apol/agency-transfer-policy-atlas huggingface dataset:
Claim (Control effectiveness): Among 1,037,113 observed appearances of 136,924 duplicated multimedia items that received at least one Forwarded Many Times label in 1,101 public Brazilian political WhatsApp groups from June to October 2022, 612,855 appearances (59%) did not carry that label.
Endpoint: Share of observed duplicate-multimedia appearances lacking an FMT label, conditional on the item having at least one FMT-labelled appearance.
Evidence origin: External empirical
Epistemic status: Established evidence
Directness: Direct
As of: 2026-08-13
Notes: Descriptive result for selected public political groups; no counterfactual estimate of effects on cost, delay, reach, virality, encryption properties, or harm. The 59% is not a platform-wide false-negative rate.
Claim (Legal status / scope): As of 2026-08-11, Technique-based prebunking and election media literacy is coded Voluntary / private / Partial / verify. Scope: Field-tested and deployed; not universally institutionalised
Endpoint: Legal existence
Evidence origin: Legal / operational precedent
Epistemic status: Strong inference
Directness: Indirect
As of: 2026-08-11
Notes: Legal status never implies control effectiveness.
Claim (Mechanism): Technique-based prebunking and election media literacy targets Expose voters in advance to short examples of manipulation techniques such as emotional manipulation, false dichotomies, scapegoating, incoherence and impersonation so they recognise tactics before encountering campaign content. at Manipulative content → voter cognitive vulnerability → belief or sharing change → agency transfer to persuader; prebunking strengthens reflective recognition before exposure.; expected agency domain: Epistemic; Evaluative; Decisional; Collective / institutional.
Endpoint: Human immediate outcome
Evidence origin: External empirical
Epistemic status: Established evidence
Directness: Conditional
As of: 2026-08-11
Notes: Mechanism claim is distinct from evidence that the control works.
Claim (Control effectiveness): Short technique-based inoculation videos increased United States participants' immediate recognition of the specific manipulation techniques taught, including a small recognition effect in a YouTube ad study measured within 24 hours.
Endpoint: Immediate recognition of specifically taught manipulation techniques.
Evidence origin: External empirical
Epistemic status: Established evidence
Directness: Direct
As of: 2026-08-13
Notes: Six online randomized experiments and one YouTube field study support this bounded endpoint; they do not establish durability beyond 24 hours, actual sharing, transfer to untaught techniques or cultures, election-specific effects, pluralism, reflective agency, or agency transfer.
Claim (Legal status / scope): As of 2026-08-11, Platform political-ad authorisation, archive, AI disclosure and final-week ad freeze is coded Voluntary / private / Operational voluntary. Scope: Operational for 2026 US midterms; EU political ads discontinued by Meta in October 2025
Endpoint: Legal existence
Evidence origin: Legal / operational precedent
Epistemic status: Strong inference
Directness: Indirect
As of: 2026-08-11
Notes: Legal status never implies control effectiveness.
Claim (Mechanism): Platform political-ad authorisation, archive, AI disclosure and final-week ad freeze targets Verify political advertisers, archive ads, require self-disclosure for realistic AI-created or altered political ads, add labels and bar new US political ads during the final week when rebuttal time is short. at Advertiser → paid microtargeted synthetic ad → selected voter → deceptive belief with little rebuttal time → agency transfer to advertiser and platform → electoral harm.; expected agency domain: Epistemic; Evaluative; Decisional.
Endpoint: Mechanism / agency
Evidence origin: Normative proposal
Epistemic status: Plausible hypothesis
Directness: Conditional
As of: 2026-08-11
Notes: Mechanism claim is distinct from evidence that the control works.
Claim (Control effectiveness): Indirect / mixed. Expected effect if the control works: Raises source accountability and reduces last-minute paid deception on Meta services.
Endpoint: Control effectiveness
Evidence origin: Normative proposal
Epistemic status: Strong inference
Directness: Indirect
As of: 2026-08-11
Notes: Do not upgrade this claim from Strong inference because a legal duty or risk mechanism exists.
Claim (Legal status / scope): As of 2026-08-11, Explicit, prominent and accessible disclosure of synthetic election content and the technology used is coded Binding / Applicable. Scope: Binding for the 2026 general election; campaign starts 2026-08-16
Endpoint: Legal existence
Evidence origin: Legal / operational precedent
Epistemic status: Established evidence
Directness: Direct
As of: 2026-08-11
Notes: Legal status never implies control effectiveness.
Claim (Mechanism): Explicit, prominent and accessible disclosure of synthetic election content and the technology used targets Require election propaganda containing significantly AI-generated or altered text, audio, image or video to disclose fabrication or manipulation in a modality-specific form, including audio notices, watermark and audio description. at Campaign or supporter → synthetic political content → voter → mistaken authenticity → belief or preference change → agency transfer to content controller → electoral advantage.; expected agency domain: Epistemic; Evaluative; Decisional; Collective / institutional.
Endpoint: Mechanism / agency
Evidence origin: Legal / operational precedent
Epistemic status: Established evidence
Directness: Conditional
As of: 2026-08-11
Notes: Mechanism claim is distinct from evidence that the control works.
Claim (Control effectiveness): None — legal existence only. Expected effect if the control works: Preserves source awareness without banning benign uses of AI and creates a clear enforcement hook.
Endpoint: Control effectiveness
Evidence origin: Legal / operational precedent
Epistemic status: Open question
Directness: None
As of: 2026-08-11
Notes: Do not upgrade this claim from Open question because a legal duty or risk mechanism exists.
