker 3: from homicides and other jurisdictions.

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Speaker 2: So is this algorithm perfect? No? Can it produce false results? Absolutely.

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Speaker 2: What we tell people always is what the algorithm does

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Speaker 2: is to identify clusters of murders that have an elevated

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Speaker 2: probability of containing serial murder. That just means if the

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Speaker 2: FBI says that serial murder occurs in less than one

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Speaker 2: percent of all homicides. We no longer believe that, but

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Speaker 2: that's the official reckoning for how common serial murder is. Well,

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Speaker 2: if less than one percent of murders are likely to

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Speaker 2: be serial, our algorithm will do better than that. It

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Speaker 2: will identify murders that have a better than one percent

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Speaker 2: probability of containing serial murders. It turns out way better

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Speaker 2: than one percent. We frequently are determining cases that are connected.

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Speaker 2: But there is a failure rate, and what are some

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Speaker 2: of the things that can go south on the algorithm.

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Speaker 2: If you have a police department that has a relentlessly

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Speaker 2: low clearance rate, like the Flint, Michigan Police Department, everything

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Speaker 2: looks serial because there's a low clearance rate for every

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Speaker 2: kind of murder, and there's not much you can do

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Speaker 2: about that. And that's a problem because we're becoming less

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Speaker 2: and less likely to solve a murder. In the United

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Speaker 2: States today, there are dozens of major cities where most

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Speaker 2: murders go unsolved. That means we're going to get false

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Speaker 2: positives because of the algorithm's technique. We're trying to overcome

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Speaker 2: those challenges, and we have actually We've made some improvements

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Speaker 2: in the methods, but it's a problem.

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Speaker 3: I want to look at the algorithm and the ways

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Speaker 3: it might be better used shortly, but first I want

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Speaker 3: to get hypothetical for a moment. Let's say we found

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Speaker 3: evidence that Vaughn was connected to one or more murders

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Speaker 3: on the algorithm's list, proof that Hargrove was right in

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Speaker 3: his twenty ten letter. What should police have done. Create

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Speaker 3: a task force to look into evidence that might connect

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Speaker 3: the crimes, notify the public, and what if police find

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Speaker 3: something more concrete, like DNA evidence or firearm forensics that

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Speaker 3: definitively link multiple murders, does the public have a right

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Speaker 3: to know that information, even though publicizing that information could

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Speaker 3: let the killer know the detectives are onto them. It

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Speaker 3: seems to me that in a situation like Vonn's twenty

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Speaker 3: fourteen murders and Gary, where the victims share characteristics, that

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Speaker 3: the police would have had some obligation to warn other

380
00:20:58,320 --> 00:21:01,639
Speaker 3: possible victims. But it's hard for the police to stop

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Speaker 3: a future homicide from taking place, and in the case

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Speaker 3: of Vaughn's twenty fourteen murders and Gary, police weren't even

383
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Speaker 3: aware of the murders until after Vaughn's arrest. There was

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Speaker 3: a strong suggestion that some of the victims, like Tira Batty,

385
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Speaker 3: had been murdered thanks to Marvin Clinton's own investigation, But

386
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Speaker 3: without discovering the bodies and submitting supplemental homicide reports to

387
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Speaker 3: the FBI, Hargrove's algorithm wouldn't have been able to detect

388
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Speaker 3: the cluster of Vonn's twenty fourteen crimes. That made me

389
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Speaker 3: curious about how many missing persons there are out there,

390
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Speaker 3: and how many of them are really homicide victims. So

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Speaker 3: I called up Todd Matthews and then to get the

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Speaker 3: levels on my end. Can you tell me what you

393
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Speaker 3: had for breakfast this morning?

394
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Speaker 1: I had coffee. I had about five cups of coffee today.

395
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Speaker 1: I'm like a snake, ill like it once a day.

396
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Speaker 1: Just ate something nice and solid.

397
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Speaker 3: After he helped identify it Jane Doe through webslew Thing,

398
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Speaker 3: Matthews founded the Dough Network in nineteen ninety nine. It

399
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Speaker 3: was a national database for missing persons and also unidentified bodies,

400
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Speaker 3: with the hopes of connecting John and Jane Doe's to

401
00:22:07,359 --> 00:22:12,119
Speaker 3: missing person reports. Similar to Hargrove, Matthews realized that police

402
00:22:12,119 --> 00:22:15,239
Speaker 3: departments struggle with solving these kinds of cases, So we

403
00:22:15,320 --> 00:22:17,800
Speaker 3: decided to create the Dough Network as a tool to

404
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Speaker 3: help police officers and amateur slews with their investigations.

405
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Speaker 1: That person could be alive and well, you don't know

406
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Speaker 1: their circumstances. Some people it's mental illness, some it's dementia,

407
00:22:29,600 --> 00:22:32,879
Speaker 1: drug abuse. Sometimes an accident, sometimes it's murdered. You just

408
00:22:32,920 --> 00:22:33,760
Speaker 1: never know what you're going.

409
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Speaker 3: To get In almost a decade after Matthews created the

410
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Speaker 3: Dough Network, the Department of Justice decided they wanted to

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Speaker 3: make their own official version called NamUs. That's nam us,

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Speaker 3: and they brought in Matthews to help.

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Speaker 1: The Department of Justice actually first contacted me with NamUs

414
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Speaker 1: in two thousand and seven to help them do what

415
00:22:54,800 --> 00:22:56,560
Speaker 1: DO Network proved was possible.

416
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Speaker 3: Like the DO Network, nemusless information like a missing person's demographics,

417
00:23:01,840 --> 00:23:04,600
Speaker 3: when and where they were last seen, and a description

418
00:23:04,800 --> 00:23:08,320
Speaker 3: of the circumstances of how they want missing. All that

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00:23:08,520 --> 00:23:12,359
Speaker 3: is available to the public. But with NAMIS, detectives working

420
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Speaker 3: on the case can log in and access additional items

421
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Speaker 3: the evidence.

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Speaker 1: You know, something that though network wouldn't necessarily have its

423
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Speaker 1: hands on like the dental records, DNA fingerprint analysis.

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Speaker 3: Do you have a sense of kind of to what

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Speaker 3: extent technology is being used in terms of police checking

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Speaker 3: cell phone records or credit card records, things like that.

