[{"_1":2,"_99":-5,"_100":-5},"loaderData",{"_3":4,"_26":27},"root",{"_5":6,"_17":10,"_18":19,"_20":21,"_22":10,"_23":-5,"_24":-5,"_25":10},"user",{"_7":8,"_9":10,"_11":10,"_12":-5,"_13":-5,"_14":15,"_16":-5},"roles",[],"isAuthenticated",false,"isPremium","planName","subscriptionStatus","featureFlags",{},"insightsBudget","isDevelopmentHost","userPreferences",{},"recaptchaSiteKey","6LcvOJcUAAAAAHsB-gPGfGktcRlKpH7OTIU_dMTD","isImpersonating","impersonation","affiliateStatus","isFreedomPortal","routes/v2/article/layout",{"_28":29,"_30":31},"notFound",true,"relatedArticles",[32,75,87],{"_33":34,"_35":36,"_37":38,"_39":40,"_41":42,"_43":44,"_45":46,"_47":48,"_49":50,"_51":52,"_53":54,"_55":56,"_57":58,"_59":60,"_61":62,"_63":64,"_65":66,"_67":68,"_69":70,"_71":72,"_73":72,"_74":72},"mediaId",6084414,"mediaKeyId","2916234-c6b76d0a099731821ef39491ceab023e","parentId",2916234,"title","District pilots show practical gains; witnesses push states and feds to fund teacher training and vetting","audioSeconds",4156,"startMs",2410000,"endMs",6566000,"viewUrl","/Search/View?dp=1&key=2916234-c6b76d0a099731821ef39491ceab023e&start=2410&end=6566","thumbnailUrl","https://assets.pipeline.soar.com/2916234-c6b76d0a099731821ef39491ceab023e/thumbnail_2410000.jpg","articleUrl","/articles/6084414/District-pilots-show-practical-gains-witnesses-push-states-and-feds-to-fund-teacher-training-and-vetting","mediaUrl","https://secure.pipeline.soar.com/6084414-344422e5ba92394d4abc97cb19590539/orig.mp4?Expires=1770998936&Signature=JsP85jScwKw14yucBrc4OOs5Fow2dNZOmA6MBqq4w9We~NZu0hjk47T-uTnPtQFMWvVnRVwyvFAAnV50BwBl0I8-X30SShx6o9l1dgLU1anJ-18wA~kDhpnYtGILaItBVUu44dGsH8kOh0HUww~3kQqj4ji14czj8OLuTU~twD7WYmbR5c937pAcbJmPa9KvfNqlb4JyacqalM~pItmtUcqZPOAkyEJBZPUA3RJvcJG8yuWc6q48BEye06rAgRB~JQP~HRVy5mpE5RboAEeFD7HKqRM52KLYo4Vsmpjj718PyIYELNSl74OF~Aw-q~r3K-sGXsltKvWxItaU5h0lXA__&Key-Pair-Id=KUT5TJCACFTXG","author","U.S. House Committee on Education & the Workforce","date","2025-04-01T00:00:00Z","article","School leaders testifying at a House Education and Labor subcommittee hearing described district pilots that used AI agents and local hosting to protect student data while improving educator efficiency and individualized supports.

Chris Chisholm, superintendent of the Pearl Public School District in Mississippi, described creating a local AI agent trained on the district’s writing rubric that helped a veteran English teacher reduce nightly grading time and stay in the classroom. \"We created an agent for her. We uploaded the state writing rubric ... and we created an agent for her to use in the classroom,\" Chisholm said, adding that the district hosts its model on an internal server to avoid FERPA concerns.

Witnesses stressed that teacher readiness and professional development are central to realizing AI’s benefits. Erin Moe described the EdSafe AI Alliance’s SAFE framework—safety, accountability, fairness and transparency—and urged federal and state support for sustained professional development. Dr. Sid Dobrin emphasized AI literacy that explains how models work so teachers and students can apply critical thinking and keep “humans in the loop.”

Panelists discussed costs and implementation models. Chisholm said a district‑hosted server is expensive but can be more cost‑effective than paying per‑use fees for commercial APIs at scale; other witnesses encouraged public funding to help underresourced districts. Several members and witnesses recommended state‑level assurance labs to vet vendors and share research about which modalities and deployments (text tutors, immersive experiences, localized models) are most effective.

Witnesses also highlighted special‑education use cases: Chisholm and Dr. Rafalvaire described using assessment data to generate individualized plans and screeners; early research (cited from county pilots) suggested AI‑assisted tutoring benefited tutors at multiple skill levels, with disproportionate gains for lower‑and middle‑performing tutors.

