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 →

Scott Belsky no published score: only 2 usable exchanges 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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2exchanges match
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Answered raw tape D 4 · C 5 · P 4 · Cm 4 4.30

Q And then I look at it and I, and I see them just completely dunking on like, um, you know, where I'm spending all, pretty much all my time. So I'm curious, yeah, I'm curious, you know, how would, how do you think about that and what sort of advice do you give to, to people who, who see that and, and don't know how to digest it?

A Well, I mean, it's one of those moments right now in technology where everyone is both right and wrong right now, right? I mean, whoever thinks that this is going to reinvent the world and solve every problem as we know it is probably wrong. And, uh, and those who feel like it's nothing are certainly wrong as well. Uh, I, I always find it fascinating when a technology forces on us a compromise of something that we typically thought was extremely important. Um, a great example happened in my industry, where five to seven years ago, um, when Adobe bought my company Behance, actually back in 2012, the idea of a creative tool for professionals on the web was insane. Like, no one would ever trade performance and precision for ease of access and collaboration. You know, when we went to creatives and asked them, like, would you want a web-based application for image editing or screen design or whatever? It was like laughable. It was like, are you kidding me? I'm not gonna bring my performance down to like whatever my web connection is. Right. And yet there were some teams out there like my friend Dylan and others who recognized that people are willing to trade performance and precision for ease of collaboration. And it was like this insight into this next generation or psychographic of like, I want everything to be with other people. Like I, I grew up in the age of Google docs. And ev…

AI assessment note: “it's one of those moments right now in technology where everyone is both right and wrong”

Answered raw tape D 4 · C 4 · P 4 · Cm 4 4.00

Q I, you know, oh, like, yeah, maybe Greg doesn't get me as well as, you know, an algorithm that has been learning, you know, trained to learn about me for 10 years. But, um, the fact that he actually created this and thought about it, even the fact that I don't like the Rolling Stones and it's literally my most hated band. Like, do you feel like we'll lose that?

A That's a good question. You know, I think that, I think that it will, I think these, I think the list that you're describing that you might make for me will never be as good. Um, now I do think we'll still have spontaneity. You know, I think that Spotify probably knows you and I are connected and, you know, might say, hey, you know, let's algorithmically test Greg's favorite three songs with Scott and see if he, you know, replays them, likes them, or ignores them, or skips them. And, you know, and so I, I feel like I mean, the answer is, of course, yes and yes, right? Like, I mean, we should still, we will still be exposed to music in totally random ways. I guess this is more about our human tendency to always collect favorites and go back to the stuff we know versus surrendering ourselves to, like, the AI algorithms that we don't know because they're just so reliable and they push us to actually open our boundaries, you know, more so than our own go-to's.

AI assessment note: “I mean the answer is, of course, yes and yes, right?”

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