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What Other Cities Have Done

Surveillance Governance Nationwide

Over two dozen U.S. cities have adopted Community Control Over Police Surveillance (CCOPS) frameworks or equivalent ordinances. None of them are in Kansas. Our proposal for Overland Park draws on the best elements of these proven models, adapted to local needs and Kansas law.

1. The CCOPS Model: How It Works

The Community Control Over Police Surveillance (CCOPS) campaign was launched by the ACLU in 2016. Over 26 jurisdictions have enacted CCOPS laws or equivalent ordinances. The core principle: police departments should not acquire, fund, or deploy surveillance technology without community knowledge and elected official authorization.

Pre-Acquisition Approval

Mandatory council vote before acquiring or deploying surveillance technology.

Surveillance Impact Report

Public release at least 21 days before any hearing. Includes civil liberties assessment, capabilities, and data practices.

Surveillance Use Policy

Defines authorized uses, retention limits, sharing agreements, and audit mechanisms.

Annual Public Reporting

Usage data, geographic deployment, complaints, audit results, and costs, published publicly.

Enforcement Mechanisms

May include private right of action, exclusionary rule, and employee discipline.

Not every city adopts every element. The framework is modular. Our proposal draws from the strongest elements across multiple cities.

Source: ACLU CCOPS Campaign

2. Comparison Matrix

How existing city frameworks compare to our proposal for Overland Park.

Provision Oakland Seattle Lawrence, KS Providence Nashville Our OP Proposal
Pre-Acquisition Council Approval Yes Yes Yes Yes Yes Yes (Sec. 1)
Civilian Oversight Body Privacy Advisory Commission Working Group Proposed Civilian review Review Board Advisory Panel (Sec. 4)
Facial Recognition Banned Restricted Banned Banned Restricted Banned (Sec. 13)
Surveillance Impact Reports Yes Yes Yes Yes Yes Yes (Sec. 2)
Annual Transparency Reports Yes Yes Yes Yes Yes Yes, 10+ metrics (Sec. 19)
Data Retention Limits Yes Yes Yes Yes Yes Tiered: 30d LPR, 90d video (Sec. 18)
Vendor NDA Prohibition Yes No Unclear No No Via data ownership (Sec. 6)
Private Camera Registry No No No No No Yes, quarterly (Sec. 10)
Parallel Access Prohibition No No No No No Yes (Sec. 11)
Neighbor Notification (Field of View) No No No No No Yes (Sec. 12a)
Data Broker Restrictions No No No No No Yes, court order req. (Sec. 9)
AI / Algorithmic Verification No No No No No Yes, human corroboration (Sec. 15)
Active Incident Framework No No No No No Yes (Sec. 5)
Evidentiary Exclusion Partial No Unclear No No Yes (Sec. 22)
Derived Data Addressed No No No No No Yes, defined & deletion-tracked (Sec. 0, 18)
Vendor Deletion Verification No No No No No Yes, certified hard-deletion (Sec. 6)
Retention Ceiling No No No No No Yes, 3/7 year max (Sec. 18)
Private Right of Action Yes No No No No Yes, modeled on Oakland (Sec. 23)
Environmental Impact Analysis No No Yes No No No
Racial Equity Toolkit No Yes No No No Via geographic analysis

Key takeaway: Our proposal incorporates the strongest elements from the national CCOPS movement while adding several provisions that go beyond what any single city has adopted: private camera registry, parallel access prohibition, neighbor notification, data broker restrictions, AI verification, derived data deletion, vendor deletion certification, retention ceilings, and a private right of action modeled on Oakland's. These additions reflect the specific technology Overland Park is deploying (Fusus, Flock, DFR drones) and the unique circumstances of the 2026 FIFA World Cup.

3. City-by-City Breakdowns

Oakland, CA

Gold Standard Enacted 2018

Oakland's framework is widely considered the most comprehensive CCOPS model in the country. The Privacy Advisory Commission (PAC) reviews every proposed surveillance technology before it can go to City Council. Oakland bans facial recognition and predictive policing outright, prohibits vendor NDAs, and, critically, gives residents a private right of action to sue for violations. Our proposal's Section 23(a) is modeled directly on Oakland's approach, giving the framework enforcement teeth that don't depend on the City prosecuting itself.

