{"resourceId":"cdt-dc-council-tech-in-schools-testimony-20261009","versions":[{"version":"external-9a241a19268d65e2361567c9907f62b626b504f675f5296137cb60eec86f120c","resource":{"id":"cdt-dc-council-tech-in-schools-testimony-20261009","title":"CDT testimony to D.C. Council: school AI use tied to more breaches, deepfakes and monitoring harms; calls for AI inventories, vendor transparency and procurement resources","organization":"Center for Democracy & Technology (CDT)","sector":"K-12 student privacy, civil rights and AI governance","geography":"Washington, D.C. (testimony) drawing on U.S. nationally representative polling","publishedAt":"October 9, 2026 (testimony to D.C. Council Committee of the Whole)","publicationDate":"2026-10-09","eventDate":"2026-10-09","sourceName":"Center for Democracy & Technology","sourceLabel":"Nonprofit testimony citing its nationally representative teacher, parent and student polling","sourceUrl":"https://cdt.org/wp-content/uploads/2026/10/10.9.26-DC-Council-Testimony-on-Tech-in-Schools.pdf","evidenceClass":"independent-research","outcomeClass":"cautionary","topics":["data-security","governance-procurement","operating-model","accessibility-workforce"],"finding":"CDT's Maddy Dwyer told the D.C. Council on October 9 that 85% of teachers and 86% of students used AI in 2024–25 and that teachers report more large-scale data breaches the more ways their school uses AI (23% of teachers reported a large-scale breach). Thirteen percent of teachers said an AI tool failed to work as described (23% where AI is used more often). Students reported deepfakes involving their school community (36%; 61% in frequent-AI schools), and fewer than a quarter of teachers report clear deepfake response policies. Nine in ten teachers say their schools use student activity monitoring; 25% of those know a student contacted by law enforcement because of it. Fifty-seven percent of special education teachers used AI for IEPs or 504 plans. CDT urges high-risk AI identification, AI literacy, model policies, community engagement, research, model procurement resources, documented response processes for safety alerts, vendor transparency, AI inventories and notice to families. Why now: not previously archived; it packages CDT polling into concrete local-government asks as D.C. and other jurisdictions set AI policy.","sledRelevance":"Gives K-12 leaders a risk inventory and a policy checklist (inventories, transparency, procurement resources, alert response processes) directly usable in district and SEA governance.","evidence":"Testimony citing CDT's nationally representative polling about the 2024–25 school year (published October 2025) and earlier CDT research. Associations between AI use intensity and harms are correlational. No new data collection in the testimony itself.","architectureImplications":"Calls for AI tool inventories, documented response workflows for AI safety alerts (monitoring, facial recognition), and transparency from vendors on testing and data use. Interpretation: districts need a registry and alert-handling workflow integrated with counseling rather than discipline by default.","governanceImplications":"Recommends defining high-risk AI uses with heightened protections, model AI and deepfake NCII policies, formal parent and community engagement, ongoing research, and notice and disclosure when adopting new tools.","securityPrivacyImplications":"Links greater AI use to more reported breaches, cites the Canvas breach exposing data of over 275 million users, and flags FERPA and IDEA concerns for AI-drafted IEPs. Recommends vendor transparency and inventories.","caveats":"Advocacy testimony; underlying survey is about 2024–25 and correlational. Figures come from CDT's own research. D.C.-specific recommendations may not transfer directly to other jurisdictions.","streamIds":["k12"],"roles":{"sales":"Sales framing: CDT's testimony gives district leaders a credible risk list and a concrete governance checklist: inventories, vendor transparency, procurement resources and alert-response processes. Lead with a bounded AI risk-and-transparency review tied to those asks. Present CDT's correlations as risk signals, not proof that AI causes breaches, and avoid security guarantees. The value is a defensible, documented governance posture that boards, families and auditors can review.","engineering":"Engineering framing: CDT's asks translate into systems work: a maintained AI tool inventory, vendor transparency fields (testing, data use, limitations), and documented workflows for AI-generated safety alerts from monitoring tools. Pre-sales should assess whether monitoring alerts route to trained staff with review steps before discipline or law enforcement contact. Proof of value is an inventory with transparency fields and a tested alert workflow.","delivery":"Delivery framing: deliver an AI inventory, a high-risk use list with added protections, a deepfake NCII response policy, and a family notice process for new tools. Owners are the privacy officer and technology director with student services. Acceptance is published inventory, adopted policies and staff trained on alert and NCII response. Risks: monitoring harms to protected groups, IEP privacy violations, and community backlash."