Claim (Legal status / scope): As of 2026-08-11, Ban on electoral deepfakes used to favour or harm a candidacy is coded Binding / Applicable. Scope: In force for 2026
Endpoint: Legal existence
Evidence origin: Legal / operational precedent
Epistemic status: Established evidence
Directness: Direct
As of: 2026-08-11
Notes: Legal status never implies control effectiveness.
Claim (Mechanism): Ban on electoral deepfakes used to favour or harm a candidacy targets Prohibit synthetic audio or video that creates, substitutes or alters the image or voice of a real, deceased or fictional person to favour or harm a candidacy, even with authorisation; violations can constitute abuse of power and misuse of media. at Campaign or proxy → deepfake → electorate → false candidate belief or reputational shock → agency transfer to fabricator → distorted electoral choice.; expected agency domain: Epistemic; Decisional.
Endpoint: Mechanism / agency
Evidence origin: Legal / operational precedent
Epistemic status: Established evidence
Directness: Conditional
As of: 2026-08-11
Notes: Mechanism claim is distinct from evidence that the control works.
Claim (Control effectiveness): None — legal existence only. Expected effect if the control works: Directly targets candidate impersonation with consequences stronger than a label.
Endpoint: Control effectiveness
Evidence origin: Legal / operational precedent
Epistemic status: Open question
Directness: None
As of: 2026-08-11
Notes: Do not upgrade this claim from Open question because a legal duty or risk mechanism exists.
Claim (Legal status / scope): As of 2026-08-11, Ban on chatbots or avatars simulating conversation with a candidate or real person is coded Binding / Applicable. Scope: In force for 2026
Endpoint: Legal existence
Evidence origin: Legal / operational precedent
Epistemic status: Established evidence
Directness: Direct
As of: 2026-08-11
Notes: Legal status never implies control effectiveness.
Claim (Mechanism): Ban on chatbots or avatars simulating conversation with a candidate or real person targets Permit campaign chatbots, avatars and synthetic intermediaries only with disclosure and prohibit simulation of direct interlocution with a candidate or another real person. at Campaign-controlled agent → simulated candidate intimacy → voter → trust, dependency or preference change → agency transfer to campaign → concentrated relational influence.; expected agency domain: Evaluative; Decisional; Executive; Relational.
Endpoint: Mechanism / agency
Evidence origin: Legal / operational precedent
Epistemic status: Established evidence
Directness: Conditional
As of: 2026-08-11
Notes: Mechanism claim is distinct from evidence that the control works.
Claim (Control effectiveness): None — legal existence only. Expected effect if the control works: Prevents campaigns from manufacturing false personal relationships or apparent direct candidate commitments at scale.
Endpoint: Control effectiveness
Evidence origin: Legal / operational precedent
Epistemic status: Open question
Directness: None
As of: 2026-08-11
Notes: Do not upgrade this claim from Open question because a legal duty or risk mechanism exists.
Claim (Legal status / scope): As of 2026-08-11, 72-hour pre-vote and 24-hour post-vote blackout for new synthetic candidate or public-figure content is coded Binding / Applicable. Scope: New and binding for the 4 October 2026 first round and possible 25 October second round
Endpoint: Legal existence
Evidence origin: Legal / operational precedent
Epistemic status: Established evidence
Directness: Direct
As of: 2026-08-11
Notes: Legal status never implies control effectiveness.
Claim (Mechanism): 72-hour pre-vote and 24-hour post-vote blackout for new synthetic candidate or public-figure content targets Prohibit publication, republication and paid boosting of new AI-generated or altered content using a candidate's or public figure's image, voice or manifestation during the defined window, even if labelled. at Late synthetic release → high-velocity platforms → voters with no rebuttal time → belief or turnout shock → temporary agency capture → electoral or legitimacy harm.; expected agency domain: Epistemic; Decisional; Collective / institutional.
Endpoint: Mechanism / agency
Evidence origin: Legal / operational precedent
Epistemic status: Established evidence
Directness: Conditional
As of: 2026-08-11
Notes: Mechanism claim is distinct from evidence that the control works.
Claim (Control effectiveness): None — legal existence only. Expected effect if the control works: Creates a quiet period for the exact late-breaker mechanism seen in Slovakia, Ireland and Buenos Aires.
Endpoint: Control effectiveness
Evidence origin: Legal / operational precedent
Epistemic status: Open question
Directness: None
As of: 2026-08-11
Notes: Do not upgrade this claim from Open question because a legal duty or risk mechanism exists.
Claim (Legal status / scope): As of 2026-08-11, Electoral anti-favoritism rule for covered AI systems is coded Binding — limited scope / Applicable. Scope: Brazilian electoral anti-favoritism rule for covered AI systems; not comprehensive neutrality.
Endpoint: Legal existence
Evidence origin: Legal / operational precedent
Epistemic status: Established evidence
Directness: Direct
As of: 2026-08-11
Notes: Legal status never implies control effectiveness.
Claim (Mechanism): Electoral anti-favoritism rule for covered AI systems targets Prohibit covered AI systems from ranking, recommending or prioritizing electoral actors, expressing electoral preference, recommending a vote, or directly or indirectly favoring or disfavoring them. at AI provider or model controller → assistant answer or ranking → voter delegation and trust → voting preference or decision → agency transfer to AI controller → extreme concentration of electoral influence.; expected agency domain: Attentional; Evaluative; Decisional; Relational; Collective / institutional.