What Worked

  • Structured public process builds legitimacy for approved tech
  • NDA prohibition forces genuine transparency
  • Private right of action gives the ordinance real teeth

Limitations

  • Does not address private camera integration
  • No AI verification or algorithmic corroboration
  • Enforcement depends on individual citizens suing

Source: Oakland Municipal Code Ch. 9.64

Seattle, WA

Enacted 2017

Seattle's framework is notable for two innovations: it required a retrospective audit of technologies already in use, and it applies a Racial Equity Toolkit to all surveillance proposals. The Community Surveillance Working Group requires at least 5 of 7 members from communities historically subject to disproportionate surveillance.

What Worked

  • Retrospective review caught previously unexamined tech
  • Racial equity lens creates structured disparate-impact analysis
  • Community composition requirement ensures representation

Limitations

  • No facial recognition ban (restricted but not prohibited)
  • No NDA prohibition
  • Working Group is advisory only

Source: Seattle Municipal Code Ch. 14.18

Lawrence, KS

Draft Kansas

The Lawrence Transparency Project formed in response to the Lawrence Police Department's deployment of Fusus, the same platform Overland Park is deploying. Their draft ordinance operates under the same state legal framework: Kansas Home Rule authority, K.S.A. 45-217 ALPR exemptions, and no state preemption. It requires written MOUs for all camera access, bans facial recognition, and proposes a public dashboard.

What Worked

  • Demonstrates Kansas communities can organize on this
  • Public dashboard goes beyond annual reporting
  • MOU requirement creates clear legal documentation

Limitations

  • Still in draft form, not yet enacted
  • Does not address parallel access through vendor portals
  • No framework for drone governance

Source: Lawrence Transparency Project

Providence, RI

Enacted

Enacted a CCOPS-style ordinance with a facial recognition ban and council approval for new surveillance technologies. Demonstrates that mid-sized cities, not just major metros, can adopt comprehensive frameworks.

Source: Providence Surveillance Ordinance

Nashville, TN

Enacted (partial)

Community Review Board issues public reports specifically on Fusus usage, creating a Fusus-specific accountability mechanism most cities lack. Directly relevant to the same platform OP is deploying.

Source: Nashville Community Oversight Board

Additional Cities of Note

San Francisco, CA: First major US city to ban facial recognition (2019)

Boston, MA: Banned facial recognition; council approval required

Portland, OR: Broadest ban: covers both public and private use

Denver, CO: $100K/violation penalties; customized Flock contract

Madison, WI: Comprehensive CCOPS with data retention emphasis

Berkeley, CA: Sanctuary contracting ordinance restricting vendor relationships

Fusus-Specific Oversight

Columbia, MO: Rejected Fusus 4-3 in 2022 after community opposition

Buncombe County, NC: Officers must log access reasons with auditing

Cleveland, OH: Community Police Commission has final policy authority

4. Cities That Rejected or Restricted Surveillance Technology

At least 23 jurisdictions have canceled or rejected Flock Safety contracts as of January 2026.

City Action Reason
Austin, TX Canceled Privacy and oversight concerns
Denver, CO Added restrictions $100K/violation penalties
Santa Cruz, CA Rejected Comprehensive surveillance ban
Cambridge, MA Rejected Civil liberties concerns
Flagstaff, AZ Canceled Privacy concerns
Columbia, MO Rejected Fusus (4-3) Community opposition
Berkeley, CA Added restrictions Sanctuary contracting ordinance

Note: Rejecting or restricting surveillance technology is not an anti-police position. These are cities making informed decisions about which tools serve their communities. That is exactly the kind of decision-making our proposal enables for Overland Park.

