153 karma · joined July 31, 2016
That's irrelevant to the claim being made. It's not education or knowledge that's inaccessible to lower classes, it's the stuff around it. It's nearly impossible to judge just knowledge and skills without any context, and even if you could manage it, it would be an unwise move leading to chaotic work environments. But it's also nearly impossible to judge "would this person be disruptive?" without also sneaking in strongly-class-biased culture fit screening, even if you explicitly prohibit doing so.
(Also, having the time to learn and knowledge of where to go to start learning are class biased. The founding population of tech was a different social community from previous power but still heavily upper-middle-class. (I'd guess tech workers 1990-2010 were about 60% from the second quintile and 80% in the 2nd-4th deciles.) They're skills that anyone could learn, but only in theory; in practice they're skills that anyone with the opportunity can learn, and the opportunity is not evenly distributed.)
But yes, it's basically "represent a quantum computer of this size", which we legitimately can't do classically beyond a certain size. It's not hugely useful but it's legitimate quantum supremacy, if it works.
>We don’t want to live like this. In our ideal distribution, the top quintile owns 32% and the bottom two quintiles own 25%. As the journalist Chrystia Freeland put it, “Americans actually live in Russia, although they think they live in Sweden. And they would like to live on a kibbutz.” Norton and Ariely found a surprising level of consensus: everyone — even Republicans and the wealthy—wants a more equal distribution of wealth than the status quo.
You'd think they'd sanity check their poetic description against professed beliefs. If your metric says that most Americans "would like to live on a kibbutz", then your metric is wrong.
What this actually shows is that most Americans have no idea what wealth inequality looks like. Ask the same group of people their predicted and ideal income inequality measurements. I predict you'll get the same numbers, plus a little noise.
A closely related question: is asking in terms of percentages biasing? And the answer is: Very Yes. http://journal.sjdm.org/12/121027/jdm121027.html
>Norton and Ariely (2011) set out to answer a remarkably important set of questions: How much inequality do ordinary Americans believe exists in the U.S.? And how much inequality do they desire? These questions have a range of important policy implications. However, the initial answers to these questions need to be reconsidered. Our findings indicate that the remarkably low estimates of wealth inequality given by Norton and Ariely’s respondents depended on the particular measure (quintile percentages) that was used. When asked to state quintile percentages for either household wealth, teacher salaries, or web page clicks, our respondents seemed to use an anchoring-and-adjustment heuristic leading to very similar responses across very different domains.
>When respondents were relieved of aggregating their intuitions about inequality into quintile percentages, another picture emerged. According to this new picture, Americans do not tend to have extremely biased perceptions of current levels of inequality. Nor do they entertain an ideal of near-perfect egalitarianism. Rather they seem to prefer a world where the poor are not as poor as they are today. Further investigation into this more tractable ideal might provide a basis for workable policy prescriptions.
It's a public good, not a private one, and so should be funded publicly.
Price discrimination is _wonderful_ for the poor. Extract tons of money from the rich who don't give a shit, but still sell the service to poorer people at a price they can afford, with almost all the same benefits.
If we didn't just have the results of scattered tests, but had an exhaustive set of docs written by the creator of the black box, it still wouldn't be easy. But we'd have a chance. This is why one of the main strands of AI value alignment research focuses on building an AI that we can understand. If we can build something we can understand, that gives us leverage to alter it to value our interests.
(What "our interests" are, in a well-specified technical sense, is a whole 'nother problem, and one that there's very little progress on.)
His list (with its diff):
-1. Do you use source control?
+1. Is your source control effective for the disconnected programmer?
2. Can you make a build in one step?
-3. Do you make daily builds?
+3. Do you build, test, and deploy (somewhere) on every commit?
4. Do you have a bug database?
5. Do you fix bugs before writing new code?
-6. Do you have an up-to-date schedule?
+6. Does your source have a stable trunk from which releases can be cut at any time?
-7. Do you have a spec?
+7. Can all of a product's features be verified in one step?
-8. Do programmers have quiet working conditions?
+8. Do programmers have access to a door that can be closed for uninterrupted work?
-9. Do you use the best tools money can buy?
+9. Do programmers have the freedom to choose the best tools for the job?
-10. Do you have testers?
+10. Is testing the team's responsibility?
11. Do new candidates write code during their interview?
12. Do you do hallway usability testing?As examples: Esperanto tries very hard to be precise, but there are playful neologisms, like "gedormi", which conjugates "dormi", "to sleep", in the mixed-gender plural, to form "to sleep with (heterosexually)", with the same innuendo as in English.
In Lojban, there is an abundance of poetry in which pieces of the phrases are intentionally and visibly omitted, which allows for flexible interpretation of created ambiguity.
I know personally I identified as a left-libertarian and then realized that classical liberal was a more legible way to express the same positions.
When in doubt, portmanteau the idiom.