Why is nicotine not on that list?

Initial results: http://slatestarcodex.com/2014/02/16/nootropics-survey-results-and-analysis/

To make sure I understand this correctly: Bob cares about winning, and getting no apples is as good as 3^^^3 apples, so long as he rejects the room with the fewest, right?

A long one-lane, no passing highway has N cars. Each driver prefers to drive at a different speed. They will each drive at that preferred speed if they can, and will tailgate if they can't. The highway ends up with clumps of tailgaters lead by slow drivers. What is the expected number of clumps?

Imagine that you have a collection of very weird dice. For every prime between 1 and 1000, you have a fair die with that many sides. Your goal is to generate a uniform random integer from 1 to 1001 inclusive.

For example, using only the 2 sided die, you can roll it 10 times to get a number from 1 to 1024. If this result is less than or equal to 1001, take that as your result. Otherwise, start over.

This algorithm uses on average 10240/1001=10.228770... rolls. What is the fewest expected number of die rolls needed to complete this task?

When you know the right answer, you will probably be able to prove it.

Solution

Stimuli can be incorporated into dreams - for example, if someone in a sleep lab sees you are in REM sleep and sprays water on you, you're more likely to report having had a dream it was raining when you wake up. Yes, this has been formally tested. This provides strong evidence that dreams are going on during sleep.

More directly, communication has been established between dreaming and waking states by lucid dreamers in sleep labs. Lucid dreamers can make eye movements during their dreams to send predetermined messages to laboratory technicians monitoring them with EEGs. Again, this has been formally tested.

This question reminds me of http://lesswrong.com/lw/8wi/inverse_pzombies_the_other_direction_in_the_hard/

Indeed, there is an essay in Brainstorms articulating this position. IIRC Dennett does not explicitly commit to defending it, rather he develops it to make the point that we do not have a privileged, first-person knowledge about our experiences. There is conceivable third-person scientific evidence that might lead us to accept this theory (even if, going by Yvain's comment, this does not seem to actually be the case), and our first-person intuition does not trump it.

This game has taught me something. I get more enjoyment than I should out of watching a random variable go up and down, and probably should avoid gambling. :)

1. Live in a place with lots of demand. Silicon Valley and Boston are both good choices; there may be others but I'm less familiar with them.
2. Have a github account. Fill it with stuff.
3. Have a personal site. Fill it with stuff.
4. Don't worry about the degree requirements; everybody means "Bachelor's of CS or equivalent".
5. Don't worry about experience requirements. Unlike the degree requirement this does sometimes matter, but you won't be able to tell by reading the advert so just go ahead and apply.
6. Prefer smaller companies. The bigger the company, the more likely it is that your resume will be screened out by some automated process before it can reach someone like me. I read peoples' githubs; HR necessarily does not.

Ignore what they say on the job posting, apply anyway with a resume that links to your Github, websites you've built, etc. Many will still reject you for lack of experience, but in many cases it will turn out the job posting was a very optimistic description of the candidate they were hoping to find, and they'll interview you anyway in spite of not meeting the qualifications on the job listing.

Practicing whiteboard-style interview coding problems is very helpful. The best places to work will all make you code in the interview [1] so you want to feel at-ease in that environment. If you want to do a practice interview I'd be up for doing that and giving you an honest evaluation of whether I'd hire you if I were hiring.

[1] Be very cautious about somewhere that doesn't make you code in the interview: you might end up working with a lot of people who can't really code.

If you have the skills to do software interviews well, the hardest part will be getting past resume screening. If you can, try to use personal connections to bypass that step and get interviews. Then your skills will speak for themselves.

I read around 600 wpm without ever taking speedreading lessons so with training it should be very possible.

This was fun. I like how he emphasizes that every kid can figure out all of math by herself, and that thinking citizens are what you need for a democracy rather than a totalitarian state - because the Czech republic was a communist dictatorship only a generation ago, and many teachers were already teachers then.

I advise that you read the first 3 books on your list, and then reevaluate. If you do not know any more math than what is generally taught before calculus, then you have no idea how difficult math will be for you or how much you will enjoy it.