5. What Worked, What Didn't, and Lessons for Overland Park

What Works Across Frameworks

  • Pre-acquisition council approval is the single most effective provision. Once technology is deployed, restricting it becomes exponentially harder.
  • Public reporting requirements create accountability even when technologies are approved. Public debate changes how departments use the tools.
  • Facial recognition bans have proven durable and politically achievable across ideological lines.
  • Civilian advisory bodies work best with defined roles, access to real data, and a clear reporting relationship to Council.

What Doesn't Work or Has Gaps

  • Advisory-only bodies without data access become rubber stamps. Our proposal gives audit log access (Sec. 17).
  • No existing framework addresses parallel access through vendor portals. Our Section 11 fills this gap.
  • No framework addresses neighbor notification for private cameras. Our Section 12a is a new provision.
  • Most frameworks predate AI analytics. Our AI verification rule (Sec. 15) and technology update trigger (Sec. 3) address current capabilities.
  • Enforcement is the weakest link. Our evidentiary exclusion (Sec. 22) and private right of action (Sec. 23) create both systemic and individual mechanisms.

Lessons for Overland Park Specifically

Ordinance Over Policy

Every city where oversight has been effective codified it in ordinance, not department policy. Policies can be changed unilaterally by the Chief. Ordinances require a public vote.

Kansas Home Rule Is an Asset

Article 12, Section 5 of the Kansas Constitution grants cities power over local affairs. No Kansas statute prohibits local regulation of ALPRs, drones, or surveillance tech.

No Preemption = Opportunity + Fragility

Without state-level protections, local ordinances are the only safeguard. Getting it right locally is critical.

Timing Matters

Cities that enacted governance before or during deployment have stronger frameworks. OP's RTIC launches April 2026. The window is now.

6. How Our Proposal Compares

Our proposal incorporates the strongest elements from the national CCOPS movement while adding provisions that address the specific technology Overland Park is deploying.

Adopted from National Models

  • Council authorization with periodic review (Oakland, Seattle, Lawrence)
  • Civilian advisory panel (Oakland PAC model, adapted)
  • Facial recognition ban (Oakland, SF, Boston, Portland, Lawrence)
  • Surveillance Impact Reports (standard CCOPS)
  • Annual Transparency Reports (standard CCOPS)
  • Data retention limits (multiple cities)
  • Evidentiary exclusion (Oakland concept, adapted)
  • Private right of action (Oakland model, Sec. 23)

New for Overland Park

  • Private Camera Registry (Sec. 10): No existing CCOPS ordinance requires this
  • Parallel Access Prohibition (Sec. 11): Closes the vendor-portal loophole
  • Neighbor Notification (Sec. 12a): Field-of-view disclosure for private cameras
  • Data Broker Restrictions (Sec. 9): Court order required for commercial data
  • AI Verification Rule (Sec. 15): Human corroboration before enforcement
  • Active Incident Framework (Sec. 5): Structured emergency operations
  • AI Training Prohibition (Sec. 6): Vendors cannot use data for model training
  • Technology Update Trigger (Sec. 3): Proactive vendor change notification
  • Derived Data Deletion (Sec. 0, 18): AI-generated metadata follows source deletion schedule
  • Vendor Deletion Certification (Sec. 6): Proof data is actually destroyed
  • Retention Ceiling (Sec. 18): 3/7 year max prevents indefinite storage
SOURCES

Sources & Research

Official Ordinance Texts
City of Oakland
The "Gold Standard" ordinance establishing a Privacy Advisory Commission and requiring Council approval for all surveillance technology.
City of Seattle
"Acquisition and Use of Surveillance Technologies" requires Surveillance Impact Reports and Council approval but lacks private enforcement.
City of Cambridge, MA
"Surveillance Technology Ordinance" requires detailed impact reports and public hearings before acquisition.
City and County of San Francisco
"Acquisition of Surveillance Technology" famously banned government use of facial recognition in 2019.
Comparative Analysis
Berkeley Law — Samuelson Clinic
Detailed comparison of enforcement mechanisms across 16 jurisdictions. Highlights strengths and weaknesses of different approaches.
ACLU
The foundational framework used by 20+ cities. Provides the structural basis for impact reports and use policies.