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 →

Julia Kirby 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 4 · C 5 · P 4 · Cm 4 4.30

Q we've talked about this a lot on the podcast, especially lately, because we just came out of a DC series where people are, the theme that came up on every single podcast was the realities of the job market, is how people, especially in the US, can adapt to this world. And even before that, what are the realities of the job market as software and automation eats the world?

A The big fear, I guess, right now, and it's justified, is that, um, a whole, uh, kind of set of us who thought that Our jobs, our livelihoods were kind of immune to this encroachment of automation are now having to, to rethink that confidence, you know, so we've invested a lot of time and money in gaining those college degrees and advanced degrees so that we can do, you know, this sophisticated knowledge work. We thought that that meant, you know, we're not going to be like those assembly line workers or Even frontline service workers in, you know, um, fast food settings who might be seeing their, their, uh, jobs gobbled up by automation and even by computers. But with the advent of cognitive technologies, we're now seeing, um, machines capable of doing decision making. So you could see this as sort of three waves of automation that first machines came along and they automated the dangerous work. And then computers came along and they started to automate some of that Dull work like transcriptions, et cetera. Now we're at the point where they're taking over decision-making. And the scary part is that, um, it's hard to see what is the higher ground that you can move to as a human and still be able to add value in a workplace.

AI assessment note: “Now we're at the point where they're taking over decision-making.”

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