It is important to ask what you want to learn math for. The last four books on your list are categorically different from the first four (or at least three of the first four). They are not a random sample of pure math, they are specifically the subset of pure math you should learn to program AI. If that is your goal, the entire calculus sequence will not be that useful.

If your goal is to learn physics or economics, you should learn calculus, statistics, analysis.

If you want to have a true understanding of the math that is built into rationality, you want probability, statistics, logic.

If you want to learn what most math PhDs learn, then you need things like algebra, analysis, topology.

For what it's worth, I'm doing roughly the same thing, though starting with linear algebra. At first I started with multivariable calc, but when I found it too confusing, people advised me to skip to linear algebra first and then return to MVC, and so far I've found that that's absolutely the right way to go. I'm not sure why they're usually taught the other way around; LA definitely seems more like a prereq of MVC.

I tried to read Spivak's Calc once and didn't really like it much; I'm not sure why everyone loves it. Maybe it gets better as you go along, idk.

I've been doing LA via Gilbert Strang's lectures on the MIT Open CourseWare, and so far I'm finding them thoroughly fascinating and charming. I've also been reading his book and just started Hoffman & Kunze's Linear Algebra, which supposedly has a bit more theory (which I really can't go without).

Just some notes from a fellow traveler. ;-)

I think people generally agree that analysis, topology, and abstract algebra together provide a pretty solid foundation for graduate study. (Lots of interesting stuff that's accessible to undergraduates doesn't easily fall under any of these headings, e.g. combinatorics, but having a foundation in these headings will equip you to learn those things quickly.)

For analysis the standard recommendation is baby Rudin, which I find dry, but it has good exercises and it's a good filter: it'll be hard to do well in, say, math grad school if you can't get through Rudin.

For point-set topology the standard recommendation is Munkres, which I generally like. The problem I have with Munkres is that it doesn't really explain why the axioms of a topological space are what they are and not something else; if you want to know the answer to this question you should read Vickers. Go through Munkres after going through Rudin.

I don't have a ready recommendation for abstract algebra because I mostly didn't learn it from textbooks. I'm not all that satisfied with any particular abstract algebra textbooks I've found. An option which might be a little too hard but which is at least fairly comprehensive is Ash, which is also freely legally available online.

For the sake of exposure to a wide variety of topics and culture I also strongly, strongly recommend that you read the Princeton Companion. This is an amazing book; the only bad thing I have to say about it is that it didn't exist when I was a high school senior. I have other reading recommendations along these lines (less for being hardcore, more for pleasure and being exposed to interesting things) at my blog.

Keep a file with notes about books. Start with Spivak's "Calculus" (do most of the exercises at least in outline) and Polya's "How to Solve It", to get a feeling of how to understand a topic using proofs, a skill necessary to properly study texts that don't have exceptionally well-designed problem sets. (Courant&Robbins's "What Is Mathematics?" can warm you up if Spivak feels too dry.)

Given a good text such as Munkres's "Topology", search for anything that could be considered a prerequisite or an easier alternative first. For example, starting from Spivak's "Calculus", Munkres's "Topology" could be preceded by Strang's "Linear Algebra and Its Applications", Hubbard&Hubbard's "Vector Calculus", Pugh's "Real Mathematical Analysis", Needham's "Visual Complex Analysis", Mendelson's "Introduction to Topology" and Axler's "Linear Algebra Done Right". But then there are other great books that would help to appreciate Munkres's "Topology", such as Flegg's "From Geometry to Topology", Stillwell's "Geometry of Surfaces", Reid&Szendrői's "Geometry and Topology", Vickers's "Topology via Logic" and Armstrong's "Basic Topology", whose reading would benefit from other prerequisites (in algebra, geometry and category theory) not strictly needed for "Topology". This is a downside of a narrow focus on a few harder books: it leaves the subject dry. (See also this comment.)

Maybe the most important thing to learn is how to prove things. Spivak's Calculus might be a good place to start learning proofs; I like that book a lot.

