Note to self, in case I come back to this problem: the Vienna Circle fits the bill.
WhySpace_duplicate0.9261692129075527
Karma: 379
:)
Honestly, there are a bunch of links I don’t click, because the 2 or 3 word titles aren’t descriptive enough. I’m a big fan of the community norm on more technically minded subreddits, where you can usually find a summary in one of the top couple comments.
So, I’m doing what I can to encourage this here. But mostly, I thought it was important on the AI front, and wanted to give a summary which more people would actually read and discuss.
Here are some thoughts on the viability of Brain Computer Interfaces. I know nothing, and am just doing my usual reality checks and initial exploration of random ideas, so please let me know if I’m making any dumb assumptions.
They seem to prefer devices in the blood vessels, due to the low invasiveness. The two specific form factors mentioned are stents and neural dust. Whatever was chosen would have to fit in the larger blood vessels, or flow freely through all of them. Just for fun, let’s choose the second, much narrower constraint, and play with some numbers.
Wikipedia says white blood cells can be up to 30 μm in diameter. (Also, apparently there are multiple kinds of white blood cells. TIL.) I’d guess that we wouldn’t want our neural dust to be any larger than that if we want to be able to give it to someone and be able to reverse the procedure later without any surgery. The injection should be fine, but if you wanted to filter these things back out of your blood, you’d have to do something like giving blood, but with a magnet or something to filter out the neural dust. So, what could we cram into 30 μm?
Well, my first hit when searching “transistors per square mm” is an article titled “Intel Now Packs 100 Million Transistors in Each Square Millimeter”, so let’s go with that. I realize Elon’s ~10 year time horizon would give us another ~6 Moore’s law doublings, but if they did an entire run of a special chip just for this, then maybe they don’t want to pay top dollar for state of the art equipent, so let’s stick with 100m/mm^2. That’d give us on the order of 10k-100k transistors to work with, if we filled the entire area with transistors and nothing else.
But, looking at most electronics, they are more than just a chip. Arduinos and cellphones and motherboards may be built around a chip, but the chip itself has a relatively small footprint on the larger PCB. So, I’m probably missing something which would be incredibly obvious to someone with more hardware experience. (Is all the other stuff just for interfacing with other components and power supplies? In principle, could most of it be done within the chip, if you were willing to do a dedicated manufacturing run just for that one divice, rather than making more modular and flexible chips which can be encorporate into a range of devices?)
If we assume it’d be powered and transmit data electromagnetically, it’d also need an antenna, and an induction coil. I have a hunch that both of these suffer from issues with the square-cube law, so maybe that’s a bad idea. The neural dust article mentioned that the (mm scale) devices both reported information and received power ultrasonically, so maybe the square-cube law is the reason. (If not, we might also run into the diffraction limit, and not have any wavelengths of light which were short enough to effect antenas that size, but still long enough to penetrate the skull without ionizing atoms.)
I like the idea of ultrasonic stuff because acoustic waves travel through tissue without depositing much energy. So, you get around the absorption problem photons have, and don’t have to literally x-ray anyone’s brain. Also, cranial ultrasounds are already a thing for infants, although they have to switch to transcranial Doppler for adults, because our skulls have hardened. Nearby pieces of neural dust would be monitoring the same neurons, and so would give off their signals at about the same time, boosting the signal but maybe smearing it out a little in time.
So, let’s play with some numbers for piezoelectric devices instead. (I assume that’s what their ultrasonic neural dust must be using, at least. They are switching between electricity and motion somehow, and piezoelectrichttps are the name for the solid state way of doing that. I can’t picture them having tiny speakers with electromagnets on flexible speaker cones. The Wikipedia page on transducers doesn’t mention other options.)
