Police Dog Named "Bono" Plays By Own Rules, Plants Drug Evidence at Virtually Every Crime Scene
The Virginia State Police has at least one very dirty cop: a K-9 pooch named "Bono" that has an uncanny ability to detect illegal drugs. Especially when there aren't any present.
The four-legged crime fighter working for the Virginia State Police has been on a hot streak, detecting drugs nearly every time he's on the job. In reality, however, illegal narcotics were found just 22 times of the 85 'alerts' by the dog.
That was the argument public defender Randy Cargill representing Herbert Green, 45, tried to use to suppress the 1.5 kilogram of cocaine found in his client's SUV with Bono's help, the Roanoke Times reported….
Cargill argued that Bono's track record was so poor that police lacked probable cause to search Green's SUV in the first place.
Oh, Cargill, you poor bastard. You probably thought that expert testimony had to be, you know, expert or something. What happened next:
Bono 'may not be a model of canine accuracy,' [federal Judge Glen] Conrad wrote in an opinion filed Thursday in U.S. District Court in Roanoke.
However, the judge ruled that other factors, including the dog's training and flawless performance during re-certification sessions, were enough to overcome a challenge raised by Green's attorney.
And there's this:
[A prosecutor] explained that in some cases where nothing was found after an alert by Bono, police later determined that cocaine or marijuana had been in the vehicle hours earlier, leaving a scent the dog was trained to detect.
Bono's handler Trooper Brian Dillon testified that variables such as wind and the possibility of well-stashed drugs in a car would affect the numbers cited by the defense.
'It's just a big game of hide-and-seek with the canine,' Dillon said.
Don't you see? It's just a game. A big freaking game.
Back in 2011, Radley Balko (then at Reason, now at Huffington Post) wrote about the incredibly shakey record that police dogs have in turning up drugs. Or, more precisely, how independent and rigorous studies show that - duh - police dogs follow cues from their oh-so-human handlers and, as a result, generate an enormous amount of false positives, especially when dealing with black and hispanic suspects.
A recent Chicago Tribune survey of traffic stops by suburban police departments from 2007 to 2009, for example, found that searches turned up contraband in just 44 percent of the cases where police dogs alerted to the presence of narcotics. (An alert is a signal, such as barking or sitting, that dogs are trained to display when they detect the target scent.) In stops involving Hispanic drivers, the dogs' success rate was just 27 percent. The two largest departments the Tribune surveyed—the Chicago Police Department and the Illinois State Police—said they don't even keep track of such information.
Summarizing a study done by University of California-Davis researchers, Balko noted:
Dog/handler teams correctly completed a search with no alerts in just 21 of the 144 walk-throughs. The other 123 searches produced an astounding 225 alerts, every one of them false. Even more interesting, the search points designed to trick the handlers (marked by the red slips of paper) were about twice as likely to trigger false alerts as the search points designed to trick the dogs (by luring them with sausages)….
And more:
In 2006 University of North Carolina law professor Richard Myers conducted a statistical analysis(PDF) of police dog accuracy tests and concluded that the animals were not reliable enough to produce probable cause for a search, let alone serve as the cornerstone of a conviction. At least five states have banned or restricted the use of scent lineups in criminal cases, but they are still frequently used in courtrooms across the country.
Man's best friend? Hardly. The MAN's best friend? Definitely.
Nick Gillespie is co-author with Matt Welch of The Declaration of Independents: How Libertarian Politics Can Fix What's Wrong With America, now out in paperback with a new foreword. Follow him on Twitter.
