ShotSpotter document reveals key human role in gunshot tech

But a confidential ShotSpotter document obtained by The Associated Press outlines something the company doesn’t always tout about its “precision policing system” — that human employees can quickly overrule and reverse the algorithm’s determinations, and are given broad discretion to decide if a sound is a gunshot, fireworks, thunder or something else.

Marked “WARNING: CONFIDENTIAL,” the 19-page operations document spells out how employees in ShotSpotter’s review centers should listen to recordings and assess the algorithm’s finding of likely gunfire based upon a series of factors that may require judgment calls, including whether the sound has the cadence of gunfire, whether the audio pattern looks like “a sideways Christmas tree” and if there is “100% certainty of gunfire in reviewer’s mind.

Another part of the document underscores ShotSpotter’s longstanding emphasis on speed and decisiveness, and its commitment to classify sounds in less than a minute and alert local police and 911 dispatchers so they can send officers to the scene. Experts say such guidance under tight time pressure could encourage ShotSpotter reviewers to err in favor of categorizing a sound as a gunshot, even if some evidence for it falls short, potentially boosting the numbers of false positives.“You’re not giving your humans much time,” said Geoffrey Morrison, a voice-recognition scientist based in Britain who specializes in forensics processes. “And when humans are under great pressure, the possibility of mistakes is higher.

ShotSpotter installed its first sensors in Redwood City, California, in 1996, and for years relied solely on local 911 dispatchers and police to review each potential gunshot until adding its own human reviewers in 2011. As cities have weighed the system’s promise against its price tag -- which can reach $95,000 per square mile per year -- company employees have explained in detail how its acoustic sensors on utility poles and light posts pick up loud pops, booms or bangs and then filter the sounds through an algorithm that automatically classifies whether they’re gunfire or something else.

We need better regulations for AI and how it’s used.

like those stupid car exhausts

watch dogs shit

Experts say the extensive role of reviewers to backstop ShotSpotter’s gunshot-detection algorithm could bring in subjectivity and conflict with why artificial intelligence is often used in law-enforcement tools: to lessen the role of fallible humans.

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ShotSpotter document reveals key human role in gunshot techIn more than 140 cities across the United States, ShotSpotter’s artificial intelligence algorithm and intricate network of microphones evaluate hundreds of thousands of sounds a year to determine if they are gunfire, generating data now being used in criminal cases nationwide. ShotSpotter said in a statement to the AP that the human role is a positive check on the algorithm and the “plain-language” document reflects the high standards of accuracy its reviewers must meet. The bias goes deep on this one
Source: YahooNews - 🏆 380. / 59 Read more »

ShotSpotter document reveals key human role in gunshot techCHICAGO (AP) — In more than 140 cities across the United States, ShotSpotter’s artificial intelligence algorithm and intricate network of microphones evaluate hundreds of thousands of sounds a year to determine if they are gunfire, generating data now being used in criminal cases nationwide. It wasn't a gun shot, it was Eric Swallwell's butt after Taco Tuesday Yee it's a racist fraud, and has been v lucrative What the heck ... Where's all these microphones being set up? On street lights?
Source: AP - 🏆 728. / 51 Read more »