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https://preppr.ai/blog/10-questions-(and-7-buzzwords)-to-ask-any-ai-vendor-before-you-sign https://preppr.ai/blog/ai-powered-community-libraries-for-emergency-management-sound-great-%E2%80%94-until-you-understand-the-data-lifecycle-justin-snair-justin-snair-chief-executive-officer-founder-preppr-the-complete-exercise-platform-february-13-2026-part-of-building-an-ai-company-in-the-preparedness-space-means-constantly-watching-how-emerging-tools-apply-to-emergency-management.-there-has-always-been-an-interest-in-community-libraries%E2%80%94shared-repositories-where-agencies-can-upload-share-and-find-plans-sops-and-after-action-reports.-recently-however-ai-has-opened-the-opportunity-to-chat-with-and-unlock-this-crowdsourced-collective-knowledge.-it%E2%80%99s-a-compelling-vision-but-it%E2%80%99s-also-where-significant-data-governance-risks-are-currently-hiding.-full-disclosure-preppr-builds-ai-powered-preparedness-tools.-however-we-do-not-co-mingle-data-across-customers.-your-sensitive-data-is-never-shared-with-other-users-or-used-to-train-models.-we-don-t-offer-a-shared-community-library-and-for-the-reasons-i-m-about-to-lay-out-that-is-a-deliberate-choice-at-this-time.-while-most-know-me-today-as-the-ceo-of-preppr-for-much-of-my-career-i-focused-specifically-on-the-intersection-of-practice-policy-and-emerging-risk%E2%80%94working-from-the-military-to-local-community-preparedness-and-national-level-policy-circles.-i-don-t-often-go-back-into-full-%E2%80%9Cconsultant-mode-or-do-long-form-writing-these-days-but-the-structural-issues-emerging-in-our-sector-require-it.-some-may-dismiss-my-positioning-as-competitive-bias.-you-should-be-skeptical-i-have-skin-in-the-game.-but-i-also-have-an-obligation-to-help-our-community-adopt-trustworthy-ai-and-understand-how-to-scrutinize-technology-vendors.-sometimes-that-means-highlighting-architectural-risks-that-aren-t-immediately-obvious.-rather-than-hiding-that-bias-i-am-flagging-it-upfront-so-you-can-read-this-analysis-with-full-context.-i-m-posting-this-on-linkedin-to-facilitate-an-open-industry-discussion-not-a-sales-pitch.-i-am-intentionally-not-naming-any-specific-platform.-the-data-governance-risks-i-m-describing-apply-to-any-vendor-offering-ai-powered-community-libraries-in-this-space.-the-emerging-governance-gap-recently-i%E2%80%99ve-been-tracking-a-new-capability-gaining-traction-in-the-field-community-libraries-where-users-contribute-documents%E2%80%94plans-sops-aars%E2%80%94to-a-shared-platform-wide-repository.-other-users-can-browse-those-documents-chat-with-them-using-ai-and-run-automated-comparisons.-to-be-clear-this-isn-t-a-fringe-concept%E2%80%94it-has-been-highlighted-at-major-industry-conferences-and-endorsed-by-leading-associations.-that-endorsement-carries-weight-in-this-community-and-signals-a-real-hunger-for-shared-knowledge.-however-the-questions-i-m-raising-in-this-post-often-don-t-get-surfaced-in-quick-product-demos-or-conference-announcements%E2%80%94they-require-a-level-of-technical-due-diligence-that-our-community-hasn-t-historically-had-to-apply-to-its-tools.-in-recent-demonstrations-of-this-capability-it-is-often-mentioned-that-users-already-span-government-healthcare-and-the-private-sector.-this-implies-a-cross-sector-mix-of-data-which-makes-the-governance-questions-significantly-harder.-i-like-the-concept-of-an-ai-powered-community-library.-but-knowing-how-ai-technology-works-i-have-questions-about-the-execution.-when-evaluating-these-tools-the-most-critical-question-to-ask-is-what-happens-if-someone-contributes-a-document-and-later-revokes-permission-the-standard-answer-is-straightforward-the-document-would-be-deleted.-okay.