apol/agency-transfer-policy-atlas huggingface dataset:
Case: Romania presidential election, 2024
Type: Observed incident
Timing: Pre-election and immediate post-election
Mechanisms: Coordinated promotion, recommender amplification, opaque sponsorship, cross-platform operation
Observed or prospective harm: Information-integrity crisis, institutional response, annulment controversy, and legitimacy damage
Missing or failed controls: Sponsor transparency, earlier network detection, auditable recommender risk, evidence preservation
Evidence status: Established platform and institutional evidence; causal vote effect unproven
Priority lesson: Do not infer result causality from virality; map controller, distribution, evidence, and institutional consequences.
Sources: Venice Commission and EU/OSCE materials; see Evidence Ledger
Case: Moldova elections / referendum, 2024–2025
Type: Observed incident
Timing: Persistent through election cycle
Mechanisms: Coordinated networks, paid influence, cross-platform and offline channels, institutional pressure
Observed or prospective harm: High response burden, trust erosion, and vulnerability to opaque external control
Missing or failed controls: Cross-platform coordination, financial attribution, rapid evidence and public communication
Evidence status: Documented foreign-influence and illicit-finance risk; AI-specific contribution varies
Priority lesson: AI is an enabling layer inside a broader influence system, not a standalone cause.
Sources: OSCE/ODIHR and official election reports; see Evidence Ledger
Case: New Hampshire AI-voice robocall, 2024
Type: Observed incident
Timing: Immediately before primary
Mechanisms: Synthetic impersonation, voter suppression message, telephony distribution, caller-ID deception
Observed or prospective harm: Deceptive voting message and demonstrated low-cost impersonation vector
Missing or failed controls: Voice consent/disclosure enforcement, rapid carrier trace, campaign verification, correction
Evidence status: Established enforcement case
Priority lesson: Channel-specific law and attribution can be more consequential than generic deepfake labeling.
Sources: https://www.fcc.gov/document/fcc-makes-ai-generated-voices-robocalls-illegal
Case: Slovakia parliamentary election audio incident, 2023
Type: Observed incident
Timing: Final campaign days
Mechanisms: Late-cycle synthetic audio, authenticity uncertainty, compressed correction window
Observed or prospective harm: Epistemic uncertainty and response difficulty close to voting
Missing or failed controls: Fast authentication, candidate verification, trusted channels, proportional correction
Evidence status: Synthetic-audio incident widely documented; effect on outcome unproven
Priority lesson: The democratic harm can be uncertainty and institutional overload even without measurable persuasion.
Sources: Case sources maintained in Part 3 and Evidence Ledger
Case: Brazil general election, 2026 — TSE implementation regime
Type: Prospective implementation study
Timing: Plans by 2026-08-16; first round 2026-10-04; possible second round 2026-10-25; consolidated reports by 2026-12-19
Mechanisms: AI assistants, synthetic media, recommender systems, boosted political content, rapid incident response
Observed or prospective harm: Prospective risk; no 2026 voting outcome yet
Missing or failed controls: Independent baseline, plan-quality audit, exposure data, assistant-neutrality tests, appeal testing and post-election causal design
Evidence status: Binding Resolution and Portaria adopted; plans due 2026-08-16; election and causal effects not yet observable as of 2026-08-11
Priority lesson: Treat as a prospective implementation study. Plan completion is not effectiveness, and virality is not evidence of changed votes.
Sources: https://www.tse.jus.br/legislacao/compilada/prt/2026/portaria-no-463-de-27-de-julho-de-2026
Case: Cambridge Analytica / political microtargeting baseline
Type: Historical governance baseline
Timing: Long-term baseline
Mechanisms: Data extraction, profiling, targeted messaging, opaque controller networks
Observed or prospective harm: Loss of informational autonomy, accountability failure, and trust damage
Missing or failed controls: Data minimization, sponsor/targeting transparency, researcher access, functional exit
Evidence status: Established data-governance and campaign-infrastructure case; individual persuasion effects contested
Priority lesson: The strongest evidence concerns data and governance failure, not deterministic mind control.
Sources: Regulatory and parliamentary records; see Evidence Ledger
Case: AI assistants answering election-administration questions
Type: Audit domain
Timing: Continuous, intensified near deadlines
Mechanisms: Answer-layer gatekeeping, retrieval failure, hallucinated authority, default trust
Observed or prospective harm: Potential misregistration, misdirection, or reduced participation
Missing or failed controls: Official-source interfaces, multilingual audits, update SLAs, visible correction
Evidence status: Recurring audit domain; error rates vary by model, language, and date
Priority lesson: Administrative accuracy is measurable and should be separated from contested political truth claims.
Sources: Election-authority and civil-society audit materials; see Evidence Ledger
Case: Legitimate synthetic media in election communication
Type: Legitimate-use counterexample
Timing: Campaign period
Mechanisms: Translation, accessibility, parody, low-cost outreach, candidate-authorized synthetic speech
Observed or prospective harm: No inherent harm; risk arises from deception, attribution failure, or discriminatory enforcement
Missing or failed controls: Clear authorization and provenance; contextual exceptions; appeal
Evidence status: Established legitimate-use category
Priority lesson: A blanket synthetic-media ban would sacrifice speech and access without addressing interactive manipulation.
Sources: International IDEA and election-regulator guidance; see Evidence Ledger
Case: Public authority dependence on proprietary AI vendors
Type: Structural risk pattern
Timing: Procurement and annual resilience review
Mechanisms: Vendor lock-in, deskilling, opaque updates, cloud-model integration, weak exit
Observed or prospective harm: Reduced institutional autonomy, continuity, contestability, and public accountability
Missing or failed controls: Public registers, multi-provider architecture, tested exit, internal expertise, contractual audit
Evidence status: Structural risk with operational precedents; democratic effects under-measured
Priority lesson: Agency transfer can occur inside institutions even without manipulative content.
Sources: Canada, UK, EU procurement, and OECD materials; see Evidence Ledger