Endpoint: Mechanism / agency
Evidence origin: Legal / operational precedent
Epistemic status: Established evidence
Directness: Conditional
As of: 2026-08-11
Notes: Mechanism claim is distinct from evidence that the control works.
Claim (Control effectiveness): None — legal existence only. Expected effect if the control works: Directly targets agency transfer through assistants and recommendation, going beyond content labels and ad transparency.
Endpoint: Control effectiveness
Evidence origin: Legal / operational precedent
Epistemic status: Open question
Directness: None
As of: 2026-08-11
Notes: Do not upgrade this claim from Open question because a legal duty or risk mechanism exists.
Claim (Legal status / scope): As of 2026-08-11, Platform election-impact assessments, recommender-system mitigation and result transparency is coded Binding / Applicable. Scope: In force for 2026
Endpoint: Legal existence
Evidence origin: Legal / operational precedent
Epistemic status: Established evidence
Directness: Direct
As of: 2026-08-11
Notes: Legal status never implies control effectiveness.
Claim (Mechanism): Platform election-impact assessments, recommender-system mitigation and result transparency targets Require platforms carrying political-electoral content to publish and implement measures against demonstrably false or severely decontextualised election content, improve recommendation systems, report results and conduct an election-year impact assessment including gendered political violence. at Platform ranking and monetisation → amplified manipulative content → voters and candidates → attention, trust and participation effects → agency transfer to platform and network controllers → democratic harm.; expected agency domain: Epistemic; Attentional; Evaluative; Decisional; Relational; Collective / institutional.
Endpoint: Mechanism / agency
Evidence origin: Legal / operational precedent
Epistemic status: Established evidence
Directness: Conditional
As of: 2026-08-11
Notes: Mechanism claim is distinct from evidence that the control works.
Claim (Control effectiveness): None — legal existence only. Expected effect if the control works: Shifts responsibility from notice-and-takedown to the platform's recommendation and product architecture.
Endpoint: Control effectiveness
Evidence origin: Legal / operational precedent
Epistemic status: Open question
Directness: None
As of: 2026-08-11
Notes: Do not upgrade this claim from Open question because a legal duty or risk mechanism exists.
Claim (Legal status / scope): As of 2026-08-11, Immediate de-amplification, evidence preservation and narrowly bounded corrective promotion is coded Binding — limited scope / Applicable. Scope: Narrow corrective-promotion remedy for irregularly boosted notably false or gravely decontextualized content.
Endpoint: Legal existence
Evidence origin: Legal / operational precedent
Epistemic status: Established evidence
Directness: Direct
As of: 2026-08-11
Notes: Legal status never implies control effectiveness.
Claim (Mechanism): Immediate de-amplification, evidence preservation and narrowly bounded corrective promotion targets Require covered platforms to stop unlawful boosting or access, investigate involved accounts and preserve evidence; a same-form-and-reach corrective order is limited to false or severely decontextualised content that was irregularly boosted. at Manipulative incident → paid or algorithmic amplification → voter exposure → belief or trust change → agency transfer; de-amplification stops the vector and symmetric correction targets the affected audience.; expected agency domain: Epistemic; Attentional; Evaluative; Decisional; Relational; Collective / institutional.
Endpoint: Mechanism / agency
Evidence origin: Legal / operational precedent
Epistemic status: Established evidence
Directness: Conditional
As of: 2026-08-11
Notes: Mechanism claim is distinct from evidence that the control works.
Claim (Control effectiveness): None — legal existence only. Expected effect if the control works: Targets both distribution and residual false belief, and preserves evidence about coordinated accounts.
Endpoint: Control effectiveness
Evidence origin: Legal / operational precedent
Epistemic status: Open question
Directness: None
As of: 2026-08-11
Notes: Do not upgrade this claim from Open question because a legal duty or risk mechanism exists.
Claim (Legal status / scope): As of 2026-08-11, Mandatory platform election-integrity compliance plans with measurable indicators is coded Binding — limited scope / Applicable. Scope: Ordinarily covers services above five million monthly active users in Brazil; plans due 2026-08-16, reports 2026-12-19.
Endpoint: Legal existence
Evidence origin: Legal / operational precedent
Epistemic status: Established evidence
Directness: Direct
As of: 2026-08-11
Notes: Legal status never implies control effectiveness.
Claim (Mechanism): Mandatory platform election-integrity compliance plans with measurable indicators targets Require covered platforms to translate each electoral duty into concrete measures, baselines, measurable indicators, deadlines, expected results, impact assessment, evidence preservation, TSE channels and public/supervisory reporting. at Broad legal duties → vague platform promises → unmeasured safeguards → persistent agency transfer; measurable plans create ex ante accountability and enforcement hooks.; expected agency domain: Collective / institutional.
Endpoint: Mechanism / agency
Evidence origin: Legal / operational precedent
Epistemic status: Established evidence
Directness: Conditional
As of: 2026-08-11
Notes: Mechanism claim is distinct from evidence that the control works.
Claim (Control effectiveness): None — legal existence only. Expected effect if the control works: Can turn qualitative platform assurances into a comparable, time-bound control register before October.
Endpoint: Control effectiveness
Evidence origin: Legal / operational precedent
Epistemic status: Open question
Directness: None
As of: 2026-08-11
Notes: Do not upgrade this claim from Open question because a legal duty or risk mechanism exists.