427
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Speaker 1: You do see a lot of that, you know, pinging

428
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Speaker 1: the cell phone and then if a cell phone's been disabled.

429
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Speaker 1: You know, that kind of leads you to think of

430
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Speaker 1: foul play possibly, But it is getting better as far

431
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Speaker 1: if you if you swipe a card or carry a phone.

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Speaker 1: It's hard to go missing. It's not easy to be

433
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Speaker 1: a missing person and still work a sleep, you know,

434
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Speaker 1: do something. It's it's hard to make yourself missing on

435
00:23:57,320 --> 00:24:00,080
Speaker 1: purpose now, for the good or the bad. It's just

436
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Speaker 1: harder to do it. And but it's going to happen.

437
00:24:03,080 --> 00:24:04,479
Speaker 1: You know, people are going to be able to get

438
00:24:04,480 --> 00:24:06,719
Speaker 1: around some of those things. They truly want to be missing.

439
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Speaker 1: And that's where some of the privacy concerns come in.

440
00:24:08,960 --> 00:24:10,840
Speaker 1: You know, if I want to go missing, can I

441
00:24:11,760 --> 00:24:13,840
Speaker 1: is it morally okay for me to just allow my

442
00:24:13,920 --> 00:24:16,040
Speaker 1: family to think that I'm you know, I don't know

443
00:24:16,080 --> 00:24:18,600
Speaker 1: where I am. Yeah, a lot of issues, a lot

444
00:24:18,639 --> 00:24:19,720
Speaker 1: of things to think about.

445
00:24:20,359 --> 00:24:22,760
Speaker 3: This podcast is kind of looking into the work of

446
00:24:22,800 --> 00:24:26,760
Speaker 3: this serial killer, and he was caught for one murder,

447
00:24:27,040 --> 00:24:30,479
Speaker 3: confessed to six more murders, and led the police to

448
00:24:30,520 --> 00:24:33,760
Speaker 3: their bodies. You know, some of them had been reported

449
00:24:33,800 --> 00:24:37,880
Speaker 3: missing at that point. Others hadn't even been reported missing.

450
00:24:38,680 --> 00:24:43,600
Speaker 3: I guess I'm curious of just like, how how good

451
00:24:43,639 --> 00:24:46,520
Speaker 3: of a sense do we have of how big this

452
00:24:46,680 --> 00:24:51,080
Speaker 3: problem actually is, and kind of are we doing everything

453
00:24:51,399 --> 00:24:54,719
Speaker 3: we can be doing to keep track of this stuff

454
00:24:54,760 --> 00:24:55,759
Speaker 3: and monitor it.

455
00:24:56,280 --> 00:24:58,719
Speaker 1: Well, it's a silent mass disaster. It's called the nation's

456
00:24:58,720 --> 00:25:02,399
Speaker 1: silent mass disaster because of the time frames the distances.

457
00:25:03,680 --> 00:25:07,200
Speaker 3: According to NIMUS, there are currently over twenty thousand missing

458
00:25:07,240 --> 00:25:10,439
Speaker 3: person cases is. Some of those will be resolved quickly

459
00:25:10,680 --> 00:25:13,759
Speaker 3: with the missing person found alive and safe, but some

460
00:25:14,000 --> 00:25:16,479
Speaker 3: are people who have been killed but their body was

461
00:25:16,520 --> 00:25:19,600
Speaker 3: never found where if it was found, they're a John

462
00:25:19,760 --> 00:25:23,480
Speaker 3: or Jane Doe waiting to be identified. But Matthew says

463
00:25:23,480 --> 00:25:27,800
Speaker 3: the database isn't yet comprehensive. Whether cases get entered into

464
00:25:27,879 --> 00:25:31,600
Speaker 3: NAMIS varies from state to state and jurisdiction to jurisdiction.

465
00:25:32,600 --> 00:25:35,520
Speaker 1: My homestead of Tennessee, I work with local officials and

466
00:25:35,680 --> 00:25:38,199
Speaker 1: in thirty days in Tennessee, you're supposed to go if

467
00:25:38,200 --> 00:25:41,960
Speaker 1: you're missing or unidentified in Tennessee within thirty days, you're

468
00:25:42,000 --> 00:25:44,600
Speaker 1: supposed to go on the name of this website. Now, whether

469
00:25:44,639 --> 00:25:49,240
Speaker 1: that happens or not, you know, there's no punishment phase

470
00:25:49,399 --> 00:25:52,199
Speaker 1: or not. And the requiring of use of names in

471
00:25:52,240 --> 00:25:55,880
Speaker 1: state law actually does other things. It begins a training

472
00:25:55,920 --> 00:25:58,880
Speaker 1: process with law enforcements, so it now will be part

473
00:25:58,879 --> 00:26:01,399
Speaker 1: of the training academies so that they know the laws

474
00:26:01,399 --> 00:26:04,600
Speaker 1: that are required. And eventually, you know, things will change,

475
00:26:04,879 --> 00:26:06,600
Speaker 1: and I think we planned a lot of stats that

476
00:26:06,600 --> 00:26:08,760
Speaker 1: are going to grow and evolve knowledge. It's going to

477
00:26:08,760 --> 00:26:10,960
Speaker 1: get better, and I think we're all going to get

478
00:26:10,960 --> 00:26:13,560
Speaker 1: better at it. It just seems like it takes so long.

479
00:26:13,720 --> 00:26:16,679
Speaker 1: If you're the family member of a missing you know,

480
00:26:16,760 --> 00:26:20,280
Speaker 1: two seconds is a very painful time period. You know,

481
00:26:20,320 --> 00:26:24,399
Speaker 1: there's probably nothing more scary than having a missing family

482
00:26:24,440 --> 00:26:26,399
Speaker 1: member and you have no control over it. You have

483
00:26:26,440 --> 00:26:29,720
Speaker 1: no idea if they're alive, they're dead, they're hungry, they're cold.

