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.

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Concern & critique Policy & governance
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Multiple readings Companies Are Using Reddit to Manipulate ChatGPT and Google AI Search Concern & critique · 2 attributable reactions
Showing signals surfaced by Eiko Fried ×
Most important

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 9d ago
⚡ 3670 h early

Companies Are Using Reddit to Manipulate ChatGPT and Google AI Search

11 experts across 4 network communities independently surfaced this.

11 experts 4 communities 1 sources clustered
404 Media Joanna Bryson Joseph Cox Sarah T Roberts, PhD Christopher Mims Jason Koebler Djamé 🟥 Mél Hogan / The Data Fix +3
3 experts discussed this · 6 posts
Joanna Bryson: So we all knew how to “google bomb” back in the 00s (remember liar -> Tony Blair?) by linking one page from several others. Is there a gemini bomb? how do we do it? (Hard to believe it’s “unintenti…
Lilian Edwards: It's "LLM grooming" now I believe and takes state actor level resources
Joanna Bryson: Have you a Url about that, by chance?
Open the full discussion →
Primary source 404media.co ↗
Developing Evaluation & benchmarks Research 1d ago
⚡ 15 h early
semantic embeddings psychological taxonomy paper

Semantic embeddings reveal and address taxonomic incommensurability in psychological measurement - Nature Human Behaviour

2 directory members surfaced this signal.

2 experts 2 communities 1 sources clustered
Eiko Fried Michael Mullarkey

“2025 paper on automated detection of jingle-jangle based on LLM embeddings. Here a proof of principle where they highlight personality scales high in label similarity (similar scale name) but low in item similarity [blue, jingle] and vice versa [beige, jang…”

Primary source nature.com ↗
Developing Evaluation & benchmarks Signal 1d ago
⚡ 31 h early

Semantic embeddings reveal and address taxonomic incommensurability in psychological measurement - Nature Human Behaviour

2 directory members surfaced this signal.

2 experts 2 communities 1 sources clustered
Eiko Fried Michael Mullarkey

“2025 paper on automated detection of jingle-jangle based on LLM embeddings. Here a proof of principle where they highlight personality scales high in label similarity (similar scale name) but low in item similarity [blue, jingle] and vice versa [beige, jang…”

Primary source nature.com ↗
Developing Evaluation & benchmarks Signal 1d ago
⚡ 33 h early

Semantic embeddings reveal and address taxonomic incommensurability in psychological measurement - Nature Human Behaviour

2 directory members surfaced this signal.

2 experts 2 communities 1 sources clustered
Eiko Fried Michael Mullarkey

“2025 paper on automated detection of jingle-jangle based on LLM embeddings. Here a proof of principle where they highlight personality scales high in label similarity (similar scale name) but low in item similarity [blue, jingle] and vice versa [beige, jang…”

Primary source nature.com ↗
Developing Evaluation & benchmarks Signal 1d ago

Semantic embeddings reveal and address taxonomic incommensurability in psychological measurement - Nature Human Behaviour

2 directory members surfaced this signal.

2 experts 2 communities 1 sources clustered
Eiko Fried Michael Mullarkey

“2025 paper on automated detection of jingle-jangle based on LLM embeddings. Here a proof of principle where they highlight personality scales high in label similarity (similar scale name) but low in item similarity [blue, jingle] and vice versa [beige, jang…”

Primary source nature.com ↗
Developing Evaluation & benchmarks Signal 1d ago

Semantic embeddings reveal and address taxonomic incommensurability in psychological measurement - Nature Human Behaviour

2 directory members surfaced this signal.

2 experts 2 communities 1 sources clustered
Eiko Fried Michael Mullarkey

“2025 paper on automated detection of jingle-jangle based on LLM embeddings. Here a proof of principle where they highlight personality scales high in label similarity (similar scale name) but low in item similarity [blue, jingle] and vice versa [beige, jang…”

Primary source nature.com ↗
Developing Evaluation & benchmarks Signal 1d ago

Semantic embeddings reveal and address taxonomic incommensurability in psychological measurement - Nature Human Behaviour

2 directory members surfaced this signal.

2 experts 2 communities 1 sources clustered
Eiko Fried Michael Mullarkey

“2025 paper on automated detection of jingle-jangle based on LLM embeddings. Here a proof of principle where they highlight personality scales high in label similarity (similar scale name) but low in item similarity [blue, jingle] and vice versa [beige, jang…”

Primary source nature.com ↗
Developing Evaluation & benchmarks Signal 1d ago

Semantic embeddings reveal and address taxonomic incommensurability in psychological measurement - Nature Human Behaviour

2 directory members surfaced this signal.

2 experts 2 communities 1 sources clustered
Eiko Fried Michael Mullarkey

“2025 paper on automated detection of jingle-jangle based on LLM embeddings. Here a proof of principle where they highlight personality scales high in label similarity (similar scale name) but low in item similarity [blue, jingle] and vice versa [beige, jang…”

Primary source nature.com ↗