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 →

Hilary Mason 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.

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1exchanges match
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Answered raw tape D 5 · C 5 · P 4 · Cm 4 4.60

Q Yes, yes, yes, it's a little bit of a hint. So, uh, thanks very much for, especially for sharing all the things that, um, you guys are working on and are excited about. Is there anything that you guys looked at and felt, okay, this is just not ready for prime time? It sounds like it is ready for prime time, but it's really not.

A Um, so I have a few strong opinions on that that my colleagues may not agree with, so I'll preface it by that. I think there are a couple of things that everyone thinks are solved problems that are absolutely not, and so something like sentiment analysis is something where we sort of take for granted that you can just plug into an API and get a number back, but this is also a problem where if we took everyone in this room and had them rate the sentiment of a document, we would not agree. So the ground truth is lacking, and so the tools are in many cases lacking. Now, some of the newer approaches may make that an interesting problem, and we may finally be able to get to a reasonable solution, um, but that's one where, where I think the common wisdom is sort of missing the point.

AI assessment note: “something like sentiment analysis is something where we sort of take for granted”

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