-sounds-great-on-the-surface.-but-what-about-all-the-information-already-derived-from-it-%E2%80%94-the-summaries-the-crosswalk-outputs-the-chat-responses-that-pulled-from-it-and-now-live-in-other-users-histories-this-is-where-the-answers-usually-stop.-it-points-to-a-data-governance-complexity-that-this-community-needs-to-understand-before-we-start-feeding-operationally-sensitive-documents-into-shared-ai-systems.-this-isn-t-just-a-technical-challenge-it-s-a-structural-one.-and-we-have-a-long-history-of-underestimating-the-structural-challenges-of-sharing-emergency-management-data.-we-ve-been-trying-to-build-this-for-twenty-years-the-desire-for-a-shared-knowledge-base-in-our-field-isn-t-new.-the-federal-government-has-tried-%E2%80%94-and-largely-failed-%E2%80%94-to-build-one-for-decades.-fema-s-lessons-learned-information-sharing-system-(llis)-was-supposed-to-be-exactly-this-a-national-network-for-sharing-best-practices-after-action-reports-and-lessons-learned-across-the-preparedness-community.-it-launched-after-9-11-accumulated-nearly-23-000-resources-over-more-than-a-decade-and-was-used-by-verified-emergency-response-providers-and-homeland-security-officials-at-every-level-of-government.-then-in-2015-fema-shut-it-down-consolidating-its-contents-into-the-naval-postgraduate-school-s-homeland-security-digital-library.-1-the-community-largely-moved-on-without-it.-the-homeland-security-information-network-(hsin)-had-an-even-rougher-run.-intended-as-dhs-s-primary-nationwide-information-sharing-tool-it-was-rushed-to-deployment-under-the-pressure-of-the-post-9-11-threat-environment.-by-2007-gao-was-testifying-before-congress-that-hsin-had-landed-on-omb-s-management-watch-list-and-high-risk-list-%E2%80%94-officially-labeled-a-poorly-planned-and-poorly-performing-project.-2-gao-found-nearly-a-dozen-overlapping-homeland-security-networks-within-dhs-costing-over-300-million-annually-with-poor-coordination-between-them.-the-system-had-been-built-around-law-enforcement-requirements-without-sufficiently-identifying-the-needs-of-other-hsin-user-communities-such-as-emergency-management-personnel.-hsin-still-exists-today-but-those-early-failures-set-a-pattern-that-shaped-how-the-em-community-thinks-about-shared-information-systems-cautiously.-so-when-a-commercial-platform-offers-a-community-library-with-ai-on-top-%E2%80%94-the-ability-to-chat-with-shared-documents-using-ai-not-just-browse-them-%E2%80%94-i-understand-the-appeal.-these-platforms-are-stepping-into-a-space-the-government-never-figured-out-how-to-fill.-and-the-ai-layer-is-genuinely-compelling.-but-cross-user-data-co-mingling-%E2%80%94-documents-outputs-and-ai-generated-insights-flowing-between-contributors-and-consumers-%E2%80%94-is-one-of-those-ideas-that-sounds-great-on-the-surface.-what-s-better-than-sharing-with-your-colleagues-automatically-the-problem-is-that-it-faces-significant-challenges-under-scrutiny-by-anyone-with-a-solid-understanding-of-both-the-technology-and-the-use-case.-ai-fundamentally-changes-the-data-governance-equation-in-ways-that-llis-and-hsin-never-had-to-worry-about.-what-actually-happens-when-you-contribute-a-document-to-an-ai-system-when-you-upload-a-document-to-a-traditional-shared-library-it-sits-in-a-folder.-someone-opens-it-reads-it-or-downloads-a-copy.-simple.-if-you-remove-it-the-source-is-gone.-ai-powered-platforms-work-differently.-there-s-a-preliminary-question-worth-addressing-what-screening-happens-before-a-document-enters-the-system-at-all-some-platforms-rely-on-manual-review-by-internal-teams.-that-s-a-start.-but-checking-for-pii-hipaa-concerns-and-content-that-shouldn-t-be-shared-publicly-is-complex.