Predictive Policing: Assessing the Ethical Implications and Effectiveness Using Data Analytics

Abhinay Yada

Abstract


This research paper explores the ethical implications and effectiveness of predictive policing through the lens of data analytics. By analyzing the intersection of technology, law enforcement, and social implications, the study aims to provide a comprehensive assessment of the controversial practice. Key themes include the potential for bias in predictive algorithms, privacy concerns, and the impact on marginalized communities. Additionally, the paper evaluates the effectiveness of predictive policing in crime prevention and resource allocation. Through a multidisciplinary approach, this research contributes to the ongoing discourse on the ethical considerations and practical outcomes of implementing data-driven strategies in law enforcement. 


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Lum, C., & Isaac, W. (2016). To predict and serve? Significance, 13(3), 14-19.

Brantingham, P. J., & Brantingham, P. L. (1995). Criminality of place: Crime generators and crime attractors. European Journal on Criminal Policy and Research, 3(3), 5-26.

Berk, R., Heidari, H., Jabbari, S., Kearns, M., & Roth, A. (2017). Fairness in criminal justice risk assessments: The state of the art. Sociological Methods & Research, 50(1), 3-47.

Harris, A., & Hansen, D. (2016). Policing predictive policing. Data & Society Research Institute. [Online]. Available:

https://datasociety.net/pubs/ia/DataAndPolicing_Primer_2016.pdf

Mohler, G. O., Short, M. B., Malinowski, S., Johnson, M., Tita, G. E., Bertozzi, A. L., & Brantingham, P. J. (2015). Randomized controlled field trials of predictive policing. Journal of the American Statistical Association, 110(512), 1399-1411.

Ratcliffe, J. H., Taniguchi, T., Groff, E. R., & Wood, J. D. (2011). The Philadelphia foot patrol experiment: A randomized controlled trial of police patrol effectiveness in violent crime hotspots. Criminology, 49(3), 795-831.

Groff, E. R., & La Vigne, N. G. (2016). Mapping hotspots of violence in a police agency. In E. R. Groff, D. Weisburd, & J. Roehl (Eds.), Research on policing: Vol. 2. The spatial distribution of crime (pp. 97-128). Springer.

Knox, G. (2018). Predictive policing and the politics of patterns. Theoretical Criminology, 22(2), 173-191.

Ferguson, A. G. (2017). Policing predictive policing. Washington University Law Review, 94, 29-108.

Williams, M. L., & Willard, N. E. (2019). Predictive policing using social media data: An empirical study of the Los Angeles Police Department. Journal of Criminal Justice, 63, 53-63.

McQuade, S. (2018). Regulating pre-crime: A new paradigm of surveillance and control. Journal of Law and the Biosciences, 5(1), 67-108.

Ferguson, A. G., & Hirschfield, P. (2017). Policing prediction: The limits of what's possible. Big Data & Society, 4(2), 2053951717730811.

Pansara, R. R. (2021). Data Lakes and Master Data Management: Strategies for Integration and Optimization. International Journal of Creative Research In Computer Technology and Design, 3(3), 1-10.

Pansara, R. R. (2022). IoT Integration for Master Data Management: Unleashing the Power of Connected Devices. International Meridian Journal, 4(4), 1-11.

Pansara, R. R. (2022). Cybersecurity Measures in Master Data Management: Safeguarding Sensitive Information. International Numeric Journal of Machine Learning and Robots, 6(6), 1-12.

Pansara, R. R. (2022). Edge Computing in Master Data Management: Enhancing Data Processing at the Source. International Transactions in Artificial Intelligence, 6(6), 1-11.

Groeneveld, S., & Kubbe, I. (2019). Predictive policing and the challenges of diversity. Philosophy & Technology, 32(3), 529-545.

Knox, D. (2019). Predictive policing and reasonable suspicion. Criminal Justice Ethics, 38(2), 136-153.

Kroll, J. A., Barocas, S., Felten, E. W., Reidenberg, J. R., Robinson, D. G., & Yu, H. (2017). Accountable algorithms. University of Pennsylvania Law Review, 165, 633-705.

Lum, K., & Isaac, W. (2016). The challenges of predictive policing. Significance, 13(5), 14-19.

Stoitchko, A., & Neudorfer, N. (2020). Predictive policing: An ethical toolkit for predictive crime mapping. Journal of Human Rights and Social Work, 5(2), 143-161.

Morel, B. L., & Simonson, J. (2015). Predictive policing and reasonable suspicion. Ohio State Journal of Criminal Law, 12, 523-569.

Rosenfeld, R., Deckard, M., & Blackburn, E. (2014). The impact of policing on crime: An overview of systematic reviews. Campbell Systematic Reviews, 10(1), 1-29.

Taylor, R. B. (2015). The local community as an ecology of games. In B. C. Welsh & D. P. Farrington (Eds.), The Oxford handbook of crime prevention (pp. 177-193). Oxford University Press.

Atluri, H., & Thummisetti, B. S. P. (2023). Optimizing Revenue Cycle Management in Healthcare: A Comprehensive Analysis of the Charge Navigator System. International Numeric Journal of Machine Learning and Robots, 7(7), 1-13.

Atluri, H., & Thummisetti, B. S. P. (2022). A Holistic Examination of Patient Outcomes, Healthcare Accessibility, and Technological Integration in Remote Healthcare Delivery. Transactions on Latest Trends in Health Sector, 14(14).

Pansara, R. R. (2020). NoSQL Databases and Master Data Management: Revolutionizing Data Storage and Retrieval. International Numeric Journal of Machine Learning and Robots, 4(4), 1-11.

Pansara, R. R. (2020). Graph Databases and Master Data Management: Optimizing Relationships and Connectivity. International Journal of Machine Learning and Artificial Intelligence, 1(1), 1-10.


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