Quartz crystals are already used for timing in electronics, so maybe the semiconductor industry already has the ability to make transducers if they wanted to. (I’d be surprised if they didn’t, since quartz is just ccrystaline silicon dioxide. Maybe they can’t get the atomic lattice into the right orientation consistently, though.) If you couldn’t transmit and receive simultaneously without interfering, you’d need a tiny capacitor to store energy for at least 1 cycle. I don’t know how small quartz crystals could be made, or whether size is even the limiting factor. Maybe sufficiently small piezoelectric can’t even put out strong enough pulses to be detectable on an ultrasound, or require too much power to be safely delivered ultrasonically? I don’t know, but I’d have to play with a bunch of numbers to get a good feel.
I don’t really know where to start, when discussing monitoring neuron firings. Could it be done electromagnetically, since they should make an instantaneous electromagnetic field? Or would the signal be too weak near a blood vessel? Apparently each neuron firing changes the concentration of Na, K, Cl, and Ca in the surrounding blood. Could one of these be monitored? Maybe spectrally, with a tiny LED of the appropriate wavelength, and a photo detector? I think such things are miniturizeable in principle, but I’m not sure we can make them with existing semiconductor manufacturing techniques, so the R&D would be expensive. We probably don’t have anything which emits at the exact wavelength we need for spectroscopy though, and even if we did, I bet the LED would need voltage levels which would be hard to deliver without adding a voltage transformer or whatever the DC equivalent is.
Or, can we dump all the fancy electronics all together? Could we do something as simple as a clay particle (tiny rock) coated with a dispersent or other Surfactant, so that changes in the surrounding chemistry cause the collapse of the double layer), making the clay particles to flocculate together? Would such clumps of clay particles be large enough and have high enough density to show up on an ultrasound or other divice? Obviously this wouldn’t let us force a neuron to fire, but it might be a cheap way of detecting them.
Maybe the electronics could be added later, if modifying surface charge and chemistry is enough to make a neuron fire. Neurotransmitrers affect neuron firings somehow, if I usnderstand correctly, so maybe chain a bunch of neurotransmitters to some neural dust as functional groups on the end of polymer chains, then change surface charge to make the chains scrunch up or fan out?
I only know just enough about any of this to get myself into trouble, so if it doesn’t look like I know what I’m talking about, I probably don’t.
(Sorry to spam comments. I’m separating questions out to keep the discussion tidy.)
The article only touches on it briefly, but suggests faster AI takeoff are worse, but “fast” is only relative to the fastest human minds.
Has there been much examination of the benefits of slow takeoff scenarios, or takeoffs that happen after human enhancements become available? I vaguely recall a MIRI fundraiser saying that they would start putting marginal resources toward investigating a possible post-Age of EM takeoff, but I have no idea if they got to that funding goal.
Personally, I don’t see Brain-Computer Interfaces as useful for AI takeoffs, at least in the near term. We can type ~100 words per minute, but it takes more than 400 minutes to write a 40,000 word novel. So, we aren’t actually I/O bound, as Elon believes. We’re limited by the number of neurons devoted to a given task.
Early BCIs might make some tasks much faster, like long division. Since some other tasks really are I/O bound, they’d help some with those. But, we wouldn’t be able to fully keep up with AI unless we had full-fledged upgrades to all our cognative architecture.
So, is almost keeping up with AI likely to be useful, or are slow takeoff just as bad? Are the odds of throwing together a FAI in the equivalent of a month any better than in a day? What % of those pannicked emergency FAI activities could be speed up by better computer user interfaces/text editors, personal assistants, a device that zapped your brain every time it detected Akrasia setting in, or by a RAM upgrade to the brain’s working-memory?
(sorry to spam. I’m separating questions out to keep the discussion tidy.)
TL;DR of the article:
This piece describes a lot of why Elon Musk wanted to start Neurolink, and how Brain-Computer Interfaces (BCIs) currently work, and how they might be implemented in the future. It’s a really, really broad article, and aims for breadth while still having enough depth to be useful. If you already have a grasp of evolution of the brain, Dual Process Theory, parts of the brain, how neurons fire, etc. you can skip those parts, as I have below.