-documents-contributed-from-different-states-carry-different-legal-protections-open-records-obligations-liability-exposures-and-regulatory-constraints.-a-hospital-surge-plan-from-california-raises-different-legal-questions-than-one-from-texas.-a-county-evacuation-plan-may-be-subject-to-public-records-laws-in-one-state-and-exempt-in-another.-unless-legal-experts-familiar-with-each-contributing-sector-are-reviewing-every-document-manual-screening%E2%80%94however-well-intentioned%E2%80%94may-miss-the-specific-legal-risks-that-matter-most.-furthermore-manual-review-is-difficult-to-scale-without-eventually-relying-on-automation-which-introduces-its-own-accuracy-questions.-even-assuming-the-intake-screening-is-solid-here-s-what-happens-next-in-a-typical-rag-(retrieval-augmented-generation)-architecture-when-a-document-enters-the-system-it-gets-broken-into-chunks.-each-chunk-is-converted-into-a-mathematical-representation-called-a-vector-embedding-and-stored-in-a-specialized-database.-when-a-user-asks-a-question-the-system-searches-those-embeddings-to-find-the-most-relevant-content-feeds-it-to-a-large-language-model-and-generates-a-response.-that-response%E2%80%94the-summary-the-crosswalk-output-the-answer-to-a-chat-question%E2%80%94gets-stored-in-the-requesting-user-s-conversation-history.-now-imagine-dozens-of-users-chatting-with-a-contributed-document-over-the-course-of-several-months.-running-crosswalks.-generating-summaries.-each-interaction-produces-ai-outputs-that-weave-in-content-from-the-original-document.-those-outputs-live-in-other-users-accounts.-when-the-contributor-revokes-permission-the-platform-can-delete-the-source-file-and-the-embeddings.-that-stops-future-retrieval.-but-standard-deletion-processes-rarely-reach-back-into-every-conversation-every-crosswalk-report-and-every-exported-summary-where-the-document-s-content-was-already-synthesized.-the-source-is-gone.-but-unless-the-platform-has-built-highly-specific-mechanisms-to-trace-and-handle-derived-works-%E2%80%94-which-is-a-hard-engineering-problem-that-most-haven-t-solved-%E2%80%94-traces-of-that-intelligence-persist-indefinitely.-this-is-the-difference-between-pulling-a-book-off-a-library-shelf-and-erasing-everything-anyone-learned-from-reading-it.-one-is-a-file-operation.-the-other-requires-tracking-provenance-and-tracing-content-from-those-documents-to-every-single-use-throughout-the-platform.-it-is-a-significant-engineering-and-governance-challenge-that-requires-deliberate-architectural-choices.-this-problem-is-already-creating-real-consequences-before-i-get-into-examples-an-important-technical-distinction-there-are-three-different-ways-your-data-can-end-up-living-inside-an-ai-system.-pre-training-the-process-of-building-a-foundational-model-like-gpt-5-or-claude-from-scratch-using-massive-datasets.-the-information-doesn-t-sit-in-the-model-as-retrievable-files-it-s-encoded-as-patterns-distributed-across-the-model-s-weights.-deleting-the-source-data-after-training-doesn-t-change-the-model-s-behavior-because-the-learning-has-already-happened.-fine-tuning-an-existing-foundational-model-is-adjusted-on-a-smaller-domain-specific-dataset-to-improve-its-performance-in-a-particular-area.-fine-tuning-also-modifies-the-model-s-internal-weights-so-it-carries-a-similar-baked-in-problem-%E2%80%94-just-at-a-smaller-scale.-retrieval-augmented-generation-(rag)-in-a-rag-system-the-ai-model-itself-isn-t-retrained-on-your-documents.-instead-your-documents-are-chunked-embedded-stored-externally-and-made-available-to-the-ai-model.-when-a-user-asks-a-question-the-system-retrieves-relevant-chunks-and-feeds-them-to-the-model-as-context-for-generating-a-response.-to-be-fair-terminology-varies.-i-have-heard-the-term-tuning-used-colloquially-in-marketing-for-this-type-of-feature.