Busted by Big Data: Algorithms Could Make Cities Safer - But They Can't Protect Us From Policing's Worst Instincts
"By combining huge tranches of data and highly sophisticated algorithms,
predictive policing appears to hold out the science-fiction promise that
technology could, one day, spit out 100 percent accurate prophecies
concerning the location of future crimes. The latest iteration of these
analytics can’t ID a killer-to-be, but it can offer insight into what
areas are potential sites for crime by drawing on information in
everything from historical records to live social-media posts.
The technology, however, has raised tough questions about whether
hidden biases in these systems will lead to even more over-policing of
racialized and lower-income communities. In such cases, the result can
turn into a feedback loop: the algorithms recommend a heightened police
presence in response to elevated arrest rates that can be attributed to a
heightened police presence.
Andrew Ferguson, who teaches law at the University of the District of Columbia and is the author of The Rise of Big Data Policing,
goes further. He says that current predictive systems use social media
and other deep wells of personal information to predict whether certain
offenders may commit future crimes—an Orwellian scenario. Canadian
governments and civilian oversight bodies, however, have done little to
establish clear policies differentiating appropriate and inappropriate
uses for these technologies. It is little wonder that critics are
becoming increasingly concerned that police departments fitted out with
big-data systems could use them to pre-emptively target members of the
public. Can we really trust crime fighting to an algorithm?"
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