AUSTIN (KXAN) — Rebecca McKee’s North Central Austin upholstery store was hit by thieves in October.
“They stole everything from our officer, laptops, papers, blank checks,” she told KXAN.
McKee said she had trouble getting help from the police, so she was happy to learn that computer algorithms had given the Austin police chief a new tool to decide how many officers to patrol he really needed.
“It’s a good first step,” McKee said. “I mean, it’s pretty obvious that we’re short on police personnel right now.”
As KXAN reported, a commissioner-appointed report funded by the Greater Austin Crime Commission used a machine learning model to sift through five years of police call data. The model recommended 108 additional patrol boats. The department is currently licensed for 774.
So what is machine learning?
To understand the technology, we turned to experts at the Machine Learning Laboratory at the University of Texas at Austin.
When asked for the simplest possible way to explain what machine learning is, director Adam Klivans said, “It’s an automated system that makes intelligent predictions based on data it has seen in the past.”
“One of the simplest examples would be to think about your email program that you use,” he said. “Every time you get an email, whatever system you’re using, it first decides, ‘Is it spam or not?’ There must be some algorithm or decision making going on, based on other emails that [it] has seen in the past to understand it.
The lab’s co-director, Alex Dimakis, warned that the results are only as reliable as the data provided.
“Machine learning models are so complicated that in relying on their predictions, you have to be very careful,” Dimakis said.
KXAN also reached out to Kathy Mitchell with the bipartisan criminal justice reform group Just Liberty. Mitchell also had a seat at the table as the city of Austin revamped the training of its police cadets.
She said she disputed the modeling in the ODA staffing report.
“The whole program is based on the idea that we will never use our agents any differently than we use them during the time this data was created,” Mitchell said. “In fact, we’ve already started using our officer time differently.”
At a press conference on Tuesday, APD chief Joseph Chacon said the report would only be a tool used to determine staffing. Chacon is expected to present a detailed plan to city council in the coming weeks.
PD staffing issues aren’t unique to Austin
The Austin Police Department is not alone when it comes to staffing issues. While nationwide hiring slowed slightly last year, the real damage came from quits and retirements.
It is according to a Police Executive Research Forum special report which surveyed 194 police departments across the country.
Responding agencies reported an 18% increase in the quit rate in 2020-21, compared to 2019-20.
Retirements were even more widespread. The trend in all departments surveyed showed an increase of 45 percent.
It should be mentioned that there are over 18,000 police departments across the country, so the 194 agencies responding to the survey represent a fairly small sample.