Reform predictive policing
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Police agencies, software firms and the public must ensure that crime-forecasting software improves public safety and officer accountability, writes Aaron Shapiro.
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The technology's reliance on lists to identify suspects or to target patrols, combined with the lower accuracy of algorithms when analysing the faces of people of colour, is likely to reinforce over-policing of black and minority ethnic groups.
“The technology's reliance on such lists to identify suspects or to target patrols 8 , combined with the lower accuracy of algorithms when analysing the faces of people of colour, is likely to reinforce over-policing of black and minority ethnic groups.”
From Rethink government with AI (2019) · cites this paper as [8]
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“Similarly, predictive policing systems ( Gerber, 2014 ; Mohler et al., 2015 ; Shapiro, 2017 ) seek to improve police operations by allocating resources to areas of anticipated crimes in advance and waste management systems ( Castro Lundin, Ozkil & Schuldt-Jensen, 2017 ; Perera, Zaslavsky, Christen…”
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Ich weiß, was du nächsten Sommer getan haben wirst
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“…incorporates weather patterns, transport schedules and school cycles into its algorithms to move beyond crime types that cluster in time and space (Shapiro 2017). all exercises in decision theory, it is shaped by two primary factors: (1) the decision problem is an ordering or prioritisation task,…”
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“With respect to reports, officers should be required to complete reports involving deadly force within days using the most sophisticated computer technology available (Shapiro 2017), and this data should be readily available for evaluation boards and public consumption.”
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“Although predictive policing has been reported to decrease local crime rates (predicting hotspots, in Goldsmith & Crawford 2014), such cause-and-effect relationship is difficult to prove (Shapiro 2017; Egbert & Leese 2021).”
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“While the “ Strategic Subject List ” program was terminated in 2019, most US police departments continue to use computerized statistics (CompStat) managerial programs that predict crimes based on past patterns — automatically perpetuating racialized persecution and discipline (Shapiro 2017).”
Dirty Versus Clean Data: The Politics of Data-Driven Policing in South Africa
Diphoorn, T. (2024) · Palgrave's critical policing studies · doi:10.1007/978-3-031-68298-8_3 · Cited by 1 · see citing works
Prädiktive Analysen in Raum und Zeit
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Gerhold, L., Schmidt, T., & Brandes, E. (2019) · IEEE International Symposium on Technology and Society (ISTAS) · doi:10.1109/istas48451.2019.8937996 · Cited by 1 · see citing works
Interpretable Hawkes Process Spatial Crime Forecasting with TV-Regularization
Sha, H., Hasan, M. A., Carter, J., & Mohler, G. (2020) · 2020 IEEE International Conference on Big Data (Big Data) · doi:10.1109/bigdata50022.2020.9377984 · Cited by 2 · see citing works
“First, we believe these models will be useful in meeting the growing demand for transparency and perceived fairness in hotspot policing [24], [27].”
BackgroundExploration on what constitutes an effective detective in South Africa
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Deep Learning and Intelligent Robots in Government
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Policing and ManagementPreprint
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The robot in city hall: the limitations, structure, and governance of smart city technology regimes
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Künstliche Intelligenz - Verstehbarkeit & Transparenz (AK13)
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- Authors
- Shapiro, A.
- Affiliations
- University of Pennsylvania (US)
- Corresponding author
- Shapiro, Aaron
- ORCID
- Shapiro, Aaron
- Venue
- Nature
- Published
- 2017-01-26
- Volume
- 541
- Issue
- 7638
- Pages
- 458-460
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W2578180596
- Cited by
- 118
- References
- 6
- Citations by year
- 2026: 2 · 2025: 7 · 2024: 12 · 2023: 19 · 2022: 16 · 2021: 21 · 2020: 14 · 2019: 16 · 2018: 8 · 2017: 3
- FWCI
- 25.68
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Nature (publishedVersion, public-domain)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Social Sciences › Political Science and International Relations › Policing Practices and Perceptions
- Social Sciences › Political Science and International Relations › Artificial Intelligence in Law
- Keywords
- predictive policing, algorithmic bias, police accountability, public safety, algorithmic transparency, police technology
- MeSH terms
- Machine Learning, Algorithms, Crime, Criminology, Evaluation Studies as Topic, Forecasting, Humans, Safety, Software, United States, Police, Law Enforcement, Criminals, Spatio-Temporal Analysis, Geographic Mapping, Racism
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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