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To support and help strengthen the work of advocates and organizers, the Hub is committed to providing and uplifting up-to-date research, reports, data, model policies, toolkits and other resources. We do this by searching for, categorizing, and making available existing resources from partner organizations and others working on issues related to policing. When needed, the Hub also produces its own research in collaboration with partners. This resource database is categorized, easy to search, and regularly updated by our research team.

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Resources that appear on the Community Resource Hub website are not necessarily supported or endorsed by the Hub. The resources that appear represent various different policies, toolkits, and data that have been presented to challenge issues relevant to safety, policing, and accountability.

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Showing 41 Resources Surveillance × Clear All

“Confronting Black Boxes: A Shadow Report of the New York City Automated Decision System Task Force”

AI Now Institute – New York University

In 2017, New York City became the first US jurisdiction to create a task force to come up with recommendations for government use of Automated decision systems (ADS). This report is a community powered shadow report that provides a comprehensive record of what happened during the Task Force’s review process and offers other municipalities and governments robust recommendations based on collective experience and current research insights on government use of ADS.

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Porch Pirate Panic and the Paranoid Racism of Snitch Apps

Citations Needed Podcast

Everywhere we turn, local media — TV, digital, radio — is constantly telling us about the scourge of crime lurking around every corner. This, of course, is not new. It’s been the basis of the local news business model since the 1970s. But what is new is the rise of surveillance and snitch apps like Amazon’s Ring doorbell systems and geo-local social media like Nextdoor. They are funded by real estate and other gentrifying interests working hand in glove with police to provide a grossly distorted, inflated and hyped-up vision of crime.

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The Daily: The End of Privacy as We Know It?

The Daily – New York Times

A secretive start-up promising the next generation of facial recognition software has compiled a database of images far bigger than anything ever constructed by the United States government: over three billion, it says. Is this technology a breakthrough for law enforcement — or the end of privacy as we know it? Federal and state law enforcement officers are using one company’s app to make arrests in 49 states. So what is Clearview AI, and what influence does it hold?Clearview’s app is being used by police to identify victims of child sexual abuse. Some question both the ethics and the accuracy of the results.

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Opening the Chicago Surveillance Fund

Lucy Parsons Labs

Through the last year and a half, MuckRock and Lucy Parsons Lab have used FOIA to investigate the use of surveillance equipment by the Chicago Police Department (CPD). Through multiple FOIA requests and lawsuits, the team has demonstrated the CPD’s purchase and use of controversial “Stingray” cellphone surveillance devices among other new surveillance technologies. The work has also shown that Chicago Police have been acting in “bad faith” in fulfilling the FOIA requests. This project page gives preliminary data on the issue and asks for assistance in compiling more information.

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Tracked and Targeted: Early Findings On Chicago’s Gang Database (2018)

Erase the Database

This preliminary report summarizes what the Policing in Chicago Research Group has been able to discover, as well as what has yet to be learned, about Chicago’s gang database. Through a combination of in-depth interviews, Freedom of Information Act (FOIA) requests, and archival research, the Research Group sought to learn about impacts of the gang database and understand relationships between law enforcement agencies involved in tracking gang affiliation (e.g., the Chicago Police Department, the FBI, ICE, Illinois State Police, Cook County Sheriff’s Office, etc.).

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Expansive and Focused Surveillance: New Findings on Chicago’s Gang Database (2018)

Erase the Database

Building on previous research into the Chicago Police Department’s (CPD) gang database, this report analyzes new statistics focused on the rapid expansion of the gang database, the data on the ages of people in the database, and evidence of racial discrimination. It ultimately concludes with an attempt to estimate the overall size of CPD’s gang database and highlights the expansive inclusion of minors and elders and the disproportionately targeted communities of color in Chicago.

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Accountability After Abolition: The Regional Gang Intelligence Database

Erase the Database

In response to community demands for public accountability and for a responsible process of abolition that provides restitution to people harmed by the database, the Policing in Chicago Research Group at the University of Illinois at Chicago carried out an evaluation of the Regional Gang Intelligence Database (RGID). This report outlines what is known about RGID and the questions that remain.

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Regional Gang Intelligence Database – Chicago

Erase the Database

This memo provides a review of the Cook County Sheriff’s Office’s (CCSO) Regional Gang Intelligence Database (RGID), which was decommissioned on January 15, 2019. It highlights CCSO policies and procedures for the gang database as well as its data-sharing agreements.

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Advisory Concerning the Chicago Police Department’s Predictive Risk Models

Chicago Office of Inspector General (OIG)

Chicago has shut down the use of predictive policing models known as the Strategic Subject List (SSL) and Crime and Victimization Risk Model (CVRM). The general areas of concern in the PTV risk model program include: the unreliability of risk scores and tiers; improperly trained sworn personnel; a lack of controls for internal and external access; interventions influenced by PTV risk models which may have attached negative consequences to arrests that did not result in convictions; and a lack of a long-term plan to sustain the PTV models.

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