yego.me
💡 Stop wasting time. Read Youtube instead of watch. Download Chrome Extension

Catching serial killers with an algorithm | Big Think x Freethink


3m read
·Nov 3, 2024

THOMAS HARGROVE: Whenever I see data, I tend to think in terms of patterns. The real world is following a rather simple mathematical formula. And it's that way with murder. Most people don't realize that we're far less likely to solve a murder today than we were 50 years ago. My name is Thomas Hargrove and I am the founder and chairman of the Murder Accountability Project. I'm not a police officer. Quite frankly, I am just a nerd.

I really know very little about serial killers. I do know what they look like in data. For 37 years, I was a newspaper reporter and it was just the best job there is in the universe. Increasingly, I became known as the numbers guy in the newsroom. We wanted to study why murders go unsolved and why a growing number of murders go unsolved.

And the first time I saw the supplementary homicide report by the FBI, my first thought was, I wonder if we could teach a computer to spot serial killers in these data. And the answer is yes. Years before I had learned of a phenomenon called linkage blindness. The only way the murders are linked to a common offender is if the two investigators get together by the water cooler and talk about their cases and discover commonalities.

We contacted the FBI and got every year's worth of reporting back to 1980. I opened it up and looked at row after row of individual murders. It had the victim's age, race, sex, how the victim was killed. We turned that into a nine-digit number, essentially a Dewey decimal system of death. During the months that I was working on the algorithm, I had over my desk a picture of Green River Killer, Gary Ridgway. He killed 48 women in Seattle in the '80s and '90s.

He was looking at me for months and months while I was trying to make an algorithm work. The only way we would know that an algorithm was successful is if it was identifying known serial killers. What worked was a technique called cluster analysis. And we told the computer to cluster the data. Seattle came up clear as day; something awful had happened, and the algorithm was producing dozens and dozens of other clusters that looked just as bad as Seattle, that were not known, like Gary, Indiana.

There were actually 15 unsolved strangulations of women in the area, including 13 in Gary itself. I contacted the Gary Police Department and gave them my usual spiel. I'm Tom Hargrove. We have a method to identify serial killers. There have been too many unsolved strangulations. What do you know about it? Absolute radio silence. They would not talk about the possibility there was a serial killer active.

In 2014, just next door to Gary, Hammond Police were summoned to a Motel 6. Dead woman in the bathtub. They made an arrest very quickly. Darren Vann started confessing that he had been at this for decades, going back to the '90s. In all, seven women died after we had tried repeatedly for months to get them to consider the possibility that they had a serial killer.

This was without question, the most frustrating experience in my professional life. I have absolutely no doubt that many of the unsolved strangulation murders of women in Gary, Indiana are Mr. Vann's handiwork. We have more than 220,000 unsolved murders in the United States. We've gathered records on more than 23,000 murders that were never reported to the Justice Department, and we are continuing.

We can see where unreported murders are and we go to police departments and say, "You must start reporting data." I'm going to do what it takes to start solving murder. That's our dream. And that's why we try to make homicide data as available as possible. There is an algorithm that can identify serial killings and does. What's more serious than murder? What's more serious than serial murder? What's better than having a computer be able to identify things that human beings are missing?

Catching killers saves lives, and so whatever we can do would be doing the Lord's work.

More Articles

View All
The water cycle | Weather and climate | Middle school Earth and space science | Khan Academy
Did you know that the water you drink is actually the same water that dinosaurs drank over 65 million years ago? It might be hard to believe, but your water is actually really, really old. In fact, water on Earth is much older than the dinosaurs. Scientis…
Africa’s Pristine Delta in 360 - Ep. 1 | The Okavango Experience
That first moment sitting by myself on an island in the Okavango Delta was the most profound moment of my life. It is, to me, a wilderness beyond comparison. The Okavango Delta is Africa’s last remaining pristine Witkin wilderness. It is an oasis in the m…
NERD WARS! Punisher Vs Riddick (Vin Diesel)
Nerd Wars: Vin Diesel versus Marvel characters take two. So this week we’re doing, uh, Vin Diesel from Ric, yes? Or Ric as Vin Diesel, or ridiculous, ha! That movie you like, that you like that. Versus The Punisher. The Punisher being one of the baddest…
Hypotheses for a two-sample t test | AP Statistics | Khan Academy
[Music] Market researchers conducted a study comparing the salaries of managers at a large nationwide retail store. The researchers obtained salary and demographic data for a random sample of managers. The researchers calculated the average salary of the…
Visually assessing standard deviation | AP Statistics | Khan Academy
Each dot plot below represents a different set of data. We see that here. Order the dot plots from largest standard deviation (top) to smallest standard deviation (bottom). So pause this video and see if you can do that, or at least if you could rank thes…
Watch: An Incredible Viking Voyage—Made Entirely of Paper | National Geographic
I am old, but I remember long ago when we Norsemen ruled the sea. As our northern kingdom expanded, the secret of our success lay in how we built our fearsome longships. Imagine a young boy named Harold who yearns to see the world. His father is a shipbu…