I'm doing precalculus now, and I've found ALEKS to be interesting and useful. For you in particular it might be useful because it tries to assess where you're up to and fill in the gaps.

I also like the Art of Problem Solving books. They're really thorough, and if you want to be very sure you have no gaps then they're definitely worth a look. Their Intermediate Algebra book, by the way, covers a lot of material normally reserved for Precalculus. The website has some assessments you can take to see what you're ready for or what's too low-level for you.

By utilitiarian you mean:

1. Caring about all people equally

2. Hedonism, i.e. caring about pleasure/pain

3. Both of the above (=Bentham's classical utilitarianism)?

In any case, what answer do you expect? What would constitute a valid reason? What are the assumptions from which you want to derive this?

Interesting recent paper: "Is ZF a hack? Comparing the complexity of some (formalist interpretations of) foundational systems for mathematics", Wiedijk; he formalizes a number of systems in Automath.

It shouldn't be that hard to find code that solves a non-linear PDE. Google search reveals http://einsteintoolkit.org/ an open source that does numerical General Relativity.

However, QFT is not a PDE, it is a completely different object. The keyword here is lattice QFT. Google reveals this gem: http://xxx.tau.ac.il/abs/1310.7087

Nonperturbative string theory is not completely understood, however all known formulations reduce it to some sort of QFT.

It's a repost from last week.

Though rereading it, does anyone know whether Zach knows about MIRI and/or lesswrong? I expect "unfriendly human-created Intelligence " to parse to AI with bad manners to people unfamiliar with MIRI's work, which is probably not what the scientist is worried about.

Is this going to become even a harder distinction to make as tech continues to get better?

Wei once described an interesting scenario in that vein. Imagine you have a bunch of human uploads, computer programs that can truthfully say "I'm conscious". Now you start optimizing them for space, compressing them into smaller and smaller programs that have the same outputs. Then at some point they might start saying "I'm conscious" for reasons other than being conscious. After all, you can have a very small program that outputs the string "I'm conscious" without being conscious.

So you might be able turn a population of conscious creatures into a population of p-zombies or Elizas just by compressing them. It's not clear where the cutoff happens, or even if it's meaningful to talk about the cutoff happening at some point. And this is something that could happen in reality, if we ask a future AI to optimize the universe for more humans or something.

Also this scenario reopens the question of whether uploads are conscious in the first place! After all, the process of uploading a human mind to a computer can also be viewed as a compression step, which can fold constant computations into literal constants, etc. The usual justification says that "it preserves behavior at every step, therefore it preserves consciousness", but as the above argument shows, that justification is incomplete and could easily be wrong.

It depends on whether you subscribe to materialism. If you do then there nothing to measure. Conscious might even be a tricky illusion as Dennett suggests.

If on the other hand you do believe that there something beyond materialism there are plenty of frameworks to choose from that provide ideas about what one could measure.

I can't tell if the author means "rationalists" in the technical sense (i.e. as opposed to empiricists) but if he doesn't then I think it's unfair of him to require that rationalists "eliminate intuition and navigate life by reasoning about it", since this is so clearly irrational (because intuition is so indispensably powerful).

I loved this quote. I think it's a characterization of UU-style humanism that is fair but that they would probably agree with.

I would suggest using AngularJs instead, since it can be purely client-side code, you don't need to deal with anything server-side.

There are also some nice online development environments like codenvy that can provide a pretty rich environment and I belieave have some collaburative features too (instead of using dropbox, doodle and slideshare, maybe).

If all those technologies seem intimidating, some strategies:

• Focus on a subset, i.e. only html and css
• Use Anki a lot - I've used anki to put in git commands, AngularJS concepts and CSS tricks so that even if I wasn't actively working on a project using those, they'd stay at the back of my mind.

the only way failure modes I can see is if the exchange takes the money and runs, if there is a catastrophic failure of the trading engine, or if they get hacked.

The exchange can just fail in a large variety of ways and close (go bankrupt). If you're not "insured" you are exposed to the trading risk and insurance costs what, about 30%? and, of course, it doesn't help you with the exchange counterparty risk.