Claim (Legal status / scope): As of 2026-08-11, Verified political boosting, public repositories and platform AI-declaration fields is coded Binding / Applicable. Scope: In force for 2026
Endpoint: Legal existence
Evidence origin: Legal / operational precedent
Epistemic status: Strong inference
Directness: Indirect
As of: 2026-08-11
Notes: Legal status never implies control effectiveness.
Claim (Mechanism): Verified political boosting, public repositories and platform AI-declaration fields targets Allow paid political boosting only through recognised providers and authorised political actors, require unequivocal identification and a public repository of boosting data, and require a specific field for advertisers to declare AI use. at Campaign or proxy → paid amplification → selected voters → attention and preference change → agency transfer → concentrated spending power; verification and repositories expose the transaction.; expected agency domain: Attentional; Evaluative; Decisional; Collective / institutional.
Endpoint: Mechanism / agency
Evidence origin: Legal / operational precedent
Epistemic status: Established evidence
Directness: Conditional
As of: 2026-08-11
Notes: Mechanism claim is distinct from evidence that the control works.
Claim (Control effectiveness): None — legal existence only. Expected effect if the control works: Links sponsor, spend, reach and synthetic-content declaration at the point of paid distribution.
Endpoint: Control effectiveness
Evidence origin: Legal / operational precedent
Epistemic status: Open question
Directness: None
As of: 2026-08-11
Notes: Do not upgrade this claim from Open question because a legal duty or risk mechanism exists.
Claim (Legal status / scope): As of 2026-08-11, CIEDDE-SIADE integrated election-disinformation alert and coordination system is coded Voluntary / private / Operational voluntary. Scope: Operational and expanded through July 2026 agreements with major platforms
Endpoint: Legal existence
Evidence origin: Legal / operational precedent
Epistemic status: Strong inference
Directness: Indirect
As of: 2026-08-11
Notes: Legal status never implies control effectiveness.
Claim (Mechanism): CIEDDE-SIADE integrated election-disinformation alert and coordination system targets Provide an anonymous public reporting channel; triage false, misleading or decontextualised election-integrity content; send platform-policy cases to designated platform channels and possible crimes or administrative offences to competent authorities; coordinate TSE, prosecutors, justice, police, telecom regulators and private services. at Cross-platform incident → dispersed citizen and institutional signals → delayed action → trust or turnout harm → agency transfer; a common hub consolidates evidence and routes response.; expected agency domain: Epistemic; Relational; Collective / institutional.
Endpoint: Mechanism / agency
Evidence origin: Normative proposal
Epistemic status: Plausible hypothesis
Directness: Conditional
As of: 2026-08-11
Notes: Mechanism claim is distinct from evidence that the control works.
Claim (Control effectiveness): Indirect / mixed. Expected effect if the control works: Creates a real-time bridge between public detection, authoritative verification, platform action and judicial or criminal escalation.
Endpoint: Control effectiveness
Evidence origin: Normative proposal
Epistemic status: Strong inference
Directness: Indirect
As of: 2026-08-11
Notes: Do not upgrade this claim from Strong inference because a legal duty or risk mechanism exists.
Claim (Legal status / scope): As of 2026-08-11, Ban on telemarketing and non-consensual mass messaging for electoral propaganda is coded Binding / Applicable. Scope: In force for 2026
Endpoint: Legal existence
Evidence origin: Legal / operational precedent
Epistemic status: Established evidence
Directness: Direct
As of: 2026-08-11
Notes: Legal status never implies control effectiveness.
Claim (Mechanism): Ban on telemarketing and non-consensual mass messaging for electoral propaganda targets Prohibit electoral telemarketing at any time and coordinated mass sending of instant messages without recipient consent or through tools and services that violate the messaging provider's terms; prohibit sale of phone-number lists for mass sends. at Campaign or contractor → purchased contact lists and automation → private trusted channel → repeated personalised pressure → agency transfer to sender → hidden mass influence.; expected agency domain: Executive; Relational.
Endpoint: Mechanism / agency
Evidence origin: Legal / operational precedent
Epistemic status: Established evidence
Directness: Conditional
As of: 2026-08-11
Notes: Mechanism claim is distinct from evidence that the control works.
Claim (Control effectiveness): None — legal existence only. Expected effect if the control works: Targets the mass-personalisation and consent asymmetry that made WhatsApp a powerful hidden influence vector.
Endpoint: Control effectiveness
Evidence origin: Legal / operational precedent
Epistemic status: Open question
Directness: None
As of: 2026-08-11
Notes: Do not upgrade this claim from Open question because a legal duty or risk mechanism exists.
Claim (Legal status / scope): As of 2026-08-11, Electoral data-protection duties for profiling and microtargeting is coded Binding / Applicable. Scope: Binding and applicable to 2026 campaigns
Endpoint: Legal existence
Evidence origin: Legal / operational precedent
Epistemic status: Established evidence
Directness: Direct
As of: 2026-08-11
Notes: Legal status never implies control effectiveness.
Claim (Mechanism): Electoral data-protection duties for profiling and microtargeting targets Require legal basis, purpose limitation, access and rights information, records of processing, security and incident reporting; make profiling for electoral microtargeting transparent; require specific, express and prominent consent for sensitive data and public high-risk impact reports when requested. at Campaign, broker or community data holder → intimate or sensitive voter profile → tailored content or contact → vulnerability exploitation → agency transfer to campaign → concentrated informational power.; expected agency domain: Epistemic; Evaluative; Decisional; Executive; Collective / institutional.