484
00:26:30,399 --> 00:26:31,919
Speaker 1: You know, you have no idea of what to do

485
00:26:32,040 --> 00:26:34,040
Speaker 1: or even word again looking you know, that's probably one

486
00:26:34,080 --> 00:26:37,160
Speaker 1: of the most helpless feelings as described to me people

487
00:26:37,200 --> 00:26:41,000
Speaker 1: that have done it all been described very similarly, the

488
00:26:41,040 --> 00:26:44,560
Speaker 1: most helpless feeling that they've ever had. You know, I've

489
00:26:44,560 --> 00:26:46,639
Speaker 1: had people I've known for years and they know of

490
00:26:46,720 --> 00:26:51,080
Speaker 1: my work and recognize and appreciate it, and then suddenly

491
00:26:51,480 --> 00:26:56,960
Speaker 1: they're in that situation. That's when things change dramatically. You know,

492
00:26:58,320 --> 00:27:00,479
Speaker 1: you don't know until you're sitting in that chair, you

493
00:27:00,560 --> 00:27:03,600
Speaker 1: don't know how bad it can be. Literally, there's a

494
00:27:03,639 --> 00:27:06,759
Speaker 1: local missing person and I've known the boy's aunt for

495
00:27:06,800 --> 00:27:09,760
Speaker 1: more than twenty years. Now I hear from her more frequently.

496
00:27:10,119 --> 00:27:12,360
Speaker 1: They're looking for him. He's a young adult, he's had

497
00:27:12,359 --> 00:27:17,119
Speaker 1: some drug issues, and he might not necessarily be on

498
00:27:17,159 --> 00:27:20,679
Speaker 1: the top of the list for law enforcement to look for. Yeah,

499
00:27:20,760 --> 00:27:23,879
Speaker 1: it doesn't change her situation. He's still her nephew and

500
00:27:23,920 --> 00:27:26,600
Speaker 1: she wants him found. Now. I don't blame her. And

501
00:27:27,840 --> 00:27:29,760
Speaker 1: it's just by the time you realize how bad it

502
00:27:29,760 --> 00:27:33,760
Speaker 1: can be, you're probably already snake bit, you know.

503
00:27:35,040 --> 00:27:36,639
Speaker 3: And when you say, like, not at the top of

504
00:27:36,639 --> 00:27:39,520
Speaker 3: the list for law enforcement to look for, what what

505
00:27:39,560 --> 00:27:40,119
Speaker 3: do you mean by that?

506
00:27:41,159 --> 00:27:43,639
Speaker 1: Well, a lot of times if somebody has had some trouble,

507
00:27:43,639 --> 00:27:45,719
Speaker 1: it's just like, well are they missing or they just

508
00:27:45,760 --> 00:27:49,440
Speaker 1: stand out of the way, have they done something? Are

509
00:27:49,480 --> 00:27:52,600
Speaker 1: they hiding out for some reason? So it's just hard

510
00:27:52,600 --> 00:27:55,000
Speaker 1: to sometimes see somebody that they might recognize as a

511
00:27:55,040 --> 00:27:57,840
Speaker 1: criminal as a vulnerable victim. Now, I know the local

512
00:27:57,840 --> 00:28:01,119
Speaker 1: boy that's missing, he has a really bad case of

513
00:28:01,200 --> 00:28:04,560
Speaker 1: diabetes and he cannot survive with that medication. So unless

514
00:28:04,560 --> 00:28:07,800
Speaker 1: he's found some way to buy medication some were he

515
00:28:07,800 --> 00:28:10,199
Speaker 1: can't have survived. And his family knows that. So where's

516
00:28:10,200 --> 00:28:14,879
Speaker 1: he at? So now into like day sixty five of

517
00:28:14,920 --> 00:28:18,760
Speaker 1: his disappearance, the family realized that he can't survive. He's

518
00:28:18,760 --> 00:28:21,800
Speaker 1: not come back to them, and it's getting way down

519
00:28:21,840 --> 00:28:25,200
Speaker 1: the line now, you know. Now it's recovery of remains

520
00:28:25,280 --> 00:28:28,720
Speaker 1: instead of finding somebody potentially in a bad situation.

521
00:28:29,840 --> 00:28:34,040
Speaker 3: Does that police attitude frustrate you or do you think

522
00:28:34,040 --> 00:28:36,920
Speaker 3: that that is just kind of the way that it is.

523
00:28:37,840 --> 00:28:39,360
Speaker 1: It is the way that it is. It does get

524
00:28:39,360 --> 00:28:43,240
Speaker 1: frustrating at time, especially when you know somebody like this person.

525
00:28:43,280 --> 00:28:45,800
Speaker 1: I knew that family, and it's always this my son

526
00:28:45,920 --> 00:28:48,440
Speaker 1: and never do that. Yeah, will my daughter didn't have

527
00:28:48,440 --> 00:28:51,000
Speaker 1: a tattoo? Maybe she did, you just didn't know about it.

528
00:28:51,040 --> 00:28:53,280
Speaker 1: So you're going to hear somebody say my child would

529
00:28:53,400 --> 00:28:56,160
Speaker 1: never do that. My adult child would never, ever, ever

530
00:28:56,240 --> 00:28:59,160
Speaker 1: ever not call me. And most of the time it's

531
00:28:59,160 --> 00:29:01,800
Speaker 1: just like, well, maybe it is possible. But then when

532
00:29:01,800 --> 00:29:04,000
Speaker 1: you do know people and you know who they are

533
00:29:04,120 --> 00:29:06,720
Speaker 1: and their story is really making sense, and it's like, yeah,

534
00:29:06,800 --> 00:29:11,280
Speaker 1: you're you're right. Probably would not be without medication for

535
00:29:11,400 --> 00:29:14,719
Speaker 1: this period of time, So something's wrong. Even though he

536
00:29:14,800 --> 00:29:17,040
Speaker 1: might have done things that put him on the wrong

537
00:29:17,040 --> 00:29:20,280
Speaker 1: side of the law, ultimately he is in danger. So

538
00:29:20,320 --> 00:29:22,360
Speaker 1: we have to think about this differently. So it is

539
00:29:22,400 --> 00:29:25,160
Speaker 1: frustrating at times, but understand because when I was with

540
00:29:25,240 --> 00:29:28,680
Speaker 1: Department of Justice with NamUs, the volume of people reaching

541
00:29:28,720 --> 00:29:31,280
Speaker 1: out can be overwhelming. So I can see how you

542
00:29:31,320 --> 00:29:35,280
Speaker 1: can quickly get frustrated getting multiple calls, and we have

543
00:29:35,360 --> 00:29:37,280
Speaker 1: to make it easier to do. We have to make

544
00:29:37,320 --> 00:29:39,640
Speaker 1: more tools available to the family. They can enter their

545
00:29:39,680 --> 00:29:42,120
Speaker 1: own missing person case and name us. They can start

546
00:29:42,160 --> 00:29:45,080
Speaker 1: the ball rolling, so instead of waiting for law enforcement

547
00:29:45,080 --> 00:29:47,200
Speaker 1: to it, they can start the process. They'll have to

548
00:29:47,240 --> 00:29:49,600
Speaker 1: be validated, but at least it gives them something to

549
00:29:49,600 --> 00:29:52,440
Speaker 1: do instead of waiting for somebody to come and help them.