Depositors are not actually trading themselves, so the only way failure modes I can see is if the exchange takes the money and runs, if there is a catastrophic failure of the trading engine, or if they get hacked.

There is risk that is baked in from the fact that depositors are on the hook if trades can not be unwound quickly enough, and because this is Bitcoins, where volatility is crazy there is even more of this risk.

For example assume you lend money for some trader to go long, and now say that suddenly prices drop so quickly that it puts the trader beyond a margin call, in fact it puts him at liquidation, oh uh...the traders margin wallet is now depleted, who makes up the balance, the lenders. They actually do mention this on their website. But they don't tell you what the margin call policy is. This is a really important part of the risk. If they allow a trader to only put up $50 of a $100 position and call you in when your portion hits 25% that would be normal for something like index equities but pretty insane for something like Bitcoin.

I'm certainly comfortable with violent fantasy when the roles are acted out. This suggests to me that if I were convinced that certain person-seeming things were not alive, conscious, were not what they seemed that this might tip me in to some violent behaviors. I think at minimum I would experiment with it, try a slap here, a punch there. And where I went from there would depend on how it felt I suppose.

Also I would almost certainly steal more stuff if I was convinced that everything was landscape.

Well, the obvious difference would be that non-solipsists might care about what happens after they die, and act accordingly.

noticed that when you take enlightened self-interest into account, it seems that many behaviors don't change regardless of whether the people around you are sentient or not.

When I was younger and studying analytical philosophy, I noticed the same thing. Unless solipsism morphs into apathy, there are still 'representations' you can't control and that you can care about. Unless it alters your values, there should be no difference in behaviour too.

If I didn't care about other people, I wouldn't worry about donating to charities that actually help people. I'd donate a little to charities that make me look good, and if I'm feeling guilty and distracting myself doesn't seem to be cost-effective, I'd donate to charities that make me feel good. I would still keep quite a bit of my money for myself, or at least work less.

As it is, I've figured that other people matter, and some of them are a lot cheaper to make happy than me, so I decided that I'm going to donate pretty much everything I can to the best charity I can find.

Technically, it depends on your utility function. However, even without knowing your utility function, I can say that for such a low amount of money, your utility function is very close to linear, and option 5 is the best.

Here's one interesting way of viewing it that I once read:

Suppose that the option you chose, rather than being a single trial, were actually 1,000 trials. Then, risk averse or not, Option 5 is clearly the best approach. The only difficulty, then, is that we're considering a single trial in isolation. However, when you consider all such risks you might encounter in a long period of time (e.g. your life), then the situation becomes much closer to the 1,000 trial case, and so you should always take the highest expected value option (unless the amounts involved are absolutely huge, as others have pointed out).

As a poker player, the idea we always batted back and forth was that Expected Value doesn't change over shorter sample sizes, including a single trial. However you may have a risk of ruin or some external factor (like if you're poor and given the option of being handed $1,000,000 or flipping a coin to win $2,000,001).

Barring that, if you're only interested in maximizing your result, you should follow EV. Even in a single trial.

That depends on your utility function, specifically your risk tolerance. If you're risk-neutral, option 5 has the highest value, otherwise it depends.

Clearly option 5 has the higest mean outcome. If you value money linearly (that is, $12 is exactly 3 times as good as $4, and there's no special utility threshold along the way (or disutility at $0), it's the best option.

For larger values, your value for money may be nonlinear (meaning: the difference between $0 and $50k may be much much larger than the difference between $500k and $550k to your happiness), and then you'll need to convert the payouts to subjective value before doing the calculation. Likewise if you're in a special circumstance where there's a threshold value that has special value to you - if you need $3 for bus fare home, then option 1 or 2 become much more attractive.

That depends on the amount of background money and randomness you have.

Although I can't really see any case where I wouldn't pick option five. Even if that's all the money I will ever have, my lifespan, and by extension my happiness, will be approximately linear with time.

If you specify that I get that much money each day for the rest of my life, and that's all I get, then I'd go for something lower risk.

