Field observations recorded as contact notes provide the most predictive data for future calls for service, behavioral health crises, and public safety risks. Whether robustly collected at an initial contact or compiled across repeated interactions, field-contact notes offer critical details for harm reduction, de-escalation, diversion, referral, and case planning.
Just a few months ago, a market leader in artificial intelligence for consumer use announced the release of a new AI chatbot solution for government. Unlike its consumer-facing counterpart, this product was developed with public sector compliance, data security, and regulations in mind. This reflects a growing demand for AI in government services, where agencies must balance innovation with strict standards for privacy, accountability, and security.
When partnering to implement evidence-based practices (EBP) in your community, there are a number of real-world factors to consider. You might even find yourself asking, what does EBP truly look like in action? For a moment, consider these scenarios:
CAPTION: AI-POWERED INSIGHTS FOR PUBLIC SAFETY
Justice-involved individuals should receive the appropriate level of care, provided in the least restrictive way possible, facing mental or other behavioral health crises. Prompt identification of risks and needs, such as access to public documents, housing security, family and social support challenges, and peer associations, can be critical to ensuring the appropriate level of care is provided. Here, we explore ways AI can assist in the facilitation of risk and needs-based assessment in the field to promote positive outcomes.