550
00:29:52,480 --> 00:29:55,600
Speaker 1: They can start the process. Because when you're getting validation

551
00:29:55,760 --> 00:29:58,320
Speaker 1: reports coming back from a program that's developed by the

552
00:29:58,320 --> 00:30:00,239
Speaker 1: Department of Justice. I mean, I think they're not just

553
00:30:00,280 --> 00:30:03,240
Speaker 1: going to tell Justice Agency how they'll be bad. We're

554
00:30:03,240 --> 00:30:04,720
Speaker 1: not going to look for him, you know. I think

555
00:30:04,840 --> 00:30:07,120
Speaker 1: once they see that, we don't really need you to

556
00:30:07,160 --> 00:30:09,920
Speaker 1: create a profile. US has a profile kind of takes

557
00:30:09,920 --> 00:30:12,680
Speaker 1: a little bit out of their control and has that helped.

558
00:30:12,800 --> 00:30:15,880
Speaker 1: It has helped, It's helped tremendously as it cleared it

559
00:30:15,960 --> 00:30:16,680
Speaker 1: up completely.

560
00:30:16,880 --> 00:30:21,160
Speaker 3: No, when you kind of like look really big picture,

561
00:30:21,200 --> 00:30:24,720
Speaker 3: is there a direction that we're heading with technology or

562
00:30:24,760 --> 00:30:26,720
Speaker 3: the way we investigate stuff.

563
00:30:26,720 --> 00:30:29,560
Speaker 1: It's only going to improve ultimately. You know, it's going

564
00:30:29,600 --> 00:30:33,280
Speaker 1: to be quicker to do the DNA test, encouraging the families.

565
00:30:33,360 --> 00:30:35,360
Speaker 1: Like every at one point in time, every singer at

566
00:30:35,360 --> 00:30:38,040
Speaker 1: my local high school's fingerprinted because I will go and

567
00:30:38,120 --> 00:30:40,480
Speaker 1: bring local law enforcement in the forensic class and will

568
00:30:40,520 --> 00:30:42,640
Speaker 1: thumb print everybody or fingerprintedy rdy to get a ten

569
00:30:42,760 --> 00:30:45,520
Speaker 1: print and then you know, you put it away and

570
00:30:45,720 --> 00:30:47,600
Speaker 1: God forbid, I hope I never have to see it again.

571
00:30:48,360 --> 00:30:50,640
Speaker 1: So there's there's lots of things that can be done,

572
00:30:50,640 --> 00:30:52,479
Speaker 1: but I mean it's at some price. You know, you

573
00:30:52,520 --> 00:30:54,800
Speaker 1: are going to have to think about things that make

574
00:30:54,840 --> 00:30:57,080
Speaker 1: you uncomfortable, and you know, thinking of a person that

575
00:30:57,200 --> 00:30:59,920
Speaker 1: might be deceased, and that's not what you want, but

576
00:31:00,040 --> 00:31:02,600
Speaker 1: it is what it is. We're all going to die eventually,

577
00:31:02,760 --> 00:31:05,880
Speaker 1: and I think we can accept a natural death. It's

578
00:31:05,960 --> 00:31:09,960
Speaker 1: just we're not programmed to have a missing person. There's

579
00:31:09,960 --> 00:31:13,840
Speaker 1: no funeral, there's no closure, there's no explanation for it.

580
00:31:13,960 --> 00:31:16,880
Speaker 1: There's no way to process. I've seen families grow stronger

581
00:31:16,920 --> 00:31:18,840
Speaker 1: as a result of it, and then they go on

582
00:31:18,920 --> 00:31:22,080
Speaker 1: to pass state laws and advocate and make sure nobody

583
00:31:22,080 --> 00:31:25,560
Speaker 1: suffers what they suffer. I've seen other families deteriorate because

584
00:31:25,600 --> 00:31:28,240
Speaker 1: of it because there's no way to move on. It

585
00:31:28,440 --> 00:31:31,600
Speaker 1: just can be devastating. I had a local lady that

586
00:31:31,720 --> 00:31:34,000
Speaker 1: her son's been missing for many years and she wanted

587
00:31:34,040 --> 00:31:38,520
Speaker 1: to show me something. She tuk me to the grave.

588
00:31:38,880 --> 00:31:40,880
Speaker 1: She actually had a tombstone put up for her son

589
00:31:40,960 --> 00:31:43,120
Speaker 1: next to her and her husband. She goes, if we're gone,

590
00:31:44,120 --> 00:31:46,560
Speaker 1: can you make sure he's buried here? If his body's found.

591
00:31:47,040 --> 00:31:50,160
Speaker 1: She's given up. You know, she's she knows that she's

592
00:31:50,200 --> 00:31:52,440
Speaker 1: at the end, and she's getting older, and you know

593
00:31:52,440 --> 00:31:54,040
Speaker 1: it's going to become more and more difficult for her

594
00:31:54,080 --> 00:31:56,320
Speaker 1: to try to find, and her hope of finding him

595
00:31:56,400 --> 00:31:59,480
Speaker 1: during her lifetime is fading, and she only ones now

596
00:31:59,600 --> 00:32:01,320
Speaker 1: is can you make sure he's buried here? Will you

597
00:32:01,360 --> 00:32:03,600
Speaker 1: let him know our wishes? I don't want him lay

598
00:32:03,600 --> 00:32:06,120
Speaker 1: in a lab in a box. You know, I can say,

599
00:32:06,160 --> 00:32:08,840
Speaker 1: you know what, I'll do everything in Yeah, I know

600
00:32:08,880 --> 00:32:12,400
Speaker 1: your wishes and I'll make them known. You know. I

601
00:32:12,440 --> 00:32:14,560
Speaker 1: have to think about will I even be around when

602
00:32:14,600 --> 00:32:17,120
Speaker 1: his body's found? If it's found, so I think the

603
00:32:17,160 --> 00:32:20,280
Speaker 1: best way to do is to tell that story, mention

604
00:32:20,400 --> 00:32:24,680
Speaker 1: it somewhere, and then you know, that's it. You just

605
00:32:24,720 --> 00:32:25,520
Speaker 1: have to share.

