A recent article in The New Yorker, “The Serial Killer Detector,” has given rise to a veritable barrage of scare-headlines across social media (“More Than 2000 Serial Killers At Large! In The United States!!”)
The article by Alec Wilkinson describes how a former journalist, Thomas Hargrove, developed a data analytics tool to identify previously undetected serial killers. Hargrove’s Murder Accountability Project (MAP) has catalogued a total of 751,785 murders since 1976 — a number that far exceeds the official tally reported by the FBI (The discrepancy between MAP and the FBI’s totals reflects the fact that many states fail to report their murder tallies accurately to the Feds. Hargrove has taken states to court to reveal those unreported numbers.)
Hargrove’s MAP tool uses an algorithm he wrote to detect patterns in unsolved murder reports within a geographical area. A high rate of unsolved murders is one indicator that a serial killer may be at large (In 2010, Hargrove spotted a pattern that suggested that a serial killer might be responsible for a series of unsolved murders in a Midwest city. Local officials brushed off Hargrove’s attempts to alert them to the potential threat; years later, a man arrested on another murder volunteered a confession that he had committed many of the earlier killings.)
Hargrove says he is still debating how and when to reach out to local police departments when MAP detects a possible serial killer within a vicinity, according to the article. But MAP has already succeeded in making the public aware that the United States is doing a poor job of solving its murder cases. (In 2016, less than 60 percent of killings were solved, down from 92 percent solved in 1965.)
If you’re adept with statistics you can run the MAP tool from their website http://www.murderdata.org to ferret out unsolved murder patterns in your own hometown.
Have any of the crime detectives in your stories (or your favorite author’s stories) used cutting edge data analytics such as MAP to help solve a fictional crime?