Across the country, criminal justice institutions have turned to a data-driven movement to drive down inequities, squelch rising prison populations, reduce recidivism, save billions of dollars and reduce the crime rate. The criminal justice system has begun to utilize predictive assessments to allocate resources to likely crime hotspots and to predict the likelihood of reoffending.
Reports have shown that the underlying algorithms of the predictive assessments are hampered by weak measures of predictive equity and unexamined levels of racial bias. As such, our focus is on determining predictive bias and developing a racial/ethnically equitable approach to identifying risk and needs.
Previous research has demonstrated that improving police-community relations along with reducing excessive surveillance and enforcement practices can strengthen perceptions of legitimacy and reduce mass incarceration. Communities rely on police departments to "protect and serve", and the police, in turn, rely on community support and cooperation. However, this relationship is not always harmonious.
Given the strained relationship between the police and the minority community, coupled with the subjective reality of the HBCU culture, it is evident that we are in a unique position to address this problem.
Below, you will find resources that will provide data-driven solutions to improve community trust, transparency and accountability. As a collective, these resources will help chart the national response for the sustainable improvement of police-community relations.