606
00:32:40,320 --> 00:32:43,680
Speaker 3: When I began researching this show, I asked myself the question,

607
00:32:44,400 --> 00:32:48,520
Speaker 3: with all the data we're collecting, storing, sorting, why is

608
00:32:48,560 --> 00:32:52,080
Speaker 3: it that we're getting worse at solving homicides When it

609
00:32:52,120 --> 00:32:55,280
Speaker 3: comes to policing. We are starting to do more with data,

610
00:32:55,440 --> 00:32:57,440
Speaker 3: but we're not really doing it in any kind of

611
00:32:57,480 --> 00:33:01,240
Speaker 3: systematic way. I think it's reasonable to worry about new

612
00:33:01,280 --> 00:33:05,400
Speaker 3: technologies like facial recognition, that they might be moving our

613
00:33:05,440 --> 00:33:08,880
Speaker 3: country towards some sort of surveillance state. But I think

614
00:33:08,920 --> 00:33:12,360
Speaker 3: the real nightmare right now is much more banal. We're

615
00:33:12,360 --> 00:33:15,760
Speaker 3: missing important connections we could be making and letting killers

616
00:33:15,800 --> 00:33:19,040
Speaker 3: go free. One of the things that surprised me about

617
00:33:19,080 --> 00:33:23,040
Speaker 3: Hargrove's algorithm was how simple it was. This wasn't some

618
00:33:23,080 --> 00:33:26,640
Speaker 3: sort of deep learning neural network getting fed mountains of data.

619
00:33:27,400 --> 00:33:31,960
Speaker 3: It was a simple, handcrafted algorithm getting basic demographic information

620
00:33:32,000 --> 00:33:35,479
Speaker 3: about the victims along with the method of killing year

621
00:33:35,560 --> 00:33:39,360
Speaker 3: in jurisdiction. And you can imagine that with richer data

622
00:33:39,520 --> 00:33:43,520
Speaker 3: and a more involved algorithm, patterns might emerge more clearly.

623
00:33:44,120 --> 00:33:47,440
Speaker 3: In fact, Hargrove has been working on an updated algorithm.

624
00:33:47,920 --> 00:33:50,320
Speaker 3: I know you said, you know that you're still in

625
00:33:50,360 --> 00:33:53,920
Speaker 3: publication for the algorithm two point zero. Is there anything

626
00:33:53,960 --> 00:33:55,040
Speaker 3: you can talk about that.

627
00:33:55,360 --> 00:33:57,680
Speaker 2: We want to get into a peer review journal, and

628
00:33:57,760 --> 00:34:01,239
Speaker 2: so we're still writing. I can tell you that what

629
00:34:01,400 --> 00:34:06,040
Speaker 2: is different about the newer version of the algorithm is

630
00:34:06,160 --> 00:34:12,400
Speaker 2: it dynamic evaluates each murder. What the old algorithm did

631
00:34:12,480 --> 00:34:15,840
Speaker 2: was just to create a group and then to assess

632
00:34:15,960 --> 00:34:19,240
Speaker 2: what the clearance rate was for the group. The new

633
00:34:19,400 --> 00:34:24,520
Speaker 2: algorithm individually assesses each murder and then decides whether or

634
00:34:24,600 --> 00:34:28,560
Speaker 2: not that murder looks suspicious and that individual assessment is

635
00:34:29,000 --> 00:34:32,160
Speaker 2: better and so it definitely is an improvement over the

636
00:34:32,200 --> 00:34:35,759
Speaker 2: old and so once we get it published, we'll make

637
00:34:35,800 --> 00:34:39,840
Speaker 2: it available. But we need that confirmation that we're onto something,

638
00:34:39,920 --> 00:34:42,600
Speaker 2: and so we need others to look at it. And

639
00:34:42,719 --> 00:34:45,920
Speaker 2: right now we're struggling with following the format for pure

640
00:34:46,000 --> 00:34:51,600
Speaker 2: reviewed publications. And apparently one of our reviewers is a

641
00:34:51,640 --> 00:34:55,880
Speaker 2: former cop and took offense to what we did. I

642
00:34:55,920 --> 00:34:59,520
Speaker 2: guess he or she thought that the algorithm made police

643
00:34:59,560 --> 00:35:03,480
Speaker 2: look bad. I don't understand that, because we've got several

644
00:35:03,520 --> 00:35:06,960
Speaker 2: former cops on the list of authors with this project,

645
00:35:08,160 --> 00:35:10,640
Speaker 2: that it's not our intent to ever make law enforcement

646
00:35:10,640 --> 00:35:13,800
Speaker 2: look bad. We're just trying to provide a new tool

647
00:35:13,880 --> 00:35:14,680
Speaker 2: and the toolkit.

648
00:35:16,279 --> 00:35:19,879
Speaker 3: I'm hoping that a bunch of people listen to this podcast,

649
00:35:20,000 --> 00:35:24,440
Speaker 3: and some of them might be data scientists or people

650
00:35:24,560 --> 00:35:27,880
Speaker 3: like that. And I was curious, if someone wants to

651
00:35:27,920 --> 00:35:30,799
Speaker 3: help you with this kind of work, they have some

652
00:35:30,920 --> 00:35:33,400
Speaker 3: idea of something they want to try with the data,

653
00:35:33,840 --> 00:35:35,560
Speaker 3: is that something you're interested in.

