723 karma · joined December 18, 2017
[edit: seems I was very clearly wrong about this]
To prevent bribery randomly sample 1% for a retest under much stricter security.
If you must, lower standards for protected classes to even out demographics.
Rich people can afford to burn their children’s childhood on the enrichment activities and “volunteer” work Harvard requires.
Standardized testing is by far the most fair way to do this. SAT prep is not that effective and besides SAT prep is now available online for free.
I don't think I disagree very much with you then.
>People thought the same thing about nuclear energy. A popular quote from the 50s was "energy too cheap to meter." Yet here we are in a world were nuclear energy exists but unforeseen factors like hardware costs cause the costs to be much more than optimists expected.
In worlds where this is true, OpenAI does not matter. So I don't really mind if they make a profit.
Or to put it another way, comparative advantage dulls the claws of capitalism such that it tends to make most people better off. Comparative advantage is much, much more powerful than most people think. But nonetheless, in a world where software can do all economically-relevant tasks, then comparative advantage breaks, at least for human workers and the Luddite fallacy becomes a non-fallacy. At this point, we have to start looking at evolutionary dynamics instead of economic ones. An unaligned AI is likely to win in such a situation. Let's call this scenerio B.
OpenAI has defined the point at which they become redistributive in the low hundreds of billions. In worlds where they are worth less than hundreds of billions (scenerio A, which is broadly what you describe above) they are not threatening so I don't care - they will help the world as most capitalist enterprises tend to, and most likely offer more good than the externalities they impose. And as in scenerio A, they will not have created cheap software that is capable of replacing all human capital, comparative advantage will work its magic.
In worlds where they are worth more, scenerio B, they have defined a plan to become explicitly redistributive and compensate everyone else, who are exposed to the extreme potential risks of AI, with a fair share of the extreme potential upsides. This seems very, very nice of them.
And should the extreme potentials be unrealizable then no problem.
This scheme allows them to leverage scenerio A in order to subsidize safety research for scenerio B. This seems to me like a really good thing, as it will allow them to compete with organizations, such as FaceBook and Baidu, that are run by people who think alignment research is unimportant.
If you have AGI, it is very clear you could very quickly displace the entire economy, especially as inference is much cheaper than training: which implies there will be plenty of hardware available at the time AGI is created.
Hearing the performative compassion of San Francisco‘s politicians and the results: streets covered in human shit, crazed heroin zombies colonizing them, a pathetic protest culture pushing zoning legislation that extracts rents from everyone; one is reminded of this Kipling poem: http://www.kiplingsociety.co.uk/poems_copybook.htm
Another aspect is photography allowed normal people access to create cheap reproductions of beautiful art. High-class people used to be able to distinguish themselves from the mob with beautiful things the mob couldn't afford.
But this does not work with cheap reproductions allowing one to signal the same taste.
In this way, there became an incentive for high-class people to acquire and inculcate a taste for art that is actively repulsive to distinguish themselves from those normal people who desire beautiful things.
Mostly this doesn't matter. They are only hurting themselves. But the effect of these incentives on public architecture has been pretty horrifying.
Once we get data sets with millions of genomes tagged with their donors IQ, this number will rise. If we can predict, say, 60% of the variance in IQ (based on the genome alone) will you change you mind?
That is, what sort of data would change your mind?
Yes.
If you read the citations you will see this is based on twin adoption studies, which control for confounding variables almost perfectly.
I assure you, ever single objection you can think of off the top of your head has been raised and overcome.
The heritability of IQ is not a conclusion psychologists wanted to affirm. It is fact the field was forced to come to from the data, despite the ideological drifts of the last 50 years yearning (or in the case of Stephen Jay Gould outright falsifying data) for the opposite conclusion.
I know it is ideologically uncomfortable but this is a fact you will have to get used to. Cognitive genomics is coming. The undeniable is becoming laughable to deny.
Caltech is such a school. And its population is largely largely Asian and Jewish, both demographics Harvard has a history of discriminating against.
I am sure Caltech’s administration is considered hopelessly reactionary, but their graduates have the highest number of Nobel prizes per capita. But again, what sort of merit does a Nobel prize prove? Look at the demographics of the winners.
Once Honda and Toyota go electric, those things will last a century.