{"resourceId":"ems1-seattle-corti-911-ai-disclosure-20260615","versions":[{"version":"external-d37cc357cd81f1553c7b3e1c6d59379cee1cf0519dc1898699ea3d1319655121","resource":{"id":"ems1-seattle-corti-911-ai-disclosure-20260615","title":"EMS1/Seattle Times: Seattle Fire used Corti AI on 911 medical calls without public disclosure or outcome metrics","organization":"Seattle Fire Department / The Seattle Times (via EMS1)","sector":"Municipal fire/EMS 911 medical dispatch","geography":"United States (Seattle, Washington)","publishedAt":"2026-06-15","publicationDate":"2026-06-15","eventDate":null,"sourceName":"EMS1 (Seattle Times)","sourceLabel":"EMS1 republication of Seattle Times investigation into undisclosed Corti AI on Seattle 911 medical calls","sourceUrl":"https://www.ems1.com/artificial-intelligence/report-finds-seattle-911-ems-calls-monitored-by-ai-without-public-disclosure","evidenceClass":"independent-reporting","outcomeClass":"cautionary","topics":["governance-procurement","data-security","operating-model","accessibility-workforce"],"finding":"EMS1 republishes Seattle Times reporting (Daniel Beekman, June 15, 2026) that for more than two years Denmark-based Corti’s AI has analyzed Seattle residents’ 911 medical calls without caller disclosure or public review, confirmed by the Fire Department in late May after Times inquiries. Corti prompts dispatchers and can nudge routing of some patients to a nurse-staffed Texas call center rather than immediate ambulance dispatch. Officials reportedly cannot explain success metrics or current contract details publicly; no public website disclaimers; no shared outcome metrics; use not assessed under Seattle’s surveillance ordinance. Why now for 2026-10-03: same-week Waukesha-scale PSAP automation (53% of ~92k Ava-handled calls) makes undisclosed 911 AI assist a live governance comparator for SLED agencies expanding conversational or triage AI.","sledRelevance":"Cautionary U.S. fire/EMS 911 AI governance case directly in emergency-services; newly relevant as PSAP automation metrics become public elsewhere.","evidence":"Investigative journalism with department confirmation of non-disclosure and missing public metrics; not a technical performance evaluation of Corti.","architectureImplications":"Real-time call audio AI prompting integrated into dispatcher workflow with nurse-line diversion path.","governanceImplications":"Highlights gaps in disclosure, surveillance-ordinance review, contract transparency, and public KPI reporting for consequential 911 AI.","securityPrivacyImplications":"Third-party AI listening to medical 911 calls without notice raises privacy, secondary-use, and interstate nurse-line data questions.","caveats":"June 2026 reporting; Seattle-specific law; clinical accuracy of Corti not measured here; why-now rests on contemporaneous PSAP automation scale-up.","streamIds":["emergency-services"],"roles":{"sales":"Use Seattle’s Corti case—years of 911 medical-call AI without caller disclosure, public review, or shared metrics—as a governance discovery opener when selling or scoping PSAP AI assist. Ask who approved surveillance-ordinance review, what KPIs exist, and what callers will be told. Bounded engagement: draft a disclosure + metrics pack before any triage-assist expansion. Unsupported claims include proving Corti harmed or helped outcomes from this article alone.","engineering":"Corti listens to medical 911 audio and prompts dispatchers, including nudges toward nurse-line diversion. Prerequisites for analogous deployments: legal review, caller disclosure language, audio processing agreements, and measurable diversion/outcome KPIs. Constraints: Seattle-specific ordinance context; missing public metrics in reporting. Proof of value must include published under/over-triage and complaint rates—not vendor claims alone.","delivery":"Before expanding AI call assist, complete disclosure UX, records-retention policy, surveillance/privacy review, and a public metrics dashboard owned by fire/EMS leadership. Ownership: fire/EMS chief for public accountability; vendor for model behavior. Risks: legitimacy backlash, ordinance noncompliance, and nurse-line diversion without outcome tracking."},"roleDetails":{"sales":{"customerProblem":"Agencies adopting 911 AI assist face trust/legitimacy risk if callers and oversight bodies are not informed.","stakeholders":["Fire/EMS chiefs","City council/oversight","Dispatchers","Public/privacy advocates"],"discoveryQuestions":["Was AI disclosed to callers?","What KPIs exist?","Did surveillance review occur?","Who can audit the vendor?"],"valueHypothesis":"Transparent AI assist with published metrics is more durable than silent optimization of diversion.","potentialEngagement":"Two-week governance gap assessment: disclosure, ordinance, metrics, contract audit rights.","unsupportedClaims":["Corti clinical harm/benefit proven here","All PSAPs have identical legal duties"]},"engineering":{"fit":"Real-time 911 medical-call AI prompting/diversion assist.","architectureIntegration":"Audio analysis alongside dispatcher workflow with pop-up prompts and nurse-line routing options.","prerequisites":["Legal/privacy review","Disclosure script","KPI definitions","Vendor audit rights"],"constraints":["Local surveillance law","Public records exposure","Cross-state nurse-line data flows"],"security":"Third-party listening to 911 audio raises privacy, retention, and secondary-use risks.","proofOfValue":["Published diversion outcomes","Complaint/appeal rates","Undertriage audits"]},"delivery":{"work":"Stand up disclosure, metrics, ordinance review, and contract transparency before scale.","dependencies":["City attorney","Council/oversight","Vendor","Nurse-line partner"],"ownership":"Fire/EMS executive owns public accountability; privacy officer owns data controls.","skillsAdoption":"Train dispatchers on when to accept/reject AI nudges and how to document overrides.","governanceCheckpoints":["Surveillance review","Public notice","Quarterly metrics release"],"acceptanceCriteria":["Caller disclosure live","KPI dashboard public","Audit clause executed"],"risks":["Secret deployment backlash","Unmeasured diversion harm","Contract opacity"]}},"retrievedAt":"2026-10-03T22:01:44-05:00","enrichedAt":"2026-10-03T22:01:44-05:00","enrichmentBasis":"retrieved source","accessibilityWorkforceImplications":"Nurse-line diversion changes who callers reach; without disclosure, accessibility and trust for limited-English or vulnerable callers may be affected.","procurementImplications":"Demands contract clauses for public metrics, audit rights, and disclosure obligations—not only accuracy SLAs.","operatingModelImplications":"AI assist that alters ambulance vs nurse-line routing is an operating-model change requiring explicit public policy, not a silent IT add-on.","sourceVerification":{"responseId":"curl-ems1-seattle-corti-20261003T220144","openedUrl":"https://www.ems1.com/artificial-intelligence/report-finds-seattle-911-ems-calls-monitored-by-ai-without-public-disclosure","referenceExcerpt":"This has happened without any disclosure to callers and without any public review","promptVersion":"sled-research-v4.0","model":null,"basis":"agent-reported inspection"}}}]}