Arvind Narayanan
Professor of Computer Science, Princeton University · 1 appearance on the record.
computed by AI from the episodes · how this works → · full disclaimer →
academicscientistauthor@random_walker ↗cs.princeton.edu/~arvindn ↗Wikipedia ↗
Arvind Narayanan is a professor of computer science and director of the Center for Information Technology Policy at Princeton University. He is known for research in data privacy and de-anonymization and has co-authored books including AI Snake Oil.
4 supported 0 partly supported 0 contradicted 2 not yet assessed 14 not checkable as stated how the 20 claims stand · each chip opens the sources
11 predictions · 9 assertions · 9 opinions · 6 insights · 1 disclosure · every statement was checked. The predictions and assertions are the 20 claims: statements the public record can support or contradict. 4 are resolved, 2 are not yet assessed, and 14 name no date, number or outcome precise enough to check. Everything else (opinions, insights, what ifs, disclosures) can never be settled by the record, so it carries no assessment.
The record, in short
What the tape says about how Arvind argues and how the claims held up. Everything they said, and everything said about them, is in the tabs below.
Their most notable supported claim
Expressed certainty vs assessment result
weighted support: a fully supported claim counts one, a partly supported claim counts half. Each filled bar is clickable and opens exactly those claims; "none yet" means nothing said at that certainty level has resolved yet
Argument clarity: do they answer the question? how? →
redirected or did not address 1 of 39 assessed questions (3%). Watch them ▸
This is a score against a rubric. It is not a rank. Every host question → answer exchange is scored with names hidden on directness, coherence, precision and compression, 1–5 each, on meaning alone: disfluencies are ignored, and only raw unedited episodes count. This is the score that measures thought. Every scored exchange, scores shown → · The rubric and its checks →
How they sound: speaking style how? →
246 words/min while actually speaking · 32.7 um and uh per 1k words · 7.3 false starts per 1k · 32.6% of pauses land inside a clause
Measured by listening to the audio itself: 7,228 words across 1 episode of raw-level tape, transcribed verbatim with every um and uh kept, each one attributed only where the alignment onto our timed stream is unambiguous. These are measurements of speaking style. We do not rank them: across this corpus, fluency and argument quality are nearly uncorrelated (ρ≈0.2), and smooth talking does not signal clear thinking. How it's measured →
How the interview went all their pushback → series average →
Across 1 rated episode:
Everything Arvind Narayanan said on 20VC that made the record, most notable first. Filter by type, assessment or year in the ledger →
The other half of the tape: Arvind Narayanan's own voice is left out of every number here. Other people bring the name up 3 times in 1 episode on 20VC. every mention, with the transcript →
Who brings them up most Harry Stebbings 3
Every mention by year
Appearances (1)
| Episode | Date | Speaking time |
|---|---|---|
| Arvind Narayanan: AI Scaling Myths, The Core Bottlenecks in AI Today & The Future of Model | Aug 28, 2024 | 35m |