Steelmanning is about fixing errors in an argument (or otherwise improving it), while retaining (some of) the argument's assumptions. As a result, the argument becomes better, even if you disagree with some of the assumptions. The conclusion of the argument may change as a result, what's fixed about the conclusion is only the question that it needs to clarify. Devil's advocacy is about finding arguments for a given conclusion, including fallacious but convincing ones.

So the difference is in the direction of reasoning and intent regarding epistemic hygiene. Steelmanning starts from (somewhat) fixed assumptions and looks for more robust arguments following from them that would address a given question (careful hypothetical reasoning), while devil's advocacy starts from a fixed conclusion (not just a fixed question that the conclusion would judge) and looks for convincing arguments leading to it (rationalization with allowed use of dark arts).

A bad aspect of a steelmanned argument is that it can be useless: if you don't accept the assumptions, there is often little point in investigating their implications. A bad aspect of a devil's advocate's argument is that it may be misleading, acting as filtered evidence for the chosen conclusion. In this sense, devil's advocates exercise the skill of coming up with misleading arguments, which might be bad for their ability to reason carefully in other situations.

As far as I can tell...nothing. Most likely, there are simply many LessWrongers (like me) that disagree with E.Y. on this point.

Additionally, playing in an MP campaign offers all sorts of opportunities for sharpening your writing skills through stories set in the alternate history!

If you play in this game, you get to play with not one, but two LWers! I am Spain, beacon of learning, culture, and industry.

Other than the alternate start, are there any mods?

You know how when you see a kid about to fall off a cliff, you shrug and don't do anything because the standards of discourse aren't as high as they could be?

Me neither.

A task with a better expected outcome is still better (in expected outcome), even if it's hopeless, silly, not as funny as some of the failure modes, not your responsibility or in some way emotionally less comfortable.

https://en.wikipedia.org/wiki/Identifiable_victim_effect

Also, would you still want to save a drowning dog even if it might bite you out of fear and misunderstanding? (let's say it is a small dog and a bite would not be drastically injurious)

If you think helping humanity is (in long term) a futile effort, because humans are so stupid they will destroy themselves anyway... I'd say the organization you are looking for is CFAR.

So, how would you feel about making a lot of money and donating to CFAR? (Or other organization with a similar mission.)

I can't speak for you, but I would hugely prefer for humanity to not wipe itself out, and even if it seems relatively likely at times, I still think it's worth the effort to prevent it.

If you think existential risks are a higher priority than parasite removal, maybe you should focus your efforts on those instead.

I think it is amazingly myopic to look at the only species that has ever started a fire or crafted a wheel and conclude that

humans are so facepalmingly bad at making decisions

The idea that climate change is an existential risk seems wacky to me. It is not difficult to walk away from an ocean which is rising at even 1 m a year and no one hypothesizes anything close to that rate. We are adapted to a broad range of climates and able to move north south east and west as the winds might blow us.

Running out of fossil fuels, thinking we are doing something wildly stupid with our use of fossil fuels seems to me to be about as sensible as thinking a centrally planned economy will work better. It is not intuitive that a centrally planned economy will be a piece of crap compared to what we have, but it turns out to be true. Thinking you or even a bunch of people like you with no track record doing ANYTHING can second guess the markets in fossil fuels, well it seems intuitively right but if you ever get involved in testing your intuitions I don't think you'll find out it holds up. And if you think even doubling the price of fossil fuels really changes the calculus by much, I think Europe and Japan have lived that life for decades compared to the US, and yet the US is the home to the wackiest and ill-thought-out alternatives to fossil fuels in the world.

Can anybody explain to me why creating a wildly popular luxury car which effectively runs on burning coal is such a boon to the environment that it should be subsidized at $7500 by the US federal government and an additional $2500 by states such as California which has been so close to bankruptcy recently? Well that is what a Tesla is, if you drive one in a country with coal on the grid, and most of Europe, China, and the US are in that category, The Tesla S Performance puts out the same amount of carbon as a car getting (WRONG14WRONG) 25 mpg of gasoline.

Thoughts?