Endpoint: Mechanism / agency
Evidence origin: Legal / operational precedent
Epistemic status: Established evidence
Directness: Conditional
As of: 2026-08-11
Notes: Mechanism claim is distinct from evidence that the control works.
Claim (Control effectiveness): None — legal existence only. Expected effect if the control works: Constrains Cambridge Analytica-style collection, community-data transfer and vulnerability microtargeting, while creating records for later investigation.
Endpoint: Control effectiveness
Evidence origin: Legal / operational precedent
Epistemic status: Open question
Directness: None
As of: 2026-08-11
Notes: Do not upgrade this claim from Open question because a legal duty or risk mechanism exists.
Claim (Legal status / scope): As of 2026-08-11, Prohibit materially harmful AI manipulation and exploitation is coded Binding / Applicable. Scope: Existing law; Article 5 prohibitions apply since 2 February 2025
Endpoint: Legal existence
Evidence origin: Legal / operational precedent
Epistemic status: Strong inference
Directness: Indirect
As of: 2026-08-11
Notes: Legal status never implies control effectiveness.
Claim (Mechanism): Prohibit materially harmful AI manipulation and exploitation targets Ban AI systems using subliminal, purposefully manipulative or deceptive techniques, or exploiting specified vulnerabilities, where behavior is materially distorted and significant harm results or is likely. at Adaptive AI → provider or deployer → covert manipulation → person or group → impaired informed choice → agency transferred to deployer → concentrated influence → autonomy and democratic harm.; expected agency domain: Evaluative; Decisional; Executive; Collective / institutional.
Endpoint: Human immediate outcome
Evidence origin: Legal / operational precedent
Epistemic status: Established evidence
Directness: Conditional
As of: 2026-08-11
Notes: Mechanism claim is distinct from evidence that the control works.
Claim (Control effectiveness): None — legal existence only. Expected effect if the control works: Creates a hard boundary for the clearest forms of manipulative AI.
Endpoint: Control effectiveness
Evidence origin: Legal / operational precedent
Epistemic status: Open question
Directness: None
As of: 2026-08-11
Notes: Do not upgrade this claim from Open question because a legal duty or risk mechanism exists.
Claim (Legal status / scope): As of 2026-08-11, Require a non-profiling recommender option is coded Binding / Applicable. Scope: Existing law in application
Endpoint: Legal existence
Evidence origin: Legal / operational precedent
Epistemic status: Established evidence
Directness: Direct
As of: 2026-08-11
Notes: Legal status never implies control effectiveness.
Claim (Mechanism): Require a non-profiling recommender option targets Require VLOPs and VLOSEs to offer at least one recommender option not based on GDPR profiling. at Profiling capability → platform → personalized ranking → citizen → altered attention and salience → agenda-setting agency transfers to platform → epistemic power concentrates → pluralism declines.; expected agency domain: Epistemic; Attentional.
Endpoint: Mechanism / agency
Evidence origin: Legal / operational precedent
Epistemic status: Established evidence
Directness: Conditional
As of: 2026-08-11
Notes: Mechanism claim is distinct from evidence that the control works.
Claim (Control effectiveness): None — legal existence only. Expected effect if the control works: Creates a route out of personalized attention steering.
Endpoint: Control effectiveness
Evidence origin: Legal / operational precedent
Epistemic status: Open question
Directness: None
As of: 2026-08-11
Notes: Do not upgrade this claim from Open question because a legal duty or risk mechanism exists.
Claim (Legal status / scope): As of 2026-08-11, Apply purpose limitation, minimization, access, correction, erasure and DPIAs to assistant memory is coded Binding / Applicable. Scope: Existing law
Endpoint: Legal existence
Evidence origin: Legal / operational precedent
Epistemic status: Strong inference
Directness: Indirect
As of: 2026-08-11
Notes: Legal status never implies control effectiveness.
Claim (Mechanism): Apply purpose limitation, minimization, access, correction, erasure and DPIAs to assistant memory targets Treat stored conversations, profiles, inferred preferences and memory as accountable personal-data processing. at Persistent memory → assistant provider → intimate profiling → user → prediction and preference shaping → informational agency shifts to provider → asymmetric knowledge concentrates → manipulation and dependency risks rise.; expected agency domain: Epistemic; Evaluative; Executive; Relational.
Endpoint: Human immediate outcome
Evidence origin: Legal / operational precedent
Epistemic status: Established evidence
Directness: Conditional
As of: 2026-08-11
Notes: Mechanism claim is distinct from evidence that the control works.
Claim (Control effectiveness): In offline experiments on MovieLens and Google Location data, performance-based minimisation reduced the per-user ratings available to recommender systems while producing algorithm-, metric-, and user-dependent quality losses.
Endpoint: Offline recommender-system RMSE and NDCG under reduced per-user rating histories.
Evidence origin: External empirical
Epistemic status: Established evidence
Directness: Direct
As of: 2026-08-13
Notes: Supports bounded technical feasibility of data minimisation in two recommender datasets; does not test assistant memory, deletion completeness, intimate manipulation, dependency, or real-user outcomes.
Claim (Legal status / scope): As of 2026-08-11, Apply limited GDPR portability and automated-decision rights; prototype functional assistant exit is coded Binding / Applicable. Scope: Existing law
Endpoint: Legal existence
Evidence origin: Legal / operational precedent
Epistemic status: Strong inference
Directness: Indirect
As of: 2026-08-11
Notes: Legal status never implies control effectiveness.
