Predictions put into practice: a quasi-experimental evaluation of Chicago’s predictive policing pilot

Saunders, Jessica; Hunt, Priscillia; Hollywood, John S.

doi:10.1007/s11292-016-9272-0

Cited by 122 publications

(99 citation statements)

References 58 publications

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“…A study 8 published last month indicates that such maps are ineffective: they increase the likelihood that certain people will be targeted by the police, but do not reduce crime.…”

Section: Social-systems Analysismentioning

confidence: 99%

There is a blind spot in AI research

Crawford

Calo

2016

Nature

277

136

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“…A study 8 published last month indicates that such maps are ineffective: they increase the likelihood that certain people will be targeted by the police, but do not reduce crime.…”

Section: Social-systems Analysismentioning

confidence: 99%

There is a blind spot in AI research

Crawford

Calo

2016

Nature

277

136

View full text Add to dashboard Cite

show abstract

“…Recently, the shift from predicting and ranking "hot spots" to "hot people" has become a new focus for predictive policing (Ferguson 2016). For example, Saunders et al (2016) evaluated the impact of a predictive policing program on gun violence based on a list of people estimated to be at the highest risk of gun violence, who were then referred for a preventive intervention. In addition, Mastrobuoni (2017) analyzed the effect of an offender-based software in Italy.…”

Section: Proactive Policingmentioning

confidence: 99%

Frontiers in the economics of crime: lessons for Latin America and the Caribbean

Jaitman¹

2019

Lat Am Econ Rev

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“…the location has a number of tourist attractions and is close to a main road and to train and bus stations. However, the advent of big data and machine-learning has given significant additional impetus to the use of profiling in law enforcement and, thereby, to socalled predictive policing (Saunders et al 2016).…”

Section: Profiling and Predictive Policingmentioning

confidence: 99%

Machine Learning, Ethics and Law

Miller

2019

AJIS

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Recent revelations concerning data firm Cambridge Analytica's illegitimate use of the data of millions of Facebook users highlights the ethical and, relatedly, legal issues arising from the use of machine learning techniques. Cambridge Analytica is, or was -the revelations brought about its demise -a firm that used machine learning processes to try to influence elections in the US and elsewhere by, for instance, targeting 'vulnerable' voters in marginal seats with political advertising. Of course, there is nothing new about political candidates and parties employing firms to engage in political advertising on their behalf, but if a data firm has access to the personal information of millions of voters, and is skilled in the use of machine learning techniques, then it can develop detailed, fine-grained voter profiles that enable political actors to reach a whole new level of manipulative influence over voters.

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Predictions put into practice: a quasi-experimental evaluation of Chicago’s predictive policing pilot

Cited by 122 publications

References 58 publications

There is a blind spot in AI research

There is a blind spot in AI research

Frontiers in the economics of crime: lessons for Latin America and the Caribbean

Machine Learning, Ethics and Law

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