Arts , Humanities & Social Science

Abstract

This paper investigates the critical issue of implicit bias within law enforcement, discussing its implications on policing practices and community relations. The analysis includes a review of relevant literature, assessment tools, training programs, and policy reforms aimed at mitigating implicit biases. By exploring the impact of implicit biases on decision-making processes in law enforcement, the paper proposes mitigation approaches in a pilot program to drastically reduce or eliminate factors contributing to the “entry” into the criminal justice system via police/civilian interactions, because implicit bias in the US jurisprudence system is even more prevalent, institutionalized, and detrimental (Kang, et al., 2014).  This paper hypothesizes five exacerbating factors of the encounter equation: inherent bias, media portrayal, police academy training deficiencies, historical discriminatory practices, and police militarization. The analysis reviews psychological research on inherent bias, documents case studies illustrating its impact on policing, and synthesizes evidence-based strategies for mitigation. Building on this foundation, the article proposes an artificial intelligence (AI)-assisted, andrological-grounded pilot educational plan for police officers and civilians. This plan integrates differentiated instruction and experiential learning designed to foster self-awareness, empathy, and behavior change to reduce implicit bias in actual policing contexts.