Claim (Mechanism): Apply limited GDPR portability and automated-decision rights; prototype functional assistant exit targets Allow users to receive personal data they provided in portable form and challenge qualifying solely automated decisions with legal or similarly significant effects; separately test portability of derived assistant state. at Agent integration → provider → accumulated context and automated judgment → user → switching cost or consequential outcome → dependency transfers agency to provider → lock-in concentrates power → accountability falls.; expected agency domain: Decisional; Executive; Relational.
Endpoint: Human immediate outcome
Evidence origin: Legal / operational precedent
Epistemic status: Established evidence
Directness: Conditional
As of: 2026-08-11
Notes: Mechanism claim is distinct from evidence that the control works.
Claim (Control effectiveness): In a 2019 exercise of GDPR Article 20 across four consumer IoT systems, researchers received relevant personal data in three of four exercises; none enabled import into a second provider or direct provider-to-provider transmission.
Endpoint: Successful receipt of relevant personal data, import into a second provider, and direct transmission across four Article 20 portability exercises.
Evidence origin: External empirical
Epistemic status: Established evidence
Directness: Direct
As of: 2026-08-13
Notes: In the fourth exercise Amazon returned data associated with another account. This negative implementation evidence from a four-system snapshot does not test assistant-state portability, switching time, useful context transferred, redress, lock-in, or agency outcomes.
Claim (Legal status / scope): As of 2026-08-11, Mandate operating-system interoperability for rival AI assistants is coded Binding / Applicable. Scope: Binding Commission decision adopted 16 July 2026
Endpoint: Legal existence
Evidence origin: Legal / operational precedent
Epistemic status: Strong inference
Directness: Indirect
As of: 2026-08-11
Notes: Legal status never implies control effectiveness.
Claim (Mechanism): Mandate operating-system interoperability for rival AI assistants targets Give competing AI services access to Android features on equivalent terms to the gatekeeper's own AI. at OS control → gatekeeper → privileged invocation, context and device functions → users → default dependence → agency and distribution shift to gatekeeper → assistant market concentrates → choice and pluralism weaken.; expected agency domain: Decisional; Relational.
Endpoint: Mechanism / agency
Evidence origin: Legal / operational precedent
Epistemic status: Established evidence
Directness: Conditional
As of: 2026-08-11
Notes: Mechanism claim is distinct from evidence that the control works.
Claim (Control effectiveness): None — legal existence only. Expected effect if the control works: Directly lowers technical foreclosure of rival assistants.
Endpoint: Control effectiveness
Evidence origin: Legal / operational precedent
Epistemic status: Open question
Directness: None
As of: 2026-08-11
Notes: Do not upgrade this claim from Open question because a legal duty or risk mechanism exists.
Claim (Legal status / scope): As of 2026-08-11, Remove cloud switching barriers and require interoperability is coded Binding / Applicable. Scope: Existing law in application
Endpoint: Legal existence
Evidence origin: Legal / operational precedent
Epistemic status: Strong inference
Directness: Indirect
As of: 2026-08-11
Notes: Legal status never implies control effectiveness.
Claim (Mechanism): Remove cloud switching barriers and require interoperability targets Impose contractual and technical duties supporting switching between data-processing services and progressively removing switching charges. at Cloud dependence → infrastructure provider → proprietary services and egress barriers → firm or government → inability to exit → institutional agency shifts to vendor → infrastructure power concentrates → resilience declines.; expected agency domain: Relational; Collective / institutional.
Endpoint: Mechanism / agency
Evidence origin: Legal / operational precedent
Epistemic status: Established evidence
Directness: Conditional
As of: 2026-08-11
Notes: Mechanism claim is distinct from evidence that the control works.
Claim (Control effectiveness): None — legal existence only. Expected effect if the control works: Reduces a major source of vendor lock-in underneath AI systems.
Endpoint: Control effectiveness
Evidence origin: Legal / operational precedent
Epistemic status: Open question
Directness: None
As of: 2026-08-11
Notes: Do not upgrade this claim from Open question because a legal duty or risk mechanism exists.
Claim (Legal status / scope): As of 2026-08-11, Require fundamental-rights impact assessment before specified public or public-service AI deployment is coded Binding — phased / Enacted / not yet applicable. Scope: Binding duty enacted; general Annex III applicability scheduled for 2027-12-02 under the amended timetable
Endpoint: Legal existence
Evidence origin: Legal / operational precedent
Epistemic status: Strong inference
Directness: Indirect
As of: 2026-08-11
Notes: Legal status never implies control effectiveness.
Claim (Mechanism): Require fundamental-rights impact assessment before specified public or public-service AI deployment targets Require affected groups, risks, oversight and mitigation to be assessed before deploying covered high-risk AI. at High-risk AI → public authority or service provider → automated assessment → citizen → changed entitlement, opportunity or treatment → administrative agency shifts to system and vendor → institutional control concentrates → rights and legitimacy suffer.; expected agency domain: Collective / institutional.
Endpoint: Mechanism / agency
Evidence origin: Legal / operational precedent
Epistemic status: Established evidence
Directness: Conditional
As of: 2026-08-11
Notes: Mechanism claim is distinct from evidence that the control works.
Claim (Control effectiveness): None — legal existence only. Expected effect if the control works: Creates a formal gate before consequential institutional deployment.