},"roleDetails":{"sales":{"customerProblem":"Districts expand AI and monitoring tools without inventories, vendor transparency, high-risk definitions or response procedures, while breaches, deepfakes and community backlash grow.","stakeholders":["Privacy officer","Technology director / CISO","Student services and counseling","Special education director","Board and parent advisory groups"],"discoveryQuestions":["Do you maintain a public inventory of AI tools, including student-facing ones?","How are monitoring-software alerts reviewed before discipline or police contact?","Do you have a deepfake NCII response policy?","How do special education staff use AI for IEPs, and under what privacy controls?"],"valueHypothesis":"An inventory, high-risk classification and response procedures could reduce privacy and civil-rights exposure; the source shows associations, not causal reductions.","potentialEngagement":"An 8–10 week AI risk and transparency program: inventory, high-risk use classification, vendor transparency review, alert and NCII response procedures, and family notice templates.","unsupportedClaims":["CDT data do not prove AI causes breaches.","No evidence that inventories alone reduce harm.","Testimony does not evaluate specific products."]},"engineering":{"fit":"Fits districts using AI-powered monitoring, AI-drafted special education documents or broad student AI tools.","architectureIntegration":"Central AI registry with vendor transparency fields; alert routing from monitoring tools into a documented review queue; access controls on AI use with IEP data.","prerequisites":["List of AI and monitoring tools","Vendor documentation on testing and data use","Defined alert reviewers"],"constraints":["Correlational evidence","Vendor transparency is often limited","Jurisdiction-specific law (FERPA, IDEA, state privacy)"],"security":"Require vendor disclosures on data use and security testing; restrict AI processing of IEP and disability data; log alert handling.","proofOfValue":["Registry covers all AI and monitoring tools with transparency fields","Test alerts follow the documented review path","IEP-related AI use runs only in approved, logged tools"]},"delivery":{"work":"Build the AI inventory, classify high-risk uses, adopt alert and deepfake NCII procedures, and set up family notice for new tools.","dependencies":["Vendor cooperation on transparency","Student services staffing","Legal review"],"ownership":"Privacy officer with technology director and student services leadership.","skillsAdoption":"Train teachers and counselors on responding to concerning student AI interactions and deepfake incidents; only one in ten teachers report such training today per CDT.","governanceCheckpoints":["High-risk use list approved","Alert review procedure adopted","Public inventory published","Annual review with community input"],"acceptanceCriteria":["Proposed: inventory published and updated annually","Proposed: 100% of monitoring alerts follow documented review","Proposed: staff trained on NCII response"],"risks":["Monitoring harms to protected students","Privacy violations in AI-drafted IEPs","Backlash from lack of family engagement","Vendor non-disclosure"]}},"retrievedAt":"2026-10-16T22:05:29-05:00","enrichedAt":"2026-10-16T22:08:57-05:00","enrichmentBasis":"retrieved source","accessibilityWorkforceImplications":"Students with disabilities are acutely affected (AI-drafted IEPs, higher self-censorship under monitoring); fewer than half of teachers and students report AI training, and urban/higher-income communities report more AI use.","procurementImplications":"Calls for model procurement resources, vendor transparency requirements and inventories so purchasing decisions rest on disclosed testing and data practices.","operatingModelImplications":"Shifts AI oversight toward a standing transparency regime: inventory, high-risk tiering, alert workflows, family notice and community engagement.","sourceVerification":{"openedUrl":"https://cdt.org/wp-content/uploads/2026/10/10.9.26-DC-Council-Testimony-on-Tech-in-Schools.pdf","referenceExcerpt":"K-12 teachers report an increase in large-scale data breaches the more ways their school uses AI","promptVersion":"sled-research-v4.0","model":null,"basis":"agent-reported inspection"}}}]}