Committee members asked practical questions about privacy safeguards, the need to scrub personally identifiable information before using commercial models, and how districts can prioritize classroom activities that are less vulnerable to off‑site AI misuse (for example, moving more assessment and project work into supervised class time). No formal policy was decided at the hearing; witnesses and members urged funding for teacher training, interoperability and cybersecurity supports to scale promising pilots equitably.","mediaType","Video","parentTitle","From Chalkboards to Chatbots: The Impact of AI on K-12 Education","oneSentenceSummary","Superintendents and technologists told a House subcommittee that local pilots—some using district‑hosted AI models—have improved grading efficiency and individualized plans, but scaling requires professional development, cybersecurity support and vetted tools.","taxTitle","Education and Labor: House Committee, Standing Committees - House & Senate, Congressional Hearings Compilation, Legislative, Federal","taxId",1979,"location","","headline","shortSummary",{"_33":76,"_35":36,"_37":38,"_39":77,"_41":78,"_43":79,"_45":80,"_47":81,"_49":82,"_51":83,"_53":84,"_55":56,"_57":58,"_59":85,"_61":62,"_63":64,"_65":86,"_67":68,"_69":70,"_71":72,"_73":72,"_74":72},6084419,"Witnesses warn AI surveillance and bias could deepen inequities in schools without federal oversight",223,4480000,4703000,"/Search/View?dp=1&key=2916234-c6b76d0a099731821ef39491ceab023e&start=4480&end=4703","https://assets.pipeline.soar.com/2916234-c6b76d0a099731821ef39491ceab023e/thumbnail_4480000.jpg","/articles/6084419/Witnesses-warn-AI-surveillance-and-bias-could-deepen-inequities-in-schools-without-federal-oversight","https://secure.pipeline.soar.com/6084419-27e9a31756d671547f9425ca4253da1e/orig.mp4?Expires=1770998936&Signature=Fn116xcWK9m40BQY4otTKhnKNAVqaB6LmmQZ2mIUqhXxxYfa5~prxd5iCLISWoZDH2Lom3gW-XOJhc7bfdsbNcF8umkX7RYbhRur-BZRBcMZNbSob3BVj3exWSmxp4wxVYqx-GcBOUtmMtCnJH2iHCTPaX4nuORgv6KL97kUPDkf1OD5c7CNHSeiVDjkocUgmPvZpx3n5G4ABJaW79q6WuW50O2556hs1nmWf9LOda6efauRfbWs4JvZ5QwHdeKvf8wP1qQizi0Qk2jlNa-DwmFu1FBgeJMYIBGNoqycqbAuMose0vMez26XhTayLz5k~Gh~G9BDsMMSib-RXDoU9A__&Key-Pair-Id=KUT5TJCACFTXG","At a House Education and Labor subcommittee hearing on Oct. 12, 2025, lawmakers and witnesses raised civil‑rights alarms about the use of AI surveillance and algorithmic decision tools in schools and the consequences of reduced federal oversight.

Representative Mary Lee (remarks during hearing) and Representative Lee of Pennsylvania highlighted studies and surveys showing disproportionate harms from automated surveillance and predictive tools: “AI often reinforces the same implicit and explicit biases that humans carry,” Representative Lee said, warning that surveillance tools such as facial recognition and so‑called aggression detection have produced racially disparate results.

Witnesses said mitigation requires data, testing and accountability. Erin Moe and Dr. Julia Rafalvaire recommended that tools be evaluated for disparate impacts, and that states and districts collect the data necessary to measure and reduce bias. Rafalvaire proposed state “AI assurance labs” to vet tools and monitor outputs over time.

Several witnesses and members warned that recent staffing cuts at the Department of Education—specifically the elimination of the Office of Educational Technology and reductions to the Institute of Education Sciences—reduce the federal government’s capacity to issue guidance, share research, and enforce civil‑rights protections through the Office for Civil Rights. “Without resources like this from the Department of Education, are schools equipped to keep students' civil rights intact when deploying AI surveillance?” Representative Lee asked.

Panelists noted industry limitations: companies can test tools only on the data they possess, limiting their ability to surface harms that appear in other populations. Erin Moe and other witnesses urged stronger public‑sector data infrastructure and federally funded research to enable independent evaluation. They also highlighted immediate district‑level precautions, including limiting student‑identifiable data, using local hosting where FERPA permits, involving parents and students in vetting, and avoiding automated disciplinary decisions without human review.