AI is dangerous, because it could achieve superhuman abilities and operate at superhuman speeds. The intelligence gap would be much smaller if we also had access to such abilities. Therefore, we should attempt this if possible.
This might be possible, despite how extremely limited and highly invasive existing BCIs are. Opening the skull is obviously way too invasive for most people, but the blood vessels offer a possible minimally invasive solution. They are essentially a highway which goes directly to every neuron in the brain. Current methods monitor at most ~100 neurons, or have low temporal resolution. 1,000,000 neurons is probably the tipping point, where it would stop being an alternative to a keyboard/screen input/outputs, and start being transformative.
Neuralink is exploring many possibilities, and probably won’t narrow to just one any time soon. However, options might include “neural dust”, or stints in the blood vessels. Just as dies have made fine cell structures visible under microscopes, and genetically engineering bioluminescent genes into living animals has made cells glow when active, Neuralink would need a way for such a device to detect individual neuron firings on a large scale.
To do this, the inserts themselves only need to be able to:
React differently to electrical discharge associated with a nearby neurons firing, or to other changes associated with neurons firing, like sodium and potassium levels.
Have that difference be detectable from outside the skull. (I’d divide this into active methods, like emitting light in a wavenelgth which penetrates the skull, or passive changes in properties detectable from the outside, like radioactive isotopes which cluster together based on variables in blood flow.)
(The piece doesn’t make this distiction, but I thought it would be useful for better discussion and understanding.)
Neuralink, of course, hasn’t narrowed the specifics down very much (and will probably pivot several times, in my opinion). However, they will start out offering something largely similar to the sorts of BCIs available to people with paralysis or sensory problems. Elon hopes that if everything goes smoothly, in a decade they would have something which could provide a useful feature to someone without such disabilities, if the FDA would allow it.
They also hope to be able to eventually influence neural firings, so that we could supply information to the brain, rather than just reading information out. This would require something which could be influenced from the outside, and then influence nearby neurons. We can already put an electric field through the whole brain, to minimize seizures, but for meaningful inputs this would also have to be done at the neuron leven.
Why you should read it anyway:
It’s >35,000 words. (For comparison, the cutoff for “short novel” is 40,000.) That said, it’s a good read, and I recommend it if you want to understand why Elon Musk might think a BCI might increase our odds of surviving an AI takeoff scenario.
A lot of it is still hand-waving, and doesn’t make it clear that we don’t necessarily need full self-replicating autonomous nanobots or whatever. Since it doesn’t provide a specific architecture, but just surveys what might be possible, I think it’s easy to give an uncharatable reading. I’ve tried to steel-man the phrasing here, but I think if we focus on tangible, near-term concepts, it can be illustrative of what is possible.
If you read this with a critical eye, you’ll just note that they haven’t narrowed down to one architecture yet, and complain that their lack-of-an-architecture can’t possibly work. The point is to convince lay people that this might even be possible, not to convince them that Neurolink will succeed, but the comments I’ve seen so far have just been skepticism of Neurolink.
Instead, I’d encourage you to read with an eye toward what could be done with a stint or neural dust, and then critically examine the more tangible challenge of how small each of those possible capabilities could be made. What could be done passively? What could be done if inductively powered? How small of blood vessels could various devices fit through? Will those shrink with Moore’s law, or are they physics-constrained?
Such questions will generate the possible concrete architectures which you can then apply a critical lens to. Don’t bother reading if you just want to be critical of the exploratory activity itself. It won’t even put up a fight.
TL;DR: What are some movements you would put in the same reference class as the Rationality movement? Did they also spend significant effort trying not to be wrong?
Context: I’ve been thinking about SSC’s Yes, We have noticed the skulls. They point out that aspiring Rationalists are well aware of the flaws in straw Vulcans, and actively try to avoid making such mistakes. More generally, most movements are well aware of the criticisms of at least the last similar movement, since those are the criticisms they are constantly defending against.
However, searching “previous ” in the comments doesn’t turn up any actual exemples.