Endpoint: Control effectiveness
Evidence origin: Legal / operational precedent
Epistemic status: Open question
Directness: None
As of: 2026-08-11
Notes: Do not upgrade this claim from Open question because a legal duty or risk mechanism exists.
Claim (Legal status / scope): As of 2026-08-11, Provide complaints, investigation and remedial routes under the AI Act is coded Binding / Applicable. Scope: Existing law; EU complaint tool launched in 2026
Endpoint: Legal existence
Evidence origin: Legal / operational precedent
Epistemic status: Strong inference
Directness: Indirect
As of: 2026-08-11
Notes: Legal status never implies control effectiveness.
Claim (Mechanism): Provide complaints, investigation and remedial routes under the AI Act targets Allow natural and legal persons to complain and empower authorities to inspect documentation, data and source code and order corrective measures. at Opaque AI harm → provider or deployer → inaccessible decision process → affected person → inability to challenge → agency remains with controller → unaccountable power consolidates → rule-of-law harm.; expected agency domain: Epistemic; Decisional.
Endpoint: Mechanism / agency
Evidence origin: Legal / operational precedent
Epistemic status: Established evidence
Directness: Conditional
As of: 2026-08-11
Notes: Mechanism claim is distinct from evidence that the control works.
Claim (Control effectiveness): None — legal existence only. Expected effect if the control works: Creates a route from observed harm to public enforcement.
Endpoint: Control effectiveness
Evidence origin: Legal / operational precedent
Epistemic status: Open question
Directness: None
As of: 2026-08-11
Notes: Do not upgrade this claim from Open question because a legal duty or risk mechanism exists.
Claim (Legal status / scope): As of 2026-08-11, Mandate independent annual audits of very large platforms is coded Binding / Applicable. Scope: Existing law in application
Endpoint: Legal existence
Evidence origin: Legal / operational precedent
Epistemic status: Established evidence
Directness: Direct
As of: 2026-08-11
Notes: Legal status never implies control effectiveness.
Claim (Mechanism): Mandate independent annual audits of very large platforms targets Require independent audits of DSA obligations, including systemic-risk assessment and mitigation. at Platform-scale algorithms → platform → ranking and moderation → population → systemic exposure changes → public agenda agency shifts to platform → power concentrates → democratic risk grows; audit introduces external scrutiny.; expected agency domain: Attentional; Relational; Collective / institutional.
Endpoint: Mechanism / agency
Evidence origin: Legal / operational precedent
Epistemic status: Established evidence
Directness: Conditional
As of: 2026-08-11
Notes: Mechanism claim is distinct from evidence that the control works.
Claim (Control effectiveness): None — legal existence only. Expected effect if the control works: Institutionalizes recurring external review of platform risk controls.
Endpoint: Control effectiveness
Evidence origin: Legal / operational precedent
Epistemic status: Open question
Directness: None
As of: 2026-08-11
Notes: Do not upgrade this claim from Open question because a legal duty or risk mechanism exists.
Claim (Legal status / scope): As of 2026-08-11, Protect and operationalize insider reporting on platform algorithmic practices is coded Voluntary / private / Operational voluntary. Scope: Operational enforcement channel
Endpoint: Legal existence
Evidence origin: Legal / operational precedent
Epistemic status: Strong inference
Directness: Indirect
As of: 2026-08-11
Notes: Legal status never implies control effectiveness.
Claim (Mechanism): Protect and operationalize insider reporting on platform algorithmic practices targets Provide an anonymous channel for insiders to report possible DSA violations involving recommender systems, advertising, risk assessment, civic discourse and children. at Internal knowledge → platform → secrecy → regulator and public → hidden manipulation persists → agency remains with platform → control concentrates → systemic harm remains uncorrected.; expected agency domain: Epistemic; Evaluative; Collective / institutional.
Endpoint: Mechanism / agency
Evidence origin: Normative proposal
Epistemic status: Plausible hypothesis
Directness: Conditional
As of: 2026-08-11
Notes: Mechanism claim is distinct from evidence that the control works.
Claim (Control effectiveness): Indirect / mixed. Expected effect if the control works: Surfaces conduct that external audits may not detect.
Endpoint: Control effectiveness
Evidence origin: Normative proposal
Epistemic status: Strong inference
Directness: Indirect
As of: 2026-08-11
Notes: Do not upgrade this claim from Strong inference because a legal duty or risk mechanism exists.
Claim (Legal status / scope): As of 2026-08-11, Evaluate, mitigate and report systemic risks from frontier general-purpose AI is coded Binding — limited scope / Applicable. Scope: Binding GPAI systemic-risk duties; GPAI Code remains a voluntary compliance route.
Endpoint: Legal existence
Evidence origin: Legal / operational precedent
Epistemic status: Established evidence
Directness: Direct
As of: 2026-08-11
Notes: Legal status never implies control effectiveness.
Claim (Mechanism): Evaluate, mitigate and report systemic risks from frontier general-purpose AI targets Require providers of GPAI models with systemic risk to assess and mitigate risk, conduct model evaluations, report serious incidents and maintain cybersecurity. at Frontier capability → model provider → downstream general-purpose deployment → large populations and institutions → scalable harmful behavior → agency shifts toward model ecosystem → capability control concentrates → systemic democratic harm becomes possible.; expected agency domain: Executive; Collective / institutional.
Endpoint: Mechanism / agency
Evidence origin: Legal / operational precedent
Epistemic status: Established evidence
Directness: Conditional
As of: 2026-08-11
Notes: Mechanism claim is distinct from evidence that the control works.