No formal regulatory action was proposed during the hearing; members on both sides called for more research, community engagement and clarified safeguards to ensure that AI tools do not exacerbate the school‑to‑prison pipeline or otherwise deepen existing disparities.","Experts and lawmakers told a House subcommittee that unchecked classroom surveillance, biased algorithms and cuts to Department of Education enforcement resources risk reinforcing disparities for students of color and those with disabilities.",{"_33":88,"_35":36,"_37":38,"_39":89,"_41":90,"_43":91,"_45":92,"_47":93,"_49":94,"_51":95,"_53":96,"_55":56,"_57":58,"_59":97,"_61":62,"_63":64,"_65":98,"_67":68,"_69":70,"_71":72,"_73":72,"_74":72},6084423,"House subcommittee hears witnesses on AI's promise and risks for K‑12 schools",7522,426000,7948000,"/Search/View?dp=1&key=2916234-c6b76d0a099731821ef39491ceab023e&start=426&end=7948","https://assets.pipeline.soar.com/2916234-c6b76d0a099731821ef39491ceab023e/thumbnail_426000.jpg","/articles/6084423/House-subcommittee-hears-witnesses-on-AIs-promise-and-risks-for-K12-schools","https://secure.pipeline.soar.com/6084423-3d57412d813d23fb4aaf120297c5b25b/orig.mp4?Expires=1770998936&Signature=APlZbuBMpbp5fG9-Mmy6dHpQNXETtA0mAaKBD1i0snYFI9aYb5tvgboCn-W3bRjhu9s6V7D3QFG-HRCfqJvMhxgRRLnd3tE5DAJUqP6KWdUFIYfuHn9Q-HPxtdrydJNZNcTOmCGDMf7oegSrwFiOoWdj9i4xYWe9sDEECjhR1V1w8RAgPXL55NVvbXehaFdzhwZHuD50X57V9fsFkHCUCGHWZtk-acQp0Sdtw9Z0~qrxzis0aXNA3adjo~ltGrBafN-2Dzv3ABMqPh7E-1bB447b9--J6A4Sjwe7cnXA8qeOsrykBV0a7uhoknWTnF5baEl6DATRSNLxq7X2BBnyuQ__&Key-Pair-Id=KUT5TJCACFTXG","The Subcommittee on Early Childhood, Elementary, and Secondary Education convened a hearing on artificial intelligence in K‑12 education on Oct. 12, 2025, where witnesses described both rapid technological gains and pressing policy gaps. Chairman Kiley opened the hearing by noting the speed of recent AI advances: \"Artificial intelligence has been advancing at such a rapid pace ... that by the end of this hearing, anything we say this morning will probably be outdated,\" he said.

Witnesses described practical classroom benefits alongside systemic risks. Dr. Sid Dobrin, chair of the Department of English at the University of Florida, said the arrival of generative AI marked “a turning point in education” and argued that schools should teach students how the tools work, not merely how to use them. Dr. Julia Rafalvaire, CEO of ILO Group, recommended that the federal role be “intentionally limited” while supporting common cybersecurity and data‑privacy guidance and funding research. Erin Moe of Innovate EDU urged investments in professional development and safety frameworks. Chris Chisholm, superintendent of Pearl Public School District in Mississippi, described a district pilot that created a locally hosted AI agent to speed grading and retain veteran teachers.

The hearing framed three interlocking issues. First, witnesses emphasized instructional potential: AI tutors and agents can provide high‑dosage, individualized practice and free teachers from time‑consuming administrative tasks. The opening testimony cited research that high‑dosage tutoring can produce substantial learning gains and a McKinsey estimate that AI tools could save teachers as much as 13 hours per week.

Second, witnesses warned of equity and civil‑rights risks if federal capacity and oversight shrink. Ranking Member Suzanne Bonamici and multiple witnesses raised concerns about cuts to the Department of Education’s Office of Educational Technology and to the Institute of Education Sciences, arguing those reductions would hamper research, data availability and federal guidance that districts rely on to protect student privacy and civil rights.

Third, witnesses urged pragmatic safeguards: keeping humans in the loop for assessments and individualized education program (IEP) decisions; investing in AI literacy for educators, parents and students; and establishing state‑level vetting processes or “AI assurance labs” to evaluate tools in context. Dr. Rafalvaire and others recommended federal support focused on data privacy, cybersecurity standards and large‑scale research rather than prescriptive curricular mandates.

The hearing included district‑level examples and research references: a classroom use of Khan Academy’s Conmigo was shown as an illustration of supplemental tutoring; survey data cited in testimony reported that nearly 50% of K‑12 students use ChatGPT at least weekly and that 35% of AI‑using students frequently use it to summarize materials. Witnesses also pointed to surveys showing uneven educator adoption—about 25% of teachers report using AI in classroom preparation—and to district pilots that host models on local servers to address FERPA concerns.

No formal policy actions or votes occurred at the hearing. Committee members and witnesses repeatedly called for more research, clearer guidance on privacy and security, and sustained investment in educator training and infrastructure to avoid widening the digital divide.

The hearing record was left open for 14 days for submissions, and members were reminded they could submit statements through the clerk.","A House Education and Labor subcommittee heard witnesses describe AI's potential to personalize learning and reduce teachers' workloads while warning about privacy, bias and gaps in federal capacity after recent Education Department staff cuts.","actionData","errors"]

Article not found

District pilots show practical gains; witnesses push states and feds to fund teacher training and vetting

Witnesses warn AI surveillance and bias could deepen inequities in schools without federal oversight

House subcommittee hears witnesses on AI's promise and risks for K‑12 schools