Full question: I’d like to know if anyone has suggestions for how to go about doing reference class forcasting to get an outside view on whether the Rationality movement has any better chance of succeeding at it’s goals than other, similar movements. (Will EA have a massive impact? Are we crackpots about Cryonics, or actually ahead of the curve? More generally, how much weight should I give to the Inside View, when the Outside View suggests we’re all wrong?)
The best approach I see is to look at past movements. I’m only really aware of Logical Positivism, and maybe Aristotle’s Lyceum, and I have a vague idea that something similar probably happened in the enlightenment, but don’t know the names of any smaller schools of thought which were active in the broader movement. Only the most influential movements are remembered though, so are there good examples from the past ~century or so?
And, how self-critical were these groups? Every group has disagreements over the path forward, but were they also critical of their own foundations? Did they only discuss criticisms made by others, and make only shallow, knee-jerk criticisms, or did they actively seek out deep flaws? When intellectual winds shifted, and their ideas became less popular, was it because of criticisms that came from within the group, or from the outside? How advanced and well-tested were the methodologies used? Were any methodologies better-tested than Prediction Markets, or better grounded than Bayes’ theorem?
Motive: I think on average, I use about a 50⁄50 mix of outside and inside view, although I vary this a lot based on the specific thing at hand. However, if the Logical Positivists not only noticed the previous skull, but the entire skull pile, and put a lot of effort into escaping the skull-pile paradigm, then I’d probably be much less certain that this time we finally did.
I’m not so sure. Would your underlying intuition be the same if the torture and death was the result of passive inaction, rather than of deliberate action? I think in that case, the torture and death would make only a small difference in how good or bad we judged the world to be.
For example, consider a corporate culture with so much of this dominance hierarchy that it has a high suicide rate.
Also:
Moloch whose buildings are judgment! … Lacklove and manless in Moloch! … Moloch who frightened me out of my natural ecstasy!
… Real holy laughter in the river! They saw it all! the wild eyes! the holy yells! They bade farewell! They jumped off the roof! to solitude! waving!
— Meditations on Moloch/Howl
Doesn’t seem like a difference of kind, and maybe not even of degree. (The suicide rate is a couple percent, and higher in industrialized countries if I recall. What percent of the citizens of Oceania are tortured to death? ~2%?) I think 1984 is mainly shocking because of status quo bias. (But I haven’t read it, so I’m probably missing some stronger points against that world.)
Most of the badness seems to be from the general state of both worlds, rather than from the occasional person tortured to death on the side. That’s just the tip of the iceberg. It’s a small, but obvious, part of much deeper problems. That’s why EA doesn’t use suicide rate or incarceration rate as their primary metrics to optimize for. They’re just symptoms.
I’d add that it also starts to formalise the phenomenon where one’s best judgement oscillates back and forth with each layer of an argument. It’s not clear what to do when something seems a strong net positive, then a strong negative, then a strong positive again after more consideration. If the value of information is high, but it’s difficult to make any headway, what should we even do?
This is especially common for complex problems like xrisk. It also makes us extremely prone to bias, since we by default question conclusions we don’t like more than ones we do.
This is really sad. I’m sorry to hear things didn’t work out, but I’m still left wondering why not.
I guess I was really hoping for a couple thousand+ word post-mortem, describing the history of the project, and which hypotheses you tested, with a thorough explanation of the results.
If you weren’t getting enough math input, why do you think that throwing more people at the problem wouldn’t generate better content? Just having a bunch of links to the most intuitive and elegant explanations, gathered in one place, would be a huge help to both readers and writers. Students trying to learn are already doing this through blind googling, so the marginal work to drop the links is low.
Pulling all the info together into a good explanation still requires one dedicated person, but perhaps that task can be broken down into chunks too. Like, once one version is written, translating it for non-mathy people should be relatively easy. Same for condensing things for mathy people.