654
00:35:35,920 --> 00:35:39,479
Speaker 2: We make our data available. If you go to murder

655
00:35:39,640 --> 00:35:43,360
Speaker 2: data dot org and go to the data and docs tab,

656
00:35:44,000 --> 00:35:49,359
Speaker 2: you can download everything, absolutely everything, the original algorithm and

657
00:35:49,440 --> 00:35:53,239
Speaker 2: the raw data, and we encourage folks to use the

658
00:35:53,320 --> 00:35:55,959
Speaker 2: data and see if they can come up with something useful.

659
00:35:56,279 --> 00:35:58,719
Speaker 2: We are hoping that someone may be able to get

660
00:35:58,800 --> 00:36:03,600
Speaker 2: artificial intelligence to do clever things with these records. So far,

661
00:36:04,040 --> 00:36:07,200
Speaker 2: all attempts that have been made have not been successful,

662
00:36:07,279 --> 00:36:10,840
Speaker 2: but that doesn't mean something good mightn't happen in the future.

663
00:36:11,520 --> 00:36:15,280
Speaker 2: So we're hoping that bright people will take free data

664
00:36:15,960 --> 00:36:17,960
Speaker 2: and see if they can come up with something clever.

665
00:36:20,400 --> 00:36:22,960
Speaker 3: At the beginning of the podcast, I also mentioned as

666
00:36:22,960 --> 00:36:26,880
Speaker 3: startling statistic that homicides today are being cleared at a

667
00:36:27,000 --> 00:36:31,439
Speaker 3: much lower rate than in previous decades. No one knows

668
00:36:31,480 --> 00:36:35,600
Speaker 3: exactly why the clearance rate for homicides is decreasing, but

669
00:36:35,719 --> 00:36:37,120
Speaker 3: Hargarve has some ideas.

670
00:36:37,600 --> 00:36:42,799
Speaker 2: Murder begets murder, and unsolved murder really begets murder. When

671
00:36:42,880 --> 00:36:47,080
Speaker 2: most killings go unsolved, there starts to develop a narrative

672
00:36:47,120 --> 00:36:49,440
Speaker 2: that the only way I'm going to get justice for

673
00:36:49,560 --> 00:36:52,000
Speaker 2: my loved ones is to take the law into my

674
00:36:52,040 --> 00:36:56,920
Speaker 2: own hands. Also, murderers who walk the street are available

675
00:36:56,920 --> 00:36:59,200
Speaker 2: to kill again. Why wouldn't they they got away with

676
00:36:59,279 --> 00:37:03,400
Speaker 2: it the first time. We are convinced that serial murder

677
00:37:03,440 --> 00:37:06,640
Speaker 2: is much much more common than anyone ever dreamed of,

678
00:37:07,279 --> 00:37:11,200
Speaker 2: even in their ninth Mars. Now, that's not to say

679
00:37:11,279 --> 00:37:15,000
Speaker 2: that serial sexual murder is on the rise. It's not.

680
00:37:15,840 --> 00:37:19,239
Speaker 2: The traditional Hollywood kind of serial killer is definitely on

681
00:37:19,279 --> 00:37:24,240
Speaker 2: the decline. But the statistical serial killer, anyone who kills

682
00:37:24,279 --> 00:37:27,680
Speaker 2: two or more people in separate incidents, that really is

683
00:37:27,840 --> 00:37:32,760
Speaker 2: is certainly more common than is recognized. It is quite

684
00:37:33,200 --> 00:37:36,839
Speaker 2: likely that the most common type of serial murder is

685
00:37:36,920 --> 00:37:41,239
Speaker 2: the gang enforcer on a local street gang. How many

686
00:37:41,239 --> 00:37:45,799
Speaker 2: of those killings get solved? I mean, increasingly, people who

687
00:37:45,800 --> 00:37:48,680
Speaker 2: have gotten an adept at committing murder and getting away

688
00:37:48,719 --> 00:37:54,280
Speaker 2: with it are just getting away with it. We believe

689
00:37:54,360 --> 00:37:59,400
Speaker 2: that the decline in homicide clearance rate is primarily driven

690
00:37:59,880 --> 00:38:04,280
Speaker 2: by a lack of leadership, a lack of public passion

691
00:38:04,480 --> 00:38:08,680
Speaker 2: that murders should be solved, a lack of re sources

692
00:38:08,719 --> 00:38:14,399
Speaker 2: for homicide detectives, a lack of accountability. The clearance rate

693
00:38:14,440 --> 00:38:19,920
Speaker 2: for homicides should be a metric that policymakers carefully follow

694
00:38:20,120 --> 00:38:23,040
Speaker 2: in determining whether or not a police department is effective.

695
00:38:24,000 --> 00:38:28,120
Speaker 2: When mayors of cities pledge to get a handle on

696
00:38:28,160 --> 00:38:32,440
Speaker 2: their murder problem, generally speaking, the murder rate starts to drop.

697
00:38:33,120 --> 00:38:37,759
Speaker 2: Improved clearance rates will reduce the rate of which murder occurs.

698
00:38:38,520 --> 00:38:43,120
Speaker 2: It's not easy and it's not cheap. Increasingly there's a

699
00:38:43,120 --> 00:38:48,480
Speaker 2: competition for limited resources in major cities. Many cities cannot

700
00:38:48,480 --> 00:38:51,920
Speaker 2: afford their pension plan. I mean, the fiscal challenges for

701
00:38:52,000 --> 00:38:57,040
Speaker 2: modern government are becoming extreme. We in America have to

702
00:38:57,040 --> 00:39:02,560
Speaker 2: make major crimes a higher priority. We cannot dismiss murders

703
00:39:02,600 --> 00:39:05,800
Speaker 2: because well, just the kinds of people that get murdered

704
00:39:05,840 --> 00:39:08,400
Speaker 2: I don't care about, which I'm afraid maybe part of

705
00:39:08,440 --> 00:39:12,439
Speaker 2: the dreadful calculus as to what's happened. It is our

706
00:39:12,480 --> 00:39:15,720
Speaker 2: hope at the Murder Accountability Project that our data become

707
00:39:15,800 --> 00:39:19,279
Speaker 2: a political force. That people can look up the rate

708
00:39:19,320 --> 00:39:22,279
Speaker 2: at which murders are cleared in their communities, and if

709
00:39:22,279 --> 00:39:23,839
Speaker 2: they don't like what they see, they should have a

710
00:39:23,880 --> 00:39:27,640
Speaker 2: conversation with their mayor and their city council members. That

711
00:39:28,080 --> 00:39:31,400
Speaker 2: unsolved murder is simply unacceptable.