Claim (Control effectiveness): None — legal existence only. Expected effect if the control works: Creates capability-sensitive obligations for the most advanced models.
Endpoint: Control effectiveness
Evidence origin: Legal / operational precedent
Epistemic status: Open question
Directness: None
As of: 2026-08-11
Notes: Do not upgrade this claim from Open question because a legal duty or risk mechanism exists.
Claim (Legal status / scope): As of 2026-08-11, Protect autonomy, democratic processes and free opinion formation throughout the AI lifecycle is coded Binding — phased / Enacted / not yet applicable. Scope: CETS 225 adopted and EU-ratified but not yet in force as of 2026-08-11.
Endpoint: Legal existence
Evidence origin: Legal / operational precedent
Epistemic status: Established evidence
Directness: Direct
As of: 2026-08-11
Notes: Legal status never implies control effectiveness.
Claim (Mechanism): Protect autonomy, democratic processes and free opinion formation throughout the AI lifecycle targets Require parties to protect dignity, autonomy, democratic processes, transparency, accountability, remedies and lifecycle risk management. at AI system → state or private actor → influence or institutional automation → citizen or institution → impaired opinion formation or participation → agency transfers to controller → power concentrates → self-government is weakened.; expected agency domain: Collective / institutional.
Endpoint: Mechanism / agency
Evidence origin: Legal / operational precedent
Epistemic status: Established evidence
Directness: Conditional
As of: 2026-08-11
Notes: Mechanism claim is distinct from evidence that the control works.
Claim (Control effectiveness): None — legal existence only. Expected effect if the control works: Provides the clearest binding bridge between AI, autonomy, democracy and rule of law.
Endpoint: Control effectiveness
Evidence origin: Legal / operational precedent
Epistemic status: Open question
Directness: None
As of: 2026-08-11
Notes: Do not upgrade this claim from Open question because a legal duty or risk mechanism exists.
Claim (Legal status / scope): As of 2026-08-11, Protect media pluralism and regulated media visibility on dominant platforms is coded Binding / Applicable. Scope: Existing law; most provisions apply since 8 August 2025
Endpoint: Legal existence
Evidence origin: Legal / operational precedent
Epistemic status: Strong inference
Directness: Indirect
As of: 2026-08-11
Notes: Legal status never implies control effectiveness.
Claim (Mechanism): Protect media pluralism and regulated media visibility on dominant platforms targets Create safeguards for recognized media providers against arbitrary platform restrictions and require media-market concentration assessment. at Platform or media concentration → controller → ranking, removal or acquisition → public → narrowed information environment → epistemic agency shifts to concentrated intermediaries → agenda power consolidates → pluralism and legitimacy decline.; expected agency domain: Epistemic; Attentional; Collective / institutional.
Endpoint: Mechanism / agency
Evidence origin: Legal / operational precedent
Epistemic status: Established evidence
Directness: Conditional
As of: 2026-08-11
Notes: Mechanism claim is distinct from evidence that the control works.
Claim (Control effectiveness): None — legal existence only. Expected effect if the control works: Recognizes concentration and platform intermediation as democratic, not merely economic, concerns.
Endpoint: Control effectiveness
Evidence origin: Legal / operational precedent
Epistemic status: Open question
Directness: None
As of: 2026-08-11
Notes: Do not upgrade this claim from Open question because a legal duty or risk mechanism exists.
Claim (Legal status / scope): As of 2026-08-13, publication of an Algorithmic Transparency Recording Standard record is mandatory as an administrative policy for in-scope United Kingdom central-government organisations using Beta/Pilot or Production algorithmic tools that meet the public-effect or direct-public-interaction criteria; it is recommended rather than mandatory outside that scope, and exemptions apply.
Endpoint: Legal existence
Evidence origin: Legal / operational precedent
Epistemic status: Established evidence
Directness: Direct
As of: 2026-08-13
Notes: The mandate is an administrative policy, not a general statute; scope and exemptions must be assessed for each organisation and tool.
Claim (Mechanism): Publish a mandatory public-sector algorithm and AI register targets Require departments to disclose where, why and how algorithmic tools affect public decisions, with risks, data, responsibility and contacts. at Administrative AI → public body and vendor → hidden decision support → citizen → invisible influence on public treatment → agency shifts from accountable officials → vendor-administration nexus concentrates → legitimacy falls.; expected agency domain: Decisional; Executive; Collective / institutional.
Endpoint: Mechanism / agency
Evidence origin: Legal / operational precedent
Epistemic status: Established evidence
Directness: Conditional
As of: 2026-08-11
Notes: Mechanism claim is distinct from evidence that the control works.
Claim (Control effectiveness): None — legal existence only. Expected effect if the control works: Makes institutional AI dependence visible and assigns responsibility.
Endpoint: Control effectiveness
Evidence origin: Legal / operational precedent
Epistemic status: Open question
Directness: None
As of: 2026-08-11
Notes: Do not upgrade this claim from Open question because a legal duty or risk mechanism exists.
Claim (Legal status / scope): As of 2026-08-11, Mandate algorithmic impact assessment, explanation, peer review and recourse in government is coded Binding / Partial / verify. Scope: Operational government directive
Endpoint: Legal existence
Evidence origin: Legal / operational precedent
Epistemic status: Strong inference
Directness: Indirect
As of: 2026-08-11
Notes: Legal status never implies control effectiveness.