But, why wouldn’t adding more mathematicians mean a few would be good at and interested in writing new articles? Where did you do outreach? What did you do? There are entire communities, scattered across the web, who exist to try and learn and teach math. Have you tried partnering with any of them, or recruiting members?
If not, why do you think it won’t work? Do you see promising alternative approaches, or are good explanations impossible even in principle?
Sorry for the flood of questions. I’ve just been waiting with baited breath for Arbital to stop pushing me away and start pulling people in. I even linked some people, but felt guilty about it for putting a strain on your overloaded servers before you were ready for the general public.
I don’t see any reason why AI has to act coherently. If it prefers A to B, B to C, and C to A, it might not care. You could program it to prefer that utility function.*
If not, maybe the A-liking aspects will reprogram B and C out of it’s utility function, or maybe not. What happens would depend entirely on the details of how it was programmed.
Maybe it would spend all the universe’s energy turning our future light cone from C to B, then from B to A, and also from A to C. Maybe it would do this all at once, if it was programmed to follow one “goal” before preceding to the next. Or maybe different parts of the universe would be in different stages, all at the same time. Think of it like a light-cone blender on pure.
Our default preferences seem about that coherent, but we’re able to walk and talk, so clearly it’s possible. It explains a lot of the madness and incoherence of the way the world is structured, certainly. Luckily, we seem to value coherence, or at least are willing to sacrifice on having our cake and eating it too when it becomes clear that we can’t have it both ways. It’s possible an subtly incoherent AGI would operate at cross purposes for a long time before discovering and correcting it’s utility function, if it valued coherence.
However, MIRI isn’t trying to program a sane AGI, not explore all possible ways an AI can be insane. Economists like to simplify human motives into idealized rational agents, because they are much, much simpler to reason about. The same is true for MIRI, I think.
I’ve given this sort of thing a little thought, and have a Evernote note I can turn into a LW post, if there is interest.
* I use the term “utility function broadly, here. I guess “programming” would be more correct, but even an A>B>C>A AI bears some rough resemblance to a utility function, even if it isn’t coherent.
I rather like this way of thinking. Clever intuition pump.
What are we actually optimizing the level-two map for, though?
Hmmm, I guess we’re optimizing out meta-map to produce accurate maps. It’s mental cartography, I guess. I like that name for it.
So, Occam’s Razor and formal logic are great tools of philosophical cartographers. Scientists sometimes need a sharper instrument, so they crafted Solomonoff induction and Bayes’ theorem.
Formal logic being a special case of Bayesian updating, where only p=0 and p=1 values are allowed. There are third alternatives, though. Instead of binary Boolean logic, where everything most be true or false, it might be useful to use a 3rd value for “undefined”. This is three-value logic, or more informally, Logical Positivism. You can add more and more values, and assign them to whatever you like. At the extreme is Fuzzy Logic, where statements can have any truth value between 0 and 1. Apparently there’s also something which Bayes is just a special case of, but I can’t recall the name.
Of all these possible mental cartography tools though, Bayes seems to be the most versatile. I’m only dimly aware of the ones I mentioned, and probably explained them a little wrong. Anyone care to share thoughts on these, or share others they may know? Has anyone tried to build a complete ontology out of them the way Eliezer did with Bayes? Are there other strong metaphysical theories from philosophy which don’t have a formal mathematical corollary (yet)?
True. Maybe we could still make celebrate our minor celebrities more, along with just individual good work, to avoid orbiting too much around any one person. I don’t know what the optimum incentive gradient is between small steps and huge accomplishments. However, I suspect that on the margin more positive reinforcement is better along the entire length, at least for getting more content.
(There are also benefits to adversarial review and what not, but I think we’re already plenty good at nitpicking, so positive reinforcement is what needs the most attention. It could even help generate more long thoughtful counterarguments, and so help with the better adversarial review, improving the dialectic.)
Awesome link, and a fantastic way of thinking about how human institutions/movements/subcultures work in the abstract.
I’m not sure the quote conveys the full force of the argument out of that context though, so I recommend reading the full thing if the quote doesn’t ring true with you (or even if it does).