-if-a-platform-is-actually-fine-tuning-models-on-contributed-content-the-data-is-baked-into-the-model.-however-it-is-more-likely-that-tuning-is-being-used-to-describe-rag-customization.-even-with-rag-the-derived-content-problem-remains.-the-model-didn-t-learn-your-content-permanently-but-it-read-your-content-synthesized-it-and-delivered-it-to-other-users-in-a-form-that-s-now-stored-in-their-history.-with-that-distinction-in-mind-each-of-the-architectures-have-already-produced-real-world-consequences.-training-based-the-openai-precedent-in-march-2023-italy-s-data-protection-authority-temporarily-banned-chatgpt-from-processing-italian-users-data.-the-core-issue-openai-had-used-personal-information-to-train-its-models-%E2%80%94-baking-it-into-the-model-weights-%E2%80%94-without-adequate-legal-basis-and-there-was-no-meaningful-mechanism-for-individuals-to-request-erasure-once-their-data-had-shaped-the-model-s-behavior.-the-ban-was-lifted-within-a-month-after-openai-took-corrective-steps.-but-the-investigation-continued-for-nearly-two-years.-in-december-2024-italy-fined-openai-%E2%82%AC15-million-(roughly-16-million)-finding-that-the-company-had-processed-personal-information-of-users-to-train-chatgpt-without-having-an-adequate-legal-basis-and-failed-transparency-obligations.-3-the-fine-was-notable-but-the-underlying-principle-was-more-important-regulators-are-starting-to-treat-ai-generated-outputs-%E2%80%94-not-just-source-data-%E2%80%94-as-part-of-the-data-governance-equation.-rag-based-the-problems-closest-to-home-the-examples-above-involve-data-permanently-encoded-into-model-weights.-but-rag-specific-risks-are-emerging-too-%E2%80%94-and-they-re-closer-to-what-a-community-library-platform-would-actually-be-doing.-microsoft-copilot-and-the-oversharing-problem.-microsoft-365-copilot-uses-rag-to-pull-from-an-organization-s-sharepoint-onedrive-teams-and-outlook-data-to-generate-responses.-researchers-at-the-university-of-texas-discovered-a-class-of-vulnerabilities-they-named-confusedpilot-demonstrating-that-copilot-s-rag-pipeline-could-be-manipulated-into-surfacing-sensitive-information-across-permission-boundaries.-10-separately-security-firm-lasso-found-that-copilot-could-expose-data-from-fortune-500-companies-due-to-overly-permissive-retrieval-scopes-%E2%80%94-the-same-rag-architecture-retrieving-content-users-shouldn-t-have-had-access-to-and-delivering-it-in-ai-generated-responses.-enterprise-rag-pipelines-leaking-sensitive-content.-security-researchers-have-documented-cases-where-enterprise-rag-systems-surfaced-api-keys-buried-in-embedded-markdown-files-slides-from-non-public-board-decks-retrieved-through-routine-queries-and-confidential-contract-details-%E2%80%94-including-pricing-%E2%80%94-served-up-because-the-rag-index-was-too-broadly-scoped.-12-this-isn-t-about-malicious-actors.-it-s-about-what-happens-when-a-rag-system-in-a-shared-environment-does-exactly-what-it-s-designed-to-do-%E2%80%94-retrieve-and-synthesize-content-across-users-%E2%80%94-without-adequate-governance.-who-controls-what-gets-retrieved-who-sees-the-output-and-what-happens-to-that-output-after-it-s-generated-samsung-when-contributed-content-becomes-irrecoverable.-in-one-of-the-most-widely-reported-ai-data-incidents-samsung-engineers-pasted-proprietary-semiconductor-source-code-and-confidential-meeting-notes-into-chatgpt-to-get-help-debugging-and-optimizing-their-work.-because-chatgpt-retained-user-inputs-for-training-samsung-s-trade-secrets-were-now-in-openai-s-system-%E2%80%94-and-samsung-had-no-mechanism-to-retrieve-or-delete-them.-14-the-difference-is-that-samsung-employees-did-it-accidentally.-a-community-library-invites-users-to-do-it-by-design.