Prejudice in Codes: The Dark Side of Predictive Policing and the Threats of Algorithmic Bias in Law Enforcement
In the past decade, predictive policing has gained widespread attention as an innovative tool for law enforcement agencies to prevent crime before it happens. With the help of advanced algorithms and big data analytics, police departments are now able to identify high-risk areas and individuals to allocate their resources effectively. While this approach has shown promising results in reducing crime rates in some areas, it also raises serious concerns about algorithmic bias and discrimination in the criminal justice system. Algorithmic bias refers to the systematic errors and prejudices that occur in automated decision-making systems. In the case of predictive policing, it means that algorithms may rely on historical crime data that reflects existing biases and prejudices of the criminal justice system, including racial profiling and discrimination against minority groups. This can lead to unfair targeting and surveillance of specific communities, exacerbating existing tensions betwee