Predictive Policing

[davidbfpo]

In a somewhat strange IMHO article 'Defence One' has an article on how China is exploiting fusion and the new capacity of IT to predict dissent, if not protest:http://www.defenseone.com/technology/2016/03/thanks-america-china-aims-tech-dissent/126491/?

It starts with:

What if the Communist Party could havepredicted Tiananmen Square? The Chinese government is deploying a new tool to keep the population from uprising. Beijing is building software to predict instability before it arises, based on volumes of data mined from Chinese citizens about their jobs, pastimes, and habits. It’s the latest advancement of what goes by the name “predictive policing,” where data is used to deploy law enforcement or even military units to places where crime (or, say, an anti-government political protest) is likely to occur. Don’t cringe: Predictive policing was born in the United States. But China is poised to emerge as a leader in the field.

[davidbfpo]

More "cold water" on predictive policing:

But according to a study to be published later this month in the academic journal Significance, PredPol may merely be reinforcing bad police habits. When researchers from the Human Rights Data Analysis Group — a nonprofit dedicated to using science to analyze human-rights violations around the world — applied the tool to crime data in Oakland, the algorithm recommended that police deploy officers to neighborhoods with mostly black residents. As it happens, police in Oakland were already sending officers into these areas.

Link:https://mic.com/articles/156286/crim...ows#.3IhFXDIIh

The cited journal Significance is an Anglo-US publication of the two national statistical groups. The article is behind a pay-wall alas, here is a summary:https://www.statslife.org.uk/signifi...-issue-preview

[flagg]

CIA claims of predicting some unrest up to 5 day ahead:

https://www.engadget.com/2016/10/05/...-5-days-ahead/

[davidbfpo]

Recently RUSI, a Whitehall "think tank" published a report 'Big Data and Policing: An Assessment of Law Enforcement Requirements, Expectations and Priorities', with 54 pgs. and there is a comprehensive summary on this link:https://rusi.org/publication/occasio...t-requirements

It is very UK-centric report, so little mention is made of the various US experiments and schemes.

Today's The Independent on Sunday has an article, based on the report, but has some other comments:http://www.independent.co.uk/news/uk...-a7963706.html

[davidbfpo]

A podcast (33 mns) via WNYC with:

Andrew Ferguson Professor of Law at the University of the District of Columbia's David A. Clarke School of Law, discusses his book The Rise of Big Data Policing: Surveillance, Race, and the Future of Law Enforcement. He examines big data and algorithm-driven policing and its impact on law enforcement. He also looks at how new technologies will alter the who, where, when and how we police, and why data-driven methods could actually improve police accountability.

Link:https://www.wnyc.org/story/data-driven-policing/

Part of his argument is that this approach has grown out of Compstat.

[davidbfpo]

I have heard hints about a large Home Office (central government) project worth £15m on 'big data' and it is actually run locally. So started a look around and found the project is National Data Analytics Solution (NDAS).

Last month there was this 'exclusive' and within an explanation by the police 'lead':

This the first such project of its kind in the world, pooling multiple data sets from a number of police forces for crime prediction, says Donnelly. In the early phases, the team gathered more than a terabyte of data from local and national police databases, including records of people being stopped and searched and logs of crimes committed. Around 5 million individuals were identifiable from the data. Looking at this data, the software found nearly 1400 indicators that could help predict crime, including around 30 that were particularly powerful. These included the number of crimes an individual had committed with the help of others and the number of crimes committed by people in that individual’s social group.
The machine learning component of NDAS will use these indicators to predict which individuals known to the police may be on a trajectory of violence similar to that observed in past cases, but who haven’t yet escalated their activity. Such people will be assigned a risk score indicating the likelihood of future offending.

Link:https://www.newscientist.com/article...re-it-happens/

[davidbfpo]

A short article and the sub-title is: A UK police force uses an algorithm to choose which crimes to investigate. It has led to half as many assaults and public order offences being pursued.

It ends with a salutary warning:

Police forces only ever know about crimes they detect or have reported to them, but plenty of crime goes unreported, especially in communities that have less trust in the police. This means the algorithms are making predictions based on a partial picture. While this sort of bias is hard to avoid, baking it into an algorithm may make its decisions harder to hold to account compared with an officer’s. John Phillips, superintendent at Kent Police, says that for the types of crimes that EBIT is being used for, under-reporting isn’t an issue and so shouldn’t affect the tool’s effectiveness.

Link:https://www.newscientist.com/article/2189986-a-uk-police-force-is-dropping-tricky-cases-on-advice-of-an-algorithm/?