-the-emerging-regulatory-framework-the-direction-is-clear-across-multiple-jurisdictions-the-oecd-published-guidance-acknowledging-that-the-right-to-erasure-might-be-invoked-in-relation-to-llms-and-that-removing-personal-data-from-training-datasets-does-not-directly-affect-the-already-trained-models.-17-germany-s-conference-of-data-protection-authorities-published-guidance-specifically-addressing-rag-(retrieval-augmented-generation)-%E2%80%94-the-exact-architecture-that-a-community-library-with-document-chat-and-crosswalk-features-would-use-%E2%80%94-and-its-data-protection-implications.-18-the-eu-ai-act-which-began-phased-enforcement-in-august-2025-requires-data-governance-documentation-across-the-ai-system-lifecycle-including-how-data-flows-through-retrieval-pipelines.-19-closer-to-home-organizations-building-emerging-community-library-tools-report-having-users-across-government-hospitals-and-the-private-sector.-that-mix-exposes-a-u.s.-specific-governance-gap-that-needs-to-be-addressed.-the-federal-government-recognized-years-ago-that-cross-sector-sharing-of-sensitive-critical-infrastructure-information-required-a-dedicated-legal-structure.-that-structure-was-the-critical-infrastructure-partnership-advisory-council-(cipac)-established-by-the-department-of-homeland-security-with-a-targeted-exemption-from-the-federal-advisory-committee-act-(faca).-it-allowed-government-and-private-sector-partners-to-exchange-threat-intelligence-and-infrastructure-information-candidly-without-triggering-public-disclosure-requirements.-building-that-trust-architecture-took-nearly-two-decades.-yet-cipac-was-terminated-by-dhs-on-march-7-2025-and-the-cybersecurity-information-sharing-act%E2%80%94which-helped-underpin-related-information-sharing-protections%E2%80%94was-set-to-expire-later-that-year.-layered-onto-this-is-the-intersection-of-state-sunshine-laws-public-records-obligations-and-records-retention-requirements-with-ai-generated-derivative-content-inside-commercial-platforms.-that-terrain-remains-largely-untested.-if-a-state-or-local-agency-uploads-documents-into-a-commercial-ai-powered-community-library-do-those-materials-remain-subject-to-open-records-laws-more-pointedly-do-ai-generated-outputs-that-synthesize-government-contributed-information-themselves-become-public-records-why-emergency-management-should-care-more-than-most-why-emergency-management-should-care-more-than-most-most-of-the-enforcement-actions-above-involve-personal-data-%E2%80%94-names-faces-chat-histories.-emergency-management-community-libraries-involve-something-different-but-equally-sensitive-operational-and-sensitive-data.-a-community-library-that-co-mingles-documents-across-all-three-sectors-(government-healthcare-private)-is-navigating-hipaa-foia-trade-secret-protections-and-sector-specific-compliance-requirements-simultaneously.-three-scenarios-worth-thinking-through-the-un-retractable-vulnerability.-a-hospital-system-shares-a-hazard-vulnerability-analysis-(hva)-identifying-a-critical-gap-in-their-backup-power-systems.-another-user%E2%80%94perhaps-a-competitor-or-a-regulator%E2%80%94asks-the-ai-to-summarize-regional-infrastructure-risks.-the-ai-generates-a-report-explicitly-detailing-that-hospital-s-power-gap.-the-hospital-later-revokes-the-document.-the-source-file-vanishes.-but-the-report-identifying-their-vulnerability-remains-in-the-other-user-s-account%E2%80%94potentially-discoverable-potentially-public-and-now-completely-outside-the-contributor-s-control.-the-zombie-evacuation-route.-a-county-emergency-manager-contributes-an-evacuation-plan.-six-months-later-a-bridge-on-a-primary-route-is-condemned-and-they-upload-a-revised-plan-deleting-the-old-one.