{"resourceId":"seattle-rtcc-policing-project-governance-audit-20261110","versions":[{"version":"external-cc66d146d8c5600becee854ce9904c7fe1b51eddcab3199485665141ce9ca15f","resource":{"id":"seattle-rtcc-policing-project-governance-audit-20261110","title":"Independent audit of Seattle’s real-time crime center finds useful guardrails but urges binding policy, shorter retention, case-number logging and AI-feature logging","organization":"Policing Project at NYU School of Law; City of Seattle and Seattle Police Department","sector":"Policing / real-time crime centers, cameras and AI tools","geography":"Seattle, Washington, United States","publishedAt":"Policing Project audit PDF posted on Seattle City Council site, November 2026","publicationDate":"2026-11-10","eventDate":null,"sourceName":"Policing Project (via Seattle City Council)","sourceLabel":"Audit of Seattle’s Real-Time Crime Center (governance audit)","sourceUrl":"https://wilson.seattle.gov/wp-content/uploads/sites/43/2026/11/Policing-Project-Seattle-RTCC-Governance-Audit.pdf","evidenceClass":"government-audit","outcomeClass":"cautionary","topics":["governance-procurement","data-security"],"finding":"The Policing Project, retained by the Mayor’s Office in May 2026, reviewed Seattle’s real-time crime center (RTCC) through documents, site visits in May and September 2026 and interviews. It finds clear rules against personal use and immigration or certain health care investigations, but gaps in data governance. It recommends that SPD require Axon to add a case number or reason for any camera activation and to log any use of object detection or other AI features, set up formal internal audits, and put the five-day raw footage retention practice into policy (policy allows 30 days). It also says case-file data is kept indefinitely and should not be. It states many guardrails exist only as informal practice and should become binding written policy, and that tracking people across cameras should generally need a warrant.","sledRelevance":"Gives a concrete, independent control checklist for AI-enabled camera and crime-center platforms that integrators and vendors can map to their own products and to buyer reviews.","evidence":"Independent audit with site visits and interviews; the authors retained editorial control after the city reviewed a draft for factual accuracy. No outcome or accuracy data on AI features.","architectureImplications":"Audit logging that forces a case number or reason, logging of AI feature use, and configurable retention are the technical requirements named; vendor feature gaps are called out.","governanceImplications":"Binding written policy, regular internal audits, codified retention and warrant expectations for tracking across cameras are recommended.","securityPrivacyImplications":"Retained data can be reached by breaches, public records requests and subpoenas, so the audit treats collection and retention as the key boundary.","caveats":"Report reviews governance only and does not assess effectiveness or whether the center should continue; findings apply to Seattle; recommendations are not binding.","streamIds":["public-safety"],"roles":{"sales":"Use the audit as a neutral checklist when talking with police and city buyers about crime center and camera platforms: required reason or case number on every activation, logging of AI features, written retention limits and internal audits. Offer a gap review against those items rather than efficiency claims, since the audit gives none. Expect questions on warrants for tracking and on data reachable by subpoena.","engineering":"Check whether your platform can force a case number or reason at camera activation, log object detection and other AI feature use, export those logs for audit, and enforce configurable retention including for saved case files. Vendor feature gaps are the audit’s main technical finding. Proof of value should be audit log completeness and retention compliance, not detection accuracy, which the report does not evaluate.","delivery":"Plan an assessment that compares an agency’s crime center practice with the audit’s recommendations: written policy for each informal practice, an internal audit schedule, codified retention periods and a published list of tools in use. Assign a named audit owner outside analyst staff. Treat legal questions on warrants and public records as agency counsel work, and schedule time for oversight body review."},"roleDetails":{"sales":{"customerProblem":"Cities face public and council pressure over crime center cameras, AI features and data retention, and many guardrails exist only as informal practice.","stakeholders":["Police chief","City council","Mayor’s office","Inspector general","Privacy advocates"],"discoveryQuestions":["Which guardrails are written policy versus habit?","Can the platform log AI feature use?","How long is footage and case-file data kept?"],"valueHypothesis":"A control gap review against an independent audit can speed council and oversight review; no crime or cost outcomes are claimed.","potentialEngagement":"Crime center governance gap review with a written policy backlog.","unsupportedClaims":["That the controls reduce crime","That AI features are accurate","That a warrant rule is required everywhere"]},"engineering":{"fit":"Audit logging, AI feature logging and retention controls for camera and crime center platforms; not an accuracy evaluation.","architectureIntegration":"Tie activation logs to case numbers and route AI feature logs and retention settings to an audit report.","prerequisites":["Vendor log export","Case number or reason field at activation","Configurable retention by data type"],"constraints":["Vendor must build missing features","Private camera feeds with limited retention control","Seattle-specific findings"],"security":"Restrict access, log every activation and AI use, and shorten retention to limit exposure to subpoenas and breaches.","proofOfValue":["Share of activations with case number or reason","AI feature use logged and reviewable","Retention periods enforced in system"]},"delivery":{"work":"Assess current practice against the audit list and draft written policy, audit schedule and retention periods.","dependencies":["Vendor feature roadmap","Agency counsel","Oversight body review"],"ownership":"Police administration with an internal audit owner.","skillsAdoption":"Train analysts to decline requests whose purpose cannot be confirmed and to log each decision.","governanceCheckpoints":["Policy review with oversight body","Annual audit","Public tool list updates"],"acceptanceCriteria":["Written policy for each informal guardrail","Internal audit schedule adopted","Retention periods codified"],"risks":["Vendor features arrive late","Policies remain informal","Council disputes warrant standard"]}},"retrievedAt":"2026-11-11T03:52:18Z","enrichedAt":"2026-11-11T03:54:44Z","enrichmentBasis":"retrieved source","accessibilityWorkforceImplications":"Audit asks for formal internal audits and trained analysts who decline unverifiable requests; staffing needs are not quantified.","procurementImplications":"Report urges requiring vendor features (case number, AI logging) and says tools in use should be disclosed; contract terms are not detailed.","operatingModelImplications":"Shows a crime center moving from informal practice to written rules, audits and public disclosure.","sourceVerification":{"openedUrl":"https://wilson.seattle.gov/wp-content/uploads/sites/43/2026/11/Policing-Project-Seattle-RTCC-Governance-Audit.pdf","referenceExcerpt":"require a case number or reason for any camera activation and (b) log any use of object detection or other AI features","promptVersion":"sled-research-v4.0","model":null,"basis":"agent-reported inspection"}}}]}