Taboo humanity.

I find it fascinating to observe.

If you're looking for ways to eliminate existential risk, then knowing that humanity is about to kill itself no matter what you do and you're just putting it off a few years instead of a few billion matters. If you're just looking for ways to help individuals, it's pretty irrelevant. I guess it means that what matters is what happens now, instead of the flow through effects after a billion years, but it's still a big effect.

If you're suggesting that the life of the average human isn't worth living, then saving lives might not be a good idea, but there are still ways to help keep the population low.

Besides, if humanity was great at helping itself, then why would we need you? It is precisely the fact that we allow extreme inequality to exist that means that you can make a big difference.

For instance, humans are so facepalmingly bad at making decisions for the long term (viz. climate change, running out of fossil fuels) that it seems clear that genetic or neurological enhancements would be highly beneficial in changing this

I think you underrate the existential risks that come along with substantial genetic or neurological enhancements. I'm not saying we shouldn't go there but it's no easy subject matter. It requires a lot of thought to address it in a way that doesn't produce more problems than it solves.

For example the toolkit that you need for genetic engineering can also be used to create artificial pandemics which happen to be the existential risk most feared by people in the last LW surveys.

When it comes to running out of fossil fuels we seem to do quite well. Solar energy halves costs every 7 years. The sun doesn't shine the whole day so there's still further work to be done, but it doesn't seem like an insurmountable challenge.

This is a tangent, but since you mention the "good founders started [programming] at 13" meme, it's a little bit relevant ...

I find it deeply bizarre that there's this idea today among some programmers that if you didn't start programming in your early teens, you will never be good at programming. Why is this so bizarre? Because until very recently, there was no such thing as a programmer who started at a young age; and yet there were people who became good at programming.

Prior to the 1980s, most people who ended up as programmers didn't have access to a computer until university, often not until graduate school. Even for university students, relatively unfettered access to a computer was an unusual exception, found only in extremely hacker-friendly cultures such as MIT.

Put another way: Donald Knuth probably didn't use a computer until he was around 20. John McCarthy was born in 1927 and probably couldn't have come near a computer until he was a professor, in his mid-20s. (And of course Alan Turing, Jack Good, or John von Neumann couldn't have grown up with computers!)

(But all of them were mathematicians, and several of them physicists. Knuth, for one, was also a puzzle aficionado and a musician from his early years — two intellectual pursuits often believed to correlate with programming ability.)

In any event, it should be evident from the historical record that people who didn't see a computer until adulthood could still become extremely proficient programmers and computer scientists.

I've heard some people defend the "you can't be good unless you started early" meme by comparison with language acquisition. Humans generally can't gain native-level fluency in a language unless they are exposed to it as young children. But language acquisition is a very specific developmental process that has evolved over thousands of generations, and occurs in a developmentally-critical period of very early childhood. Programming hasn't been around that long, and there's no reason to believe that a critical developmental period in early adolescence could have come into existence in the last few human generations.

So as far as I can tell, we should really treat the idea that you have to start early to become a good programmer as a defensive and prejudicial myth, a bit of tribal lore arising in a recent (and powerful) subculture — which has the effect of excluding and driving off people who would be perfectly capable of learning to code, but who are not members of that subculture.

The same tortured analysis plays out in the business world, where Paul Graham, the head of YCombinator, a startup incubator, explained that one reason his company funds fewer women-led companies is because fewer of them fit this profile of a successful founder:

If someone was going to be really good at programming they would have found it on their own. Then if you go look at the bios of successful founders this is invariably the case, they were all hacking on computers at age 13.

The trouble is, successful founders don’t run through a pure meritocracy, either. They’re supported, mentored, and funded when they’re chosen by venture capitalists like Graham. And, if everyone is working on the same model of “good founders started at 13″ then a lot of clever ideas, created by people of either gender, might get left on the table.

