The Exchanges

Every argument clarity score on this site is built from rows on this page. Each question and answer was assessed with names hidden, the host's own answers included, on four things from 1 to 5: directness (does it answer the question asked), coherence (do the ideas follow), precision (concrete details and clear references), compression (says a lot per word). The weighted mix (30/30/25/15) is the exchange score. A person's published score averages their exchange scores on raw tape only, at least 8 of them, shrunk toward the cohort mean. Full method →

Ricky Van Veen no published score: only 1 usable exchange on raw tape, and a fair score needs 8+ record → ← everyone

Every exchange below was scored with names hidden, four dimensions each from 1 to 5. An exchange's score is 0.30·directness + 0.30·coherence + 0.25·precision + 0.15·compression. The published score averages the raw tape exchange scores and shrinks small samples toward the cohort mean, so five great answers can't beat twenty good ones. Produced feed rows count only toward coarse estimates, never toward a full score.

clear all ✕
1exchanges match
1on raw tape
1redirected or not addressed
Redirected raw tape D 3 · C 4 · P 4 · Cm 3 3.55

Q And Ricky, if you were, like, starting College Humor today with AI as it exists, would you do anything differently?

A I'd probably use it as a tool, and it, you know, in the, being in the partnerships org, like, we think about how to empower creators with AI. So, You know, an example, my colleague, the wonderful Eva Chen, who's a big fashion person and a great person, you know, she gets asked the same question 10 times a day, which is like, which Apple watch band do you have? Right? Because everyone sees it and they, and they want to know. And like, she doesn't have time to respond to everybody and you would leave some fans hanging and not to, they want the question answers not answered, but like with AI, like you can solve that problem. And The viewer can get their question answered. Eva can, uh, gain, uh, uh, maybe another fan or viewer, and it's like, and it's a win-win, you know, and of course the viewer knows that it's an AI that's responding because Eva is, you know, so those type of things that we look at and think, like, what are the pain points for creators now, and how does AI solve those rather than some, like, wholesale reimagining of the entire ecosystem, that sort of thing.

AI assessment note: “being in the partnerships org, like, we think about how to empower creators”

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