712
00:39:31,360 --> 00:39:34,640
Speaker 3: And Hargrove's analysis of the declining clearance rate for murder

713
00:39:35,040 --> 00:39:37,800
Speaker 3: shows that it is driven by homicides where the victim

714
00:39:37,880 --> 00:39:38,360
Speaker 3: is black.

715
00:39:38,960 --> 00:39:43,640
Speaker 2: The entirety of that declining homicide clearance rate was born

716
00:39:44,040 --> 00:39:50,200
Speaker 2: by African American victims. In cases of Caucasian murder, Asian murder,

717
00:39:50,400 --> 00:39:54,759
Speaker 2: Native American murder, those murders are about as likely to

718
00:39:54,800 --> 00:39:58,640
Speaker 2: be solved today as they were fifty years ago. That's

719
00:39:59,000 --> 00:40:01,799
Speaker 2: just a fact, and we should never ignore what the

720
00:40:01,880 --> 00:40:04,640
Speaker 2: data show us today.

721
00:40:04,840 --> 00:40:07,479
Speaker 3: If your loved one is murdered and they're white, there's

722
00:40:07,560 --> 00:40:10,080
Speaker 3: over a six seventy five percent chance someone will be

723
00:40:10,160 --> 00:40:13,839
Speaker 3: arrested for the crime. If they're black, the chance someone

724
00:40:13,880 --> 00:40:18,080
Speaker 3: will be arrested drops below sixty percent, And the chance

725
00:40:18,080 --> 00:40:21,919
Speaker 3: of being murdered is much higher for Black Americans, particularly

726
00:40:22,040 --> 00:40:26,160
Speaker 3: young black men. As I mold over these statistics, I

727
00:40:26,239 --> 00:40:29,239
Speaker 3: kept thinking back to my interview with Kerrie Rice, the

728
00:40:29,279 --> 00:40:33,319
Speaker 3: police officer who responded to Vaughan's gasoline incident. When I

729
00:40:33,360 --> 00:40:36,120
Speaker 3: googled him, I saw an article about how one of

730
00:40:36,120 --> 00:40:37,920
Speaker 3: his sons had been shot and killed.

731
00:40:38,759 --> 00:40:38,920
Speaker 2: You know.

732
00:40:39,000 --> 00:40:41,680
Speaker 3: I saw that your family has kind of personally been

733
00:40:41,719 --> 00:40:46,600
Speaker 3: affected by violent crime, yea, And I was just wondering

734
00:40:46,640 --> 00:40:48,680
Speaker 3: if you wanted to talk a little bit about that

735
00:40:48,880 --> 00:40:52,000
Speaker 3: and how it, you know, if it has changed the

736
00:40:52,239 --> 00:40:55,040
Speaker 3: perspective on the work that you do.

737
00:40:57,120 --> 00:40:58,680
Speaker 7: Like I say I have, I've had a lot of

738
00:40:58,680 --> 00:41:03,959
Speaker 7: family members killed in this city all the way back

739
00:41:04,000 --> 00:41:08,600
Speaker 7: far of ninety eight, but my nephew was Kilo actually

740
00:41:08,640 --> 00:41:13,040
Speaker 7: before that and eighty six my older brother was killed.

741
00:41:14,600 --> 00:41:17,479
Speaker 7: It really didn't affect me too much and doing my job.

742
00:41:19,440 --> 00:41:21,120
Speaker 7: I know, I still had a job to do, and

743
00:41:21,480 --> 00:41:24,280
Speaker 7: I did it, and it really, you know, after a while,

744
00:41:24,560 --> 00:41:28,200
Speaker 7: you don't think about it too much. The last two

745
00:41:28,200 --> 00:41:30,839
Speaker 7: people in my family actually they had two sons that

746
00:41:30,920 --> 00:41:33,160
Speaker 7: were killed within in the past year.

747
00:41:33,800 --> 00:41:39,480
Speaker 3: So yeah, I mean, I guess it's homicide is one

748
00:41:39,520 --> 00:41:42,999
Speaker 3: of the leading causes of death for young black men.

749
00:41:43,279 --> 00:41:46,560
Speaker 3: And you know, I don't know if you have any

750
00:41:46,640 --> 00:41:50,200
Speaker 3: thoughts from kind of your perspective and law enforcement or

751
00:41:50,320 --> 00:41:54,799
Speaker 3: just in general what people can do as individuals or

752
00:41:54,840 --> 00:41:58,960
Speaker 3: what we can do as a broader society to change that.

753
00:42:00,400 --> 00:42:04,160
Speaker 7: Well, I really believe that there's two main things that

754
00:42:04,239 --> 00:42:06,879
Speaker 7: need to be done, and one of them I was doing.

755
00:42:07,000 --> 00:42:11,200
Speaker 7: I was running truancy court, making sure the kids went

756
00:42:11,239 --> 00:42:14,720
Speaker 7: to school and got an education. And it's a shame

757
00:42:14,800 --> 00:42:17,879
Speaker 7: that you have to make Some parents actually send their.

758
00:42:17,880 --> 00:42:18,839
Speaker 1: Kids to school, but.

759
00:42:18,840 --> 00:42:22,120
Speaker 7: They just don't understand how that affects a kid when

760
00:42:22,120 --> 00:42:26,120
Speaker 7: they get older. I guarantee you at least seventy percent

761
00:42:26,640 --> 00:42:28,839
Speaker 7: of people we arrest here. And Geary, you don't have

762
00:42:28,840 --> 00:42:31,839
Speaker 7: a high school diploma, and I think that fees into

763
00:42:31,880 --> 00:42:35,440
Speaker 7: the crime because everybody gonna grow up, everybody gonna want things,

764
00:42:35,800 --> 00:42:39,359
Speaker 7: and you can't even reason fell out application your you know,

765
00:42:39,520 --> 00:42:40,240
Speaker 7: your job.

766
00:42:40,160 --> 00:42:41,200
Speaker 1: Choices are limited.

767
00:42:41,360 --> 00:42:42,439
Speaker 7: So uh.

768
00:42:42,480 --> 00:42:43,520
Speaker 1: And another thing.