I agree that philosophy and neuroscience haven’t confirmed that the qualia I perceive as red is the same thing as the qualia you experience when you look at something red. My red could be your blue, etc. (Or, more likely, completely unrelated sensations chosen randomly from trillions of possibilities.) Similarly, we can’t know exactly what it’s like to be someone else, or to be an animal or something.
However, it’s perfectly reasonable to group all possible human experiences into one set, and group all possible things that an ant might experience in another. If you scanned the brains of a trillion ants and a trillion humans, and ran them as digital simulations, it would be easy for someone to look at them and know which was which.
Similarly, if you scanned 3^^^3 artists and 3^^^3 programmers, I’d bet that you could find certain patterns and systematic differences in how they think. After looking at all those minds, you could easily look at another one and tell whether they were an artist or an programmer. Same for men/women, or republicans/democrats, etc.
This is despite potentially huge differences in the internal subjective experiences of programmers. It’s not that there’s one single “what it’s like to be an programmer” experience or anything, but there is a single set of all programmer minds. This includes qualia and programming methods of thought, and whatever else.
Maybe you could even measure these differences with even crude MRI scans of people’s brains. It would be interesting to scan a thousand cis men after certain verbal prompts asking how they feel about their gender identity. If OP’s hypothesis is true, then confident trans men should look pretty similar to confident cis men, and trans men worrying “am I really an X” should look a lot like cis men questioning their own gender identity.
You should get about the same result if you ran the experiment again on cis and trans women. Obviously there would be some confounders, like hormone levels and any physical differences between people born biologically male or female. However, this sort of thing seems easy enough to control for. The bigger issue I see is that all those MRIs would cost a fortune, and we may not even have sufficiently high resolution technology to even see the differences we’re looking for.
But, doing philosophy is cheap, and it seems to me that hypotheses like these have decent odds of being true. I agree that reasoning about individual differences may be as hopeless as wondering what it’s like to be a bat, but reasoning about huge classes of mind states seems entirely valid.
that still rules out the globehopping, couchsurfing lifestyle.
Not necessarily. I’d be fine with it if my girlfriend decided to hitchhike around Europe for a month or two, and I’m pretty sure she’d be fine with me doing the same. There’s no reason the one with the job couldn’t take a vacation in the middle, too.
If the unemployed partner did this twice a year, for 2 months at a time, that’d be 1⁄3 of their time spent globetrotting. If they did this 3x a year, (2 months home, then 2 months exploring, then 2 months home again) that’d be pushing it, but might be stable long term if they could find ways to make sure the working party didn’t feel used or left out.
This was a useful article, and it’s nice to know the proper word for it. Let me see if I can add to it slightly.
Maybe a prisoner is on death row, and if they run away they are unlikely to suffer the consequences, since they’ll be dead anyway. However, even knowing this, they may still decide to spend their last day on earth nursing bruises, because they value the defiance itself far more than any pain that could be inflicted on them. Perhaps they’d even rather die fighting.
It looks like you don’t reflectively endorse actions taken for explicitly semiotic reasons, and lean toward more pure consequentialism. Based only on what you’ve said, semiotic actions aren’t fallacious when they yield outside benefits in the long run, but are fallacious when they don’t lead to other good things. (Because you treat semiotic acts as only instrumentally valuable, rather than as terminal values.)
However, it seems likely that some semiotic acts can be good in and of themselves. That is, we reflectively endorse them, rather than just doing them because evolution gave us an impulse to signal which we have a hard time fighting. Semiotic impulse is certainly a human universal, and therefore a part of our current utility function, and it seems plausible that it will survive intact in some form even after more careful examination of our values.
It seems like that sorts of the things we do for explicitly symbolic reasons are more likely to fall into this category than normal subconscious signaling. If we didn’t endorse it to some degree, we’d just make sure not to be conscious of doing it, and then keep doing it anyway. To be aware that we’re doing it, it can’t conflict too much with our positive self-image, or societal values, or anything like that.