A similar argument was presented in an article at Slate: Affirmative action doesn’t work. It never did. It’s time for a new solution.:

But even if the government were keeping better tabs on affirmative action, the bigger problem is that its jurisdiction doesn’t reach the parts of the economy where affirmative action is most desperately needed: the places where real money is made and real power is allocated. The best example of this is the industry that dominates so much of our economy today: the technology sector. Silicon Valley’s racial diversity is pretty terrible, the kind of gross imbalance that inspires special reports on CNN.

It’s a dismal state of affairs, but how could it really be otherwise? Silicon Valley isn’t just an industry; it’s a social and cultural ecosystem that grew out of a very specific social and cultural setting: mostly West Coast, upper-middle-class white guys who liked to tinker with motherboards and microchips. If you were around that culture, you became a part of it. If you weren’t, you didn’t. And because of the social segregation that pervades our society, very few black people were around to be a part of it.

Some would purport to remedy this by fixing the tech industry job pipeline: more STEM graduates, more minority internships and boot camps, etc. And that will get you changes here and there, at the margins, but it doesn’t get at the real problem. The big success stories of the Internet age—Instagram, YouTube, Twitter—all came about in similar ways: A couple of people had an idea, they got together with some of their friends, built something, called some other friends who knew some other friends who had access to friends with serious money, and then the thing took off and now we’re all using it and they’re all millionaires. The process is organic, somewhat accidental, and it moves really, really fast. And by the time those companies are big enough to worry about their “diversity,” the ground-floor opportunities have already been spoken for

A freaky thing I once saw... when my daughter was about 3 there were certain things she responded to verbally, I can't remember what the thing was in this example, but something like me asking here "who is your rabbit?" and her replying "Kisses" (which was the name of her rabbit).

I had videoed some of this exchange and was playing it on a TV with her in the room. I was appalled to hear her responding "Kisses" upon hearing me on the TV saying "who is your favorite rabbit." Her response was extremely similar to her response on the video, tremendous overlap in timing tone and inflection. Maybe 20 to 50 ms off in timing (almost sounded like unison).

I really had the sense that she was a machine and it did not feel good.

This doesn't seem related to reductionism to me, except in that most reductionists don't believe in Knightian free will.

One person being horribly tortured for eternity is equivalent to that one person being copied infinite times and having each copy tortured for the rest of their life. Death is better than a lifetime of horrible torture, and 3^^^3, despite being bigger than a whole lot of numbers, is still smaller than infinity.

Of course, society as a whole should (and does) work on both of these things. But one individual can really only pick one to make a sizable impact -- or at the very least, one at a time. Which do you guys think may be more effective to work on?

The core question is: "What kind of impact do you expect to make if you work on either issue?"

Do you think there work to be done in the space of solar power development that other people than yourself aren't effectively doing? Do you think there work to be done in terms of better judgment and decision-making that other people aren't already doing?

we need to develop solar power or whatever else before all the oil and coal run out,

The problem with coal isn't that it's going to run out but that it kills hundred of thousands of people via pollution and that it creates climate change.

I know CFAR is working on that sort of thing, but I'm talking about more genetic or neurological changes)

Why? To me it seems much more effective to focus on more cognitive issues when you want to improve human judgment. Developing training to help people calibrate themselves against uncertainty seems to have a much higher return than trying to do fMRI studies or brain implants.

The economy is quite capable of dealing with finite resources. If you have land with oil on it, you will only drill if the price of oil is increasing more slowly than interest. If this is the case, then drilling for oil and using the value generated by it for some kind of investment is more helpful than just saving the oil.

Climate change is still an issue of course. The economy will only work that out if we tax energy in proportion to its externalities.

We should still keep in mind that climate change is a problem that will happen in the future, and we need to look at the much lower present value of the cost. If we have to spend 10% of our economy on making it twice as good a hundred years from now, it's most likely not worth it.

Why?

Criticism's well and good, but 140 characters or less of out-of-context quotation doesn't lend itself to intelligent criticism. From the looks of that feed, about half of it is inferential distance problems and the other half is sacred cows, and neither one's very interesting.

If we can get anything from it, it's a reminder that killing sacred cows has social consequences. But I'm frankly tired of beating that particular drum.

Already deployed is a better example: computer network protocols.