-but-users-in-neighboring-jurisdictions-have-already-asked-the-ai-to-list-evacuation-routes-for-county-x.-those-ai-generated-lists%E2%80%94referencing-the-now-dangerous-route%E2%80%94persist-in-their-chat-histories.-during-a-crisis-a-mutual-aid-partner-might-act-on-that-zombie-intelligence-believing-it-to-be-current-because-it-came-from-the-trusted-community-platform.-the-governance-death-spiral.-this-is-the-macro-risk.-once-it-becomes-clear-that-deleting-a-document-doesn-t-scrub-the-intelligence-derived-from-it-the-incentive-structure-flips.-general-counsels-will-block-participation.-agencies-will-stop-sharing-operational-plans-and-start-sharing-only-sanitized-useless-brochures.-the-community-library-concept-dies%E2%80%94not-because-the-tech-failed-but-because-the-governance-model-couldn-t-guarantee-the-one-thing-contributors-need-most-control.-the-questions-that-need-to-be-asked-%E2%80%94-and-answered-before-you-contribute-documents-or-subscribe-to-ai-powered-community-libraries-ask-these-questions.-these-are-the-minimum-due-diligence.-before-you-contribute-what-exactly-am-i-authorizing-when-i-upload-a-document-to-a-community-library-does-my-content-become-training-data-retrieval-context-or-both-can-i-see-which-users-or-features-have-accessed-my-contributed-documents-does-the-platform-s-terms-of-service-explicitly-address-what-happens-to-derived-content-on-revocation-when-i-revoke-permission-what-specifically-gets-deleted-%E2%80%94-the-file-the-vector-embeddings-or-both-what-happens-to-ai-generated-outputs-that-already-incorporated-my-content-before-revocation-are-other-users-notified-that-source-material-underlying-their-saved-outputs-has-been-withdrawn-on-derived-content-governance-does-the-platform-distinguish-between-source-documents-and-content-derived-from-them-is-there-any-mechanism-to-flag-expire-or-invalidate-ai-outputs-whose-source-material-has-been-revoked-how-does-the-platform-handle-the-risk-that-outdated-information-persists-in-derived-form-long-after-the-source-is-updated-or-removed-building-this-right-i-want-to-be-clear-i-m-not-arguing-against-ai-powered-community-libraries.-the-need-is-real.-two-decades-of-failed-federal-attempts-to-build-shared-preparedness-knowledge-infrastructure-prove-that.-llis-accumulated-23-000-resources-and-still-couldn-t-sustain-itself.-hsin-cost-hundreds-of-millions-and-still-wasn-t-built-for-the-people-who-needed-it-most.-the-appetite-for-this-capability-is-enormous-and-legitimate.-ai-powered-community-libraries-have-the-potential-to-finally-deliver-what-those-systems-couldn-t.-but-they-also-introduce-a-category-of-risk-those-earlier-systems-never-faced.-a-shared-folder-of-pdfs-is-straightforward-to-govern.-an-ai-system-that-ingests-synthesizes-and-redistributes-contributed-content-across-thousands-of-user-interactions-is-a-fundamentally-different-thing.-the-platforms-building-these-features-owe-their-users-%E2%80%94-particularly-users-in-a-community-where-operational-security-matters-and-trust-is-the-currency-that-makes-mutual-aid-work-%E2%80%94-an-honest-accounting-of-the-full-content-lifecycle.-not-just-the-upload-and-the-deletion-but-everything-that-happens-in-between.-including-the-parts-that-are-hard-to-undo.-sources-fema-lessons-learned-information-sharing-consolidation.-in-spring-2015-the-llis.gov-website-ceased-independent-operations-and-delivered-nearly-23-000-resources-to-the-naval-postgraduate-school-s-homeland-security-digital-library.-see-hsdl---fema-llis-hs-today-coverage.-gao-testimony-on-hsin.-david-powner-director-of-it-management-issues-testified-that-hsin-was-on-omb-s-management-watch-list-and-high-risk-list-with-nearly-a-dozen-overlapping-dhs-networks-costing-300m-annually.