Of course, just because we naively support a semiotic act explicitly doesn’t mean we still will after closer examination. Maybe we think engagement rings are a touching form of costly signaling at first, but once we understand more about the signaling dynamics at play making us do such things, we decide that conspicuous displays of consumption make society far worse off. You may then decide not to feed Moloch, and try to lessen the keeping up with the Joneses effect.
Personally, I’m rather a fan of the Apollo program, and the idea that long after humanity has killed itself off, the Voyager probe may still survive drifting among the stars, with our last surviving words inscribed in gold.
Agreed. I’d love to see even more of all of these sorts of things, but the low margin nature of the industry makes this somewhat difficult to attack directly, so there isn’t anywhere near as much money being invested in that direction as I would like.
I believe NASA has gotten crop yields high enough that a single person can be fed off of only ~25 m^2 of land, (figure may be off, or may be m^3 or something, but that’s what I vaguely recall.) but that would have been with fancy hydroponic/aquaponic/aeroponic setups or something, and extremely high crop density. It would be awesome to see fully automated vertical greenhouses pumping out GMO produce for almost 0 cost.
I recently saw someone joke about engineering GMO wheat as an invasive species to out-compete grass. If we wanted to, I suppose we could also replace all the planet’s trees with fruit trees, and build ourselves a garden of Eden, with an absurd surplus of food, available for free. That’s probably a little extreme, considering that some people are rather attached to nature as it is, but maybe we’ll terraform other planets like that?
Just some musings and paradise engineering. It’s interesting to consider various post-scarcity economies where things we work hard for are as common as air.
A job is a cost
Agreed. When I said the “cost to local jobs” I was being informal, but referring to the (supposed) increase in unemployment as Walmart displaces local, less efficient small businesses.
Paying people to do a job which can be eliminated is like paying people to dig holes and fill them back in. I’d rather just give them the money than pay them to do useless work, but I’ll take the second option over them being unemployed.
As an interesting side note, I think this might put me on the opposite side of the standard anti-Walmart argument. The meme argues that, Walmart not paying its workers a living wage and making it difficult to unionize forces the government to step in and provide aid, and that this is in effect subsidizing Walmart.
However, because Walmart sells mainly to the poor, I am in favor of subsidizing them in any way that passes through to the poor and doesn’t get skimmed off the top. Maybe that would mean I’d even be against a law forcing them to pay $10/hr or some such, if the benefits to the employees didn’t outweigh the net drawbacks to the customers.
Mainly I just find it depressing that all current political narratives seem to ignore these complexities, and boil down to “Walmart bad” or “markets good” or whatever. Maybe some more intelligent conversations happen behind closed doors, where no one can hear politicians make sane concessions to the other side.
these are called “recessions” and … “depressions”.
Ha, very good point. Our current society is largely built around growth, and when growth stops the negative effects absolutely do trickle down, even to people who don’t own stocks. In fact, companies were counting on those increases, and so have major issues when they don’t materialize, and need to get rid of workers to cut costs.
I will mention that through most of history and prehistory, the economic growth rate has been much, much, smaller. I haven’t read it, so I can’t vouch for its quality, but apparently the book The End of Growth: Adapting to Our New Economic Reality suggests that economic growth can’t continue indefinitely due to physics limitations, and lays out a framework for transitioning to a post-growth economy. I have no idea how gentle or unpleasant such a transition might actually be. (Also, note that I am hopeful that we can avoid resource limitations by transitioning to a space based economy, and am nowhere near as pessimistic as I think the authors are likely to be.)
China.
China did indeed achieve massive benefits from industrialization. There’s a lot of evidence that maximizing economic growth is an excellent way to play catch-up and obtain modern amenities for your population. Perhaps it’s even the fastest theoretically possible way, since access to capital is the limiting factor for improved quality of life, and selling cheap stuff gets you lots of capital. I don’t think developing countries should try communism or anything like that, unless for some reason they expect it to result in higher economic growth, since the data suggests that free markets are much better for them.
