by A recent study conducted by The Markup and Wired has shed light on the effectiveness of predictive policing, a law enforcement technique that uses data analysis to predict crime hotspots. The study focused on the city of Plainfield, New Jersey, and revealed that the crime prediction software used by the police department, Geolitica (formerly known as PredPol), had an abysmal success rate.
The dataset provided by the Plainfield Police Department contained 23,631 predictions made by Geolitica between February 25 and December 18, 2018. Shockingly, the software accurately predicted the locations of crimes with less than a 0.5% success rate during this period. This revelation raises serious concerns about the effectiveness and reliability of predictive policing as a whole.
Captain David Guarino of the Plainfield Police Department was frank about the software’s shortcomings. He admitted that the decision to adopt Geolitica was driven by the department’s desire to enhance crime reduction efforts. However, the software did not live up to expectations. Guarino expressed skepticism, stating that the department rarely, if ever, relied on the software for decision-making. As a result, they eventually decided to discontinue its use.
This study adds to the growing body of evidence questioning the efficacy of predictive policing software. In a prior collaboration between Gizmodo and The Markup, investigators found that PredPol’s software was disproportionately used to target low-income communities of color. These findings raise concerns about potential biases in the implementation of predictive policing algorithms, further undermining their credibility and reliability.
While proponents of predictive policing argue that it can help allocate resources effectively and prevent crime, this study highlights the need for a more critical assessment of the technology and its impact on communities. It calls into question the validity of relying heavily on algorithms that may perpetuate biases and fail to deliver accurate predictions.
Moving forward, it is crucial for law enforcement agencies and policymakers to take a more cautious approach in adopting and implementing predictive policing strategies. They must rigorously evaluate the methodologies and algorithms employed, ensuring transparency and accountability in the process. Additionally, addressing potential biases and the disproportionate targeting of marginalized communities is essential to prevent further harm and uphold the principles of fairness and justice.
As the debate surrounding the use of predictive policing intensifies, it is imperative to prioritize community input and involve stakeholders in decision-making processes. Striking a balance between leveraging technology and safeguarding civil liberties is crucial in ensuring effective and equitable law enforcement practices.
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1. Source: Coherent Market Insights, Public sources, Desk research
2. We have leveraged AI tools to mine information and compile it
