Predictive Policing and Public Trust — Where Do We Draw the Line?

In today’s ever-evolving law enforcement landscape, technology is not just a tool; it’s a strategic catalyst for accountability, efficiency, and public trust. A recent technology summit brought together a diverse panel of partners and police executives to dissect the implementation challenges and operational realities of modern policing technology—from body-worn cameras and license plate readers to AI-assisted transcription and investigative platforms. The conversation underscored a universal truth: success hinges on solving real problems, rigorous governance, and earning community trust through transparency.

Core Points:

• Prioritize solving real operational problems with technology, not just adopting new tools for the sake of innovation.
• Emphasize change management, governance, and training to maximize adoption, with clear ownership and succession planning.
• Build and maintain transparency: policy alignment, auditing, data retention, and public dashboards to sustain community trust.
• Ensure systems are interoperable: connect core data systems, avoid silos, and use open APIs to enable cross-system collaboration.
• Balance risk, cost, and impact: assess total value (implementation, maintenance, training, integration) and pursue solutions that demonstrably improve day-to-day operations and reduce liability.

Summary

Main Topic 1: Implementation challenges and value of technology in policingThe panel discusses how technology adoption has evolved from simple document management to a broad ecosystem including body-worn cameras, LPRs, and AI tools. A core theme is that successful deployment hinges on solving actual operational problems rather than chasing “shiny objects.” Vendors and police leaders stress the need for clear problem statements, measurable outcomes, and return on investment. Chief Case and others highlight the importance of testing periods and avoiding vendor lock-in by selecting solutions that demonstrably improve accountability, investigations, and community safety. The discussion also covers the tension between rapid technological change and budgetary constraints, underscoring that prudent choices require evaluating total value, not just purchase price.

Main Topic 2: Governance, policy, and transparencyA recurring emphasis is the necessity of robust policies, training, and supervision (the policy–training–supervision triad) to accompany technology. Auditing capabilities, retention schedules, and public dashboards are debated as essential for building trust with communities and meeting legislative expectations. The speakers present diverse perspectives on retention (e.g., 14 days for certain data) and note that transparency about audits, data access, and the use of information by federal agencies is critical. They advocate for proactive leadership in policy creation to stay ahead of legislative changes and to demonstrate accountability when misuse occurs.

Main Topic 3: Interoperability and data governanceThe group consistently returns to the need for connected platforms and data interoperability among CAD, RMS, records management, evidence, and IA tools. They warn against creating data silos and emphasize practical integration through APIs and partnerships. Chance from Rev discusses safeguarding AI-generated content with source citations and human oversight, while Tim from VersaTerm stresses that connected data platforms enable better command decisions and community trust. The overarching message is that interoperable systems, with transparent governance, maximize efficiency and reduce risk.

Main Topic 4: Community trust and accountabilityCommunity concerns about surveillance and data use are central. Leaders describe how outreach and transparent explanation of policy decisions help assuage fears a...

Chapters

• (00:00:00) - DLG Tech Summit
• (00:01:02) - The Public Sa