Predictive Policing: The Role of Crime Forecasting in Law Enforcement Operations

By W. Perry, B. McInnis, C. Price, Susan Smith, John S. Hollywood. 2013

494 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Sociology and Political Science, AI Ethics, Fairness & Society, Time-Series & Forecasting

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Bernhard Schölkopf
2. Julius von Kügelgen
3. Amir-Hossein Karimi
4. Isabel Valera
5. Anupam Datta
6. Shayak Sen
7. Virginia Dignum
8. Max Tegmark

In Sociology and Political Science

1. Isabel Valera
2. Amir-Hossein Karimi
3. Bernhard Schölkopf
4. Max Tegmark
5. Anupam Datta
6. Yair Zick
7. Tero Karppi
8. Richard A. Berk

In AI Ethics, Fairness & Society

1. Bernhard Schölkopf
2. Isabel Valera
3. Amir-Hossein Karimi
4. Virginia Dignum
5. Shayak Sen
6. Anupam Datta
7. Richard A. Berk
8. Julius von Kügelgen

In Time-Series & Forecasting

1. Bernhard Schölkopf

Citations in the corpus

• Algorithmic recourse under imperfect causal knowledge: a probabilistic approach (2020, background): “As machine learning algorithms are increasingly used to assist consequential decision making in a wide range of real world settings [28, 33], providing explanations for the decision of these black-box models becomes crucial [5, 46].”
• “The Computer Said So”: On the Ethics, Effectiveness, and Cultural Techniques of Predictive Policing (2018, background): “According to Josh Scannell (2015), many of the current predictive policing technologies are based on disease or weather prediction models: these technologies focus on locations and operate preventively by, for example, increasing law enforcement presences in the areas of potential crime.”
• Machine Learning Risk Assessments in Criminal Justice Settings (2018, background): “Some conceptions of predictive policing include most any use of data to prevent crime and solve crimes (Perry et al. 2013).”
• The role of artificial intelligence in achieving the Sustainable Development Goals (2019, background): “Examples of the positive impacts include AI algorithms aimed at improving fraud detection 56,57 or assessing the possible effects of certain legislation 58,59 .”
• Algorithmic Transparency via Quantitative Input Influence: Theory and Experiments with Learning Systems (2016, background): “They drive decisions in sectors as diverse as Web services, health-care, education, insurance, law enforcement and defense [1], [2], [3], [4], [5].”