Expert attention map

The Who's Who of AI

What credible people across AI noticed, why it matters, and where the field is converging or disagreeing.

2,397 searchable experts 4,280 tracked across all sources
Filter the conversation Who is saying what?

Combine a professional role with a reaction lens. Both must match the same attributed contribution.

Clear all
New Network reaction maps

See how experts are reacting—not just what they shared.

Posts are grouped by conversation and tone. Select a lens to filter the stream; these are never permanent labels on people.

0 live reaction maps in this view

No development in this filter has enough independent reactions yet. The maps appear as soon as the evidence supports them.

Showing signals surfaced by Tom Hope ×

The developments commanding sustained expert attention

One card per development. Sources are clustered; reaction bundles describe these posts, never the people behind them.

Established AI field signal Signal 3d ago

Can ai help solve peer review crisis here are its promises and pitfalls

3 experts across 2 network communities independently surfaced this.

3 experts 2 communities 1 sources clustered

“🧪 We are staring down a crisis with peer-review. Editors needed 4.5 invitations to secure a single peer reviewer in 2025, double the effort required back in 2018. Meanwhile, we have half of surveyed scientists admit to using AI to draft their reviews. This …”

“Enjoyed being interviewed by @jeffreybrainard.bsky.social @science.org on AI for scientific novelty assessment—a problem that is still unsolved by SOTA LLMs in my experience. Stay tuned for more on this! www.science.org/content/arti...”