How we can turn racism into a solvable problem -- and improve policing | Phillip Atiba Goff

Episode Summary

Executive Summary: Philip Atiba Goff argues that racism in policing is solvable when defined as measurable behavior rather than hidden prejudice. Using data-driven accountability modeled on ComStat, his Center for Policing Equity helps departments identify gaps between predicted and actual harm, then change policies and practices to reduce force, arrests, and disparities.

Main Topics: Racism as behavior, not just attitude (Priority: 5/5): Goff rejects the common view that racism is mainly about bad hearts or minds, arguing that the real harm lies in measurable actions like stops, searches, arrests, and use of force. Data-driven accountability in policing (Priority: 5/5): He proposes adapting the crime-focused ComStat model into a 'ComStat for justice' that tracks racial disparities and holds departments accountable for reducing them. How the Center for Policing Equity works (Priority: 4/5): The center partners with police departments, analyzes data, compares predicted versus actual outcomes, and identifies the biggest gaps where policy and behavior can change. Case studies from U.S. cities (Priority: 4/5): Examples from Minneapolis, Salt Lake City, Houston, Las Vegas, Oakland, San Jose, Pittsburgh, and Baltimore show how specific local problems can be addressed with targeted reforms. Scaling reform nationally (Priority: 4/5): Goff frames the work as an audacious but achievable infrastructure challenge: expanding tools and partnerships so justice-oriented data systems can reach 100 million people. Broader social harms of unnecessary police contact (Priority: 3/5): He connects police disparities to downstream harms such as cash bail, incarceration, family instability, and mental health and substance abuse crises.

Key Arguments: Racism is better understood as behavior than as private prejudice, because harms are produced through actions that can be measured and changed. A definition of racism that centers intentions over harms makes the problem seem impossible; a behavior-based definition makes it solvable. Police departments already use data-driven accountability for crime through ComStat, so the same logic can be applied to racial justice. By comparing predicted police use of force with actual use of force, departments can identify where policy and behavior—not uncontrollable factors—drive disparities. When departments are given specific, solvable problems, they can reduce force, arrests, and injuries without waiting for society to solve racism abstractly. Many police encounters stem from unmet social needs such as homelessness, mental illness, substance use, or fear of immigration enforcement, so non-police interventions can prevent harm before police are called. Scaling this approach requires infrastructure and collective will, but the model is already producing measurable improvements across partner cities.

Data Points: Adults with law-enforcement contact annually: about 1 in 5 - Goff cites the scale of police contact in the United States. People targeted for police use of force each year: about 1 million - He describes the number of adults targeted for force. Black people’s likelihood of being targeted for force: 2 to 4 times more likely than white people - He highlights racial disparity in police use of force. Partner city capacity: about 40 cities at a time - Current scale of the Center for Policing Equity’s partnerships. Target population for expansion: 100 million people in the United States - Five-year goal for scaling a ComStat for justice. Average reduction in arrests: 25% fewer arrests - Average outcome across partner cities after interventions. Average reduction in use of force incidents: fewer use of force incidents - Goff reports reductions across partner cities; exact percentage not specified in the transcript. Average reduction in officer-related injuries: 13% fewer officer-related injuries - Reported average improvement across partner cities.

Pivotal Quotes: "Trying to solve racism feels impossible because our definition of racism makes it impossible. But it doesn't have to be that way." — Philip Atiba Goff: Core thesis of the talk, reframing racism as a solvable measurement problem. "If a definition of racism makes it harder to see the injuries racism causes, that's not just wrong. A definition that cares about the intentions of abusers more than the harms to the abused. That definition of racism is racist." — Philip Atiba Goff: He critiques intent-focused definitions and centers harm. "Our audacious idea is to deliver a Comstat for justice to departments serving 100 million people across the United States in the next five years." — Philip Atiba Goff: He states the scaling goal for the initiative.

Implications: The talk suggests police reform can be operationalized through metrics, accountability, and targeted interventions. For listeners, it reframes anti-racism as practical systems design rather than abstract moral debate.