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.

2,364 searchable experts 2,966 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.

What is moving across the network now

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

Developing Responsible AI Development 1d ago
⚡ 174 h early

AI is more likely than humans to form biases when hiring

2 directory members surfaced this signal.

2 experts 1 community 1 sources clustered
How the network is reacting 2 experts are emphasizing concern & critique.
Shared emphasis

Concern & critique

2 experts

Risks, limits and unintended consequences.

“New research suggests that LLMs can develop their own biases from experience, separate from their training data. This can lead them to stereotype job applicants even more than humans do. www.technologyreview.com/2026/07/20/1...”

Established AI field signal Development 5d ago
⚡ 7 h early
Google spiralling AI costs

Google burning through cash with spiralling AI costs

2 directory members surfaced this signal.

2 experts 2 communities 1 sources clustered

“www.bbc.com/news/article... Google in the poorhouse! "The company's free cash flow, the cash it maintained after paying for operations and investments, came in at negative $5.9bn (£4.3bn) for the first time in at least a decade, according to its past financ…”