Maybe I’m way off base here, but it seems like average utilitarianism leads to disturbing possibility itself. That being 1 super happy person is considered a superior outcome to 1000000000000 pretty darn happy people. Please explain how, if at all, I’m misinterpreting average utilitarianism.
Dan_Weinand
Karma: 70
Two notes: First, the term “genius” is difficult to define. Someone may be a “genius” at understanding the sociology of sub-Saharan African tribes, but this skill will obviously command a much lower market value compared to someone who is a “genius” as a chief executive officer of a large company. A more precise definition of genius will narrow the range of costs per year.
Second, and related to the first, MIRI is (to the extent of my knowledge) currently focusing on mathematics and formal logic research rather than programming. This makes recruiting a team of “geniuses” much cheaper. While skilled mathematicians can attract quite strong salaries, highly skilled programmers can demand significantly more. It seems the most common competing job for MIRI’s researchers would be that of a mathematics professor (which have a median salary ~88,000$). Based on this, MIRI could likely hire high quality mathematicians while offering them relatively competitive salaries.
Give machine A one nickel and have it produce a random sequence of 499 characters. Have machine B write a random sequence of 500 characters. Code machine A to pay machine B one nickel for its “book” whenever it has a nickel. Code machine B to give a nickel to machine A for its book whenever it has a nickel. Wait perhaps a few days, and you will have two bestselling authors reminiscent of Zach Weiner’s Macroeconomica http://www.smbc-comics.com/?id=2855
Sorry, a more applicable study is behind a pay-wall. http://www.jstor.org/discover/10.2307/351391?uid=3739640&uid=2&uid=4&uid=3739256&sid=21103313626383 Summary: data from six surveys suggest negative correlation between having children and several measures of life satisfaction. Standard caveats that correlation doesn’t imply causation, etc.
A study suggests that happiness is negatively affected by having children http://www.npr.org/2013/02/19/172373125/does-having-children-make-you-happier Note, there seem to be some issues with the methodology used in the study, but it also seems to be fairly well respected in academia.
Nitpick, the link in the first sentence reads “Definability of Truth in Probabilistic Locic” rather than logic.
Could you elaborate? I’m relatively familiar with and practice mindfulness meditation, but I’ve never heard of loving-kindness meditation.
Correct, it is enjoyable but I wish to make it more so. Hence why I used “more”.
I find myself happier when I act more kindly to others. In addition, lowering suffering/increasing happiness are pretty close to terminal values for me.
Thanks! And out of curiosity, does the first book have much data backing it? The author’s credentials seem respectable so the book would be useful even if it relied on mostly anecdotal evidence, but if it has research backing it up then I would classify it as something I need (rather than ought) to read.
Any good advice on how to become kinder? This can really be classified as two related goals, 1) How can I get more enjoyment out of alleviating others suffering and giving others happiness? 2) How can I reliably do 1 without negative emotions getting in my way (ex. staying calm and making small nudges to persuade people rather than getting angry and trying to change people’s worldview rapidly)?
It’s a quirk of the community, not an actual mistake on your part. LessWrong defines probability as Y, the statistics community defines probability as X. I would recommend lobbying the larger community to a use of the words consistent with the statistical definitions but shrug...
Then let me respecify what I should have stated originally, Christians who evangelize for Christianity are effective at persuading others to join the cause. I am concerned with how bugging people about a cause (aka evangelizing for it) will effect the number of people in that cause. The numbers shown suggest that if we consider evangelizing Christians to be a group, then they are growing as support of my hypothesis.
Oh, I’m well aware that this technique could be used to spread irrational and harmful memes. But if you’re trying to persuade someone to rationality using techniques of argument which presume rationality, it’s unlikely that you’ll succeed. So you may have to get your rationalist hands dirty.
Your call on what’s the better outcome: successfully convincing someone to be more rational (but having their agency violated through irrational persuasion) or leaving that person in the dark. It’s a nontrivial moral dilemma which should only be considered once rational persuasion has failed.
This would be the explanation http://lesswrong.com/lw/oj/probability_is_in_the_mind/ It really should be talked about more explicitly elsewhere though.
In light of the downvotes, I just wanted to explain that probability is frequently used to refer to a degree of belief by LessWrong folks. You’re absolutely right that statistical literature will always use “probability” to denote the true frequency of an outcome in the world, but the community finds it a convenient shorthand to allow “probability” to mean a degree of belief.
The proxy I am specifically looking at for evangelical Christianity is people who claim to have spread the “good news” about Jesus to someone. In other words, asking people whether they themselves have evangelized (the data on this is the fairly clear 47% to 52% upward trend). To me, it makes a lot of sense to call someone an Evangelical Christian if they have in fact evangelized for Christianity. And if we disagree on that definition, then there is really nothing more I can say.
The margin of sampling error is +- 3% while the difference the 1980 percentage and the 2005 percentage is 5%. I do think that a trend which has a p value less than .05 is statistically significant.
False, according to both the source you cited and http://www.gallup.com/poll/16519/us-evangelicals-how-many-walk-walk.aspx
Cross validation is actually hugely useful for predictive models. For a simple correlation like this, it’s less of a big deal. But if you are fitting a local linearly weighted regression line for instance, chopping the data up is absolutely standard operating procedure.