INSUBCONTINENT EXCLUSIVE:
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Can algorithms really predict where new crimes will take place
The new crime-fighting weapon of choice for a growing number of police forces around the world isn't a gun, a taser or pepper spray - it's
But can computer algorithms really help reduce crimeImagine a gang of bank robbers arriving at their next heist, only to find an armed
response unit already waiting on the corner
Or picture walking down a dark alley and feeling afraid, then seeing the reassuring blue lights of a police car sent to watch over you
Now imagine if all of this became possible thanks to mathematics
Ever since the Philip K Dick novel The Minority Report, which was later turned into a Tom Cruise blockbuster, was published in the 1950s,
futurists and philosophers have grappled with the concept of "pre crime"
It's the idea that we can predict when an offence is going to occur and take measures to prevent it
Now artificial intelligence and machine learning mean this concept has leapt straight from the pages of science fiction into the real world
Tech firm PredPol - short for predictive policing - claims its data analytics algorithms can improve crime detection by 10-50% in some
cities.Image copyrightPredPolImage caption
The PredPol software advises police forces on where they should concentrate
their patrols
It takes years of historic data, including the type, location and time of crime, and combines this with lots
of other socio-economic data, which is then analysed by an algorithm originally designed to forecast earthquake aftershocks
The software tries to predict where and when specific crimes will occur over the next 12 hours, and the algorithm is updated every day as
new data comes in."PredPol was inspired by experiments run by the University of California in collaboration with the Los Angeles Police
Department," says PredPol co-founder and anthropology professor Jeff Brantingham."That study demonstrated that algorithmically driven
forecasts could predict twice as much crime and, when used in the field, prevent twice as much crime as existing best practice."Predictions
are displayed on a map using colour-coded boxes, each one representing a 500 sq ft (46 sq m) area
Red boxes are classed as "high risk" and officers are encouraged to spend at least 10% of their time there
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The ultimate aim of predictive analytics is to prevent crime before it happens
Prof Brantingham says machine learning allows PredPol to analyse data, draw conclusions and make connections between large
amounts of data that human analysts simply could not cope with.Sceptics say this is pseudoscience, because crunching crime data to make
informed decisions on police deployment is nothing new
Many forces have traditionally used "hot spot analysis", where past offences are recorded and overlaid onto a map, with officers
concentrating on those areas
But PredPol and others working in this space, such as Palantir, CrimeScan and ShotSpotter Missions, say that traditional hot spot analysis
is just reacting to what happened yesterday, not anticipating what will happen tomorrow.AI and machine learning can spot patterns we've
never noticed before."Machine learning provides a suite of approaches to identifying statistical patterns in data that are not easily
described by standard mathematical models, or are beyond the natural perceptual abilities of the human expert," says Prof
Brantingham.Alexander Babuta, of the National Security and Resilience Studies group at the Royal United Services Institute, agrees, saying:
"Retrospective hotspot mapping does not distinguish between two types of 'risky' locations, those that simply experience a high volume of
crime over time because they are more attractive to criminals, such as insecure car parks and busy shopping areas, and areas where the
likelihood of crime has been temporarily increased due to crime events that have recently occurred
"But machine learning predictive policing technology does." Police forces certainly seem to be buying in to the idea
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Data from more surveillance cameras and sensors could improve predictive
accuracy
More than 50 police departments across the US use PredPol software, as well as a handful of forces in the UK
Kent Constabulary, for example, says street violence fell by 6% following a four-month trial."We found that the model was just incredibly
accurate at predicting the times and locations where these crimes were likely to occur," says Steve Clark, deputy chief of Santa Cruz Police
Department."At that point, we realised we've got something here." But predictive policing has its critics.Frederike Kaltheuner, data
programme lead at civil rights group Privacy International, wonders whether it will also be used to predict police violence and white collar
crime, or simply used against communities that she says are already marginalised
"We're moving away from innocent until proven guilty towards a world where people are innocent until found suspicious by opaque and
proprietary systems that can be difficult, if not impossible, to challenge," she says.Image copyrightGetty ImagesImage caption
The Los Angeles Police Department has been criticised by civil rights activists worried about its use of predictive policing
There are also concerns about racial and other biases hidden within the datasets
The Los Angeles Police Department, which has been working with Palantir for its predictive policing project, has attracted criticism from
local activist groups worried about threats to civil liberties and racial profiling.Rand Corporation, a policy research institution, has
produced a number of studies looking at predictive policing.More Technology of BusinessRand analyst John Hollywood says recent advances in
analytical techniques have produced only "small, incremental" improvements in crime prediction; results that are 10-25% more accurate than
traditional hot spot mapping
"Current technologies are not much more accurate than traditional methods," he says
"It is enough to help improve deployment decisions, but is far from the popular hype of a computer telling officers where they can go to
pick up criminals in the act."More data, from surveillance cameras equipped with image and behaviour recognition, and sensors detecting
gunshot and intrusion, should help improve the accuracy of predictive techniques, he argues
Citizens need to decide whether a reduction in crime is worth the potential assault on our civil liberties should such technology be misused
or abused by those in power.Follow Technology of Business editor Matthew Wall on Twitter and Facebook