769
00:42:43,360 --> 00:42:46,440
Speaker 7: That I really think need to be addressed is mental health.

770
00:42:46,960 --> 00:42:49,320
Speaker 7: You have a lot of females and if it's sexually

771
00:42:49,360 --> 00:42:52,080
Speaker 7: molested and never got any treatment. They had a lot

772
00:42:52,120 --> 00:42:55,880
Speaker 7: of males they have missed either sexually molested or have

773
00:42:56,040 --> 00:42:59,040
Speaker 7: been in the car with somebody around somebody and they

774
00:42:59,200 --> 00:43:02,080
Speaker 7: got shot and killed, or they've been shot before and

775
00:43:02,120 --> 00:43:05,200
Speaker 7: they patched the body up, but they never talked to

776
00:43:05,239 --> 00:43:08,480
Speaker 7: them about the mental issues. And you know, most men,

777
00:43:08,640 --> 00:43:11,480
Speaker 7: they refuse to be a happen me and I like say,

778
00:43:11,560 --> 00:43:14,399
Speaker 7: after what happened, you know in my family, I had

779
00:43:14,440 --> 00:43:18,040
Speaker 7: to go, and I'm glad I went. But the average person,

780
00:43:18,120 --> 00:43:20,319
Speaker 7: average male, don't want to go and they just don't

781
00:43:20,400 --> 00:43:24,640
Speaker 7: understand unless they need it. But that's a lot of it,

782
00:43:24,719 --> 00:43:28,080
Speaker 7: you know, the lack of education and people been abused

783
00:43:28,320 --> 00:43:31,360
Speaker 7: and have no clue even now how that's really affecting

784
00:43:31,400 --> 00:43:32,960
Speaker 7: their everyday decisions.

785
00:43:35,200 --> 00:43:38,799
Speaker 3: Hargrove's algorithm can definitely highlight a place where something is

786
00:43:38,840 --> 00:43:42,919
Speaker 3: going wrong, but when it comes to preventing future homicides,

787
00:43:43,320 --> 00:43:45,600
Speaker 3: I don't think technology is going to provide us with

788
00:43:45,640 --> 00:43:49,640
Speaker 3: any magic bullets. The real solutions are going to be

789
00:43:49,719 --> 00:43:55,040
Speaker 3: less glamorous. They're solutions that sound almost like cliches, things

790
00:43:55,080 --> 00:43:58,960
Speaker 3: we already know we should be doing. Supporting children and

791
00:43:59,000 --> 00:44:04,040
Speaker 3: protecting them from abuse, providing mental health services, cleaning up

792
00:44:04,080 --> 00:44:09,080
Speaker 3: neighborhoods and demolishing derelict buildings, and taking violent crime seriously,

793
00:44:09,440 --> 00:44:12,120
Speaker 3: regardless of who the victim is or where the crime

794
00:44:12,160 --> 00:44:20,360
Speaker 3: took place. This is the end of the weekly episodes

795
00:44:20,360 --> 00:44:22,680
Speaker 3: of Algorithm, but it's not the end of the show.

796
00:44:23,759 --> 00:44:27,279
Speaker 3: Many factors facilitated Darren Vond's killing spree, and there's still

797
00:44:27,279 --> 00:44:30,640
Speaker 3: some angles I'd like to explore. I've already got bonus

798
00:44:30,719 --> 00:44:34,319
Speaker 3: episodes planned and ideas for another season, but I'd love

799
00:44:34,360 --> 00:44:38,000
Speaker 3: to hear your questions and your ideas. Please reach out

800
00:44:38,040 --> 00:44:40,479
Speaker 3: to me or call and leave a voicemail at eight

801
00:44:40,520 --> 00:44:44,439
Speaker 3: eight eight five zero one three three zero nine. We're

802
00:44:44,440 --> 00:44:47,440
Speaker 3: going to have another Q and A episode soon, and

803
00:44:47,480 --> 00:44:49,640
Speaker 3: if you haven't yet. Please do you subscribe to our

804
00:44:49,680 --> 00:44:52,839
Speaker 3: podcast speeds you don't miss any updates and you can

805
00:44:52,840 --> 00:44:55,440
Speaker 3: find all this information and the social media for the

806
00:44:55,480 --> 00:44:58,920
Speaker 3: podcast in the show notes. This episode was written and

807
00:44:58,960 --> 00:45:03,000
Speaker 3: produced by me ben Keebrick Algorithm is executive produced by

808
00:45:03,080 --> 00:45:07,719
Speaker 3: Alex Williams, Donald Albright, and Matt Frederick. Production assistance and

809
00:45:07,759 --> 00:45:11,839
Speaker 3: mix by Eric Quintana. The music is by Makeup and

810
00:45:11,920 --> 00:45:16,200
Speaker 3: Vanity Set and Blue Doot Sessions. Thanks to Christina Dana,

811
00:45:16,520 --> 00:45:21,280
Speaker 3: Miranda Hopkins, Jamie Albright, Rima l k Ali, Trevor Young,

812
00:45:21,560 --> 00:45:25,279
Speaker 3: and Josh Thain for their help and notes. For more

813
00:45:25,320 --> 00:45:29,720
Speaker 3: podcasts from iHeart Radio, visit the iHeartRadio app, Apple Podcasts,

814
00:45:29,840 --> 00:45:31,480
Speaker 3: or wherever you get your podcasts.

815
00:45:39,160 --> 00:45:42,120
Speaker 2: You know, the awful truth is you could just about

816
00:45:42,279 --> 00:45:45,920
Speaker 2: pick any major American city and take a shovel. I

817
00:45:46,040 --> 00:45:48,680
Speaker 2: promise you. Serial murder is more common than we ever

818
00:45:48,719 --> 00:45:53,000
Speaker 2: want to believe. If this project ends up having legs,

819
00:45:53,040 --> 00:45:56,080
Speaker 2: Atlanta would be a good place to go. Frankly, that's

820
00:45:56,120 --> 00:45:59,719
Speaker 2: the largest cluster our computer knows about. In fact, he

821
00:45:59,920 --> 00:46:02,640
Speaker 2: was of the opinion that some of these might be

822
00:46:02,719 --> 00:46:03,279
Speaker 2: solvable