-see-gao-07-822t-congressional-hearing-record-chrg-110hhrg48909.-italy-fines-openai-%E2%82%AC15-million.-the-garante-found-openai-processed-personal-data-without-adequate-legal-basis-and-failed-transparency-obligations.-see-the-hacker-news-lewis-silkin-analysis.-eu-wide-chatgpt-investigations.-the-european-data-protection-board-launched-a-dedicated-chatgpt-task-force-in-april-2023.-dpas-in-germany-france-spain-and-other-member-states-initiated-preliminary-investigations.-see-lexology-freshfields-analysis.-dutch-dpa-fines-clearview-ai-%E2%82%AC30.5-million.-see-complydog-analysis.-italian-dpa-fines-clearview-ai-%E2%82%AC20-million.-see-mit-technology-review.-uk-ico-clearview-ai-enforcement.-original-%C2%A37.5m-fine-issued-may-2022-first-tier-tribunal-overturned-on-jurisdiction-upper-tribunal-reversed-in-october-2025-ruling-uk-gdpr-applies-regardless-of-company-location.-see-the-register-infosecurity-magazine.-canada-s-privacy-commissioner-on-clearview-ai.-commissioner-daniel-therrien-what-clearview-does-is-mass-surveillance-and-it-is-illegal.-see-wikipedia---clearview-ai.-australia-calls-off-clearview-investigation-without-evidence-of-compliance.-see-infosecurity-magazine.-microsoft-copilot-rag-vulnerabilities.-roychowdhury-et-al.-confusedpilot-compromising-enterprise-information-integrity-and-confidentiality-with-copilot-for-microsoft-365-university-of-texas-at-austin-spark-research-lab-august-2024.-see-arxiv-lasso-security-fortune-500-data-exposure-findings-lasso-security-coverage-it-pro.-us-congress-bans-copilot-for-staff.-see-metomic-enterprise-safety-guide.-enterprise-rag-pipeline-data-leakage-incidents.-security-red-team-findings-including-api-key-exposure-board-deck-retrieval-and-contract-details-surfaced-through-routine-queries.-see-we45-security-sombra-inc..-zeng-et-al.-the-good-and-the-bad-exploring-privacy-issues-in-retrieval-augmented-generation-(rag)-findings-of-the-association-for-computational-linguistics-acl-2024.-demonstrates-rag-systems-vulnerability-to-leaking-private-retrieval-database-contents.-see-acl-anthology.-samsung-chatgpt-data-leak.-engineers-pasted-proprietary-source-code-and-meeting-notes-into-chatgpt-samsung-banned-the-tool-stating-the-data-was-irrecoverable.-see-techcrunch-the-register.-clearview-ai-bipa-class-action-settlement.-in-re-clearview-ai-inc.-consumer-privacy-litigation-no.-1-21-cv-00135-u.s.-district-court-for-the-northern-district-of-illinois.-see-clearviewclassaction.com.-ftc-civil-investigative-demand-to-openai-july-2023.-see-eye-on-privacy-sheppard-mullin.-oecd-guidance-on-data-access-requests-in-ai-driven-processing.-notes-that-erasure-rights-may-apply-to-llms-and-that-removing-data-from-training-sets-does-not-directly-affect-the-already-trained-models.-see-oecd.ai.-german-data-protection-conference-publishes-rag-specific-guidance-2025.-see-cms-lawnow---2025-in-data-protection.-eu-ai-act-data-governance-requirements.-article-10-requires-training-validation-and-testing-datasets-to-be-relevant-sufficiently-representative-and-free-of-errors.-phased-enforcement-began-august-2025.-see-artificialintelligenceact.eu.-techpolicy.press-on-the-right-to-be-forgotten-in-ai.-gdpr-article-17-grants-individuals-the-right-to-request-data-erasure-but-it-does-not-define-erasure-in-the-context-of-ai.-see-techpolicy.press.-cipac-termination-and-cisa-2015-expiration.-dhs-terminated-cipac-in-march-2025-as-part-of-a-broader-dissolution-of-advisory-committees.-the-cybersecurity-information-sharing-act-of-2015-which-provided-legal-protections-for-cross-sector-threat-intelligence-sharing-was-set-to-expire-september-30-2025.-see-ropes-gray-axios-hogan-lovells. 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