I would, however, suggest that the price of basic amenities appears to me to be a limiting factor in the quality of life of poor people in developed nations, and that increases in national wealth tend not to translate into proportional increases in purchasing power for them, although there is still some gain. (As I said before, I should really look into the details, though.) I see 2 basic classes of solutions:
You can try to funnel more goods and money to them. This might be done through tax structures, aid programs, education, basic income, etc. Either you try and improve their earning potential, or give them things directly, but either way they wind up with more. The end result is that they can purchase more such amenities at the same price, or perhaps a little cheaper due to more economies of scale and more competition for those items.
You can try to funnel more R&D into the sorts of things that the poor want than a free market would otherwise do. Most of the ways of doing this will cut into GDP somewhat, but maybe there are some public good type things that would out-preform the market, but where the benefits are difficult for one company to capture. A dollar spent on specific types of education, for example, may increase GDP by more than 1 dollar. However, since it can be difficult to capture a return on investment,^[1] we have a tragedy of the commons scenario, and government or some powerful entity has to step up and foot the bill for the common good, if we want things like that. (Note that I’m not sure that this is still true on the margin, just that if we cut all funding for education that the GDP would drop by more than the amount saved.)
No one
I was being a bit hyperbolic there, but you’ll note that I followed it with 2 examples of startups which might in the future actually be cheaper than what the poor currently use. (3D printing might remove labor costs from construction, and Soylent has aspirations of making food into a utility. I probably should have said so specifically.)
Walmart is a good point. I’m not sure whether the benefits from cheaper goods outweigh the cost to local jobs, but I’m sure we’ve both heard the complaints. That’s getting dangerously close to talking politics, so I’d prefer to avoid getting into details, but I’d be interested if anyone knows of any academic research or cost-benefit analyses.
Uber may be cheaper than taxis, and AirBnB may be cheaper than hotels, but the poor don’t use taxis or hotels. I am hopeful that self-driving cars will make transportation cheap enough that the poor benefit, though.
My point wasn’t that the poor aren’t any better off decade by decade. That appears to be false. My point is that they aren’t 5% better off each year, even though the economic growth rate is about maybe 7.5-ish-percent with maybe 2.5% inflation. So, most (but not all) of that growth is going into sectors which don’t benefit the poor much.
[1] Interestingly, this appears to be precisely what Signal Data Science’s business model is. They teach you in exchange for a fraction of your future salary. However, perhaps due to irrationality, there doesn’t seem to be a wider market for this sort of thing.
I’m not really sure how shortform stuff could be implemented either, but I have a suggestion on how it can be used: jokes!
Seriously. If you look at Scott’s writing, for example, one of the things which makes it so gripping is the liberal use of amusing phrasing, and mildly comedic exaggerations. Not the sort of thing that makes you actually laugh, but just the sort of thing that is mildly amusing. And, I believe he specifically recommended it in his blog post on writing advice. He didn’t phrase his reasoning quite like this, but I think of it as little bits of positive reinforcement to keep your system 1 happy while your system 2 does the analytic thinking stuff to digest the piece.
Now, obviously this could go overboard, since memetics dictates that short, likeable things will get upvoted faster than long, thoughtful things, outcompeting them. But, I don’t think we as a community are currently at risk of that, especially with the moderation techniques described in the OP.
And, I don’t mean random normal “guy walks into a bar” jokes. I mean the sort of thing that you see in the comments on old LW posts, or on Weird Sun Twitter. Jokes about Trolley Problems and Dust Specks and Newcomb-like problems and negative Utilitarians. “Should Pascal accept a mugging at all, if there’s even a tiny chance of another mugger with a better offer?” Or maybe “In the future, when we’re all mind-uploads, instead of arguing about the simulation argument we’ll worry about being mortals in base-level reality. Yes, we’d have lots of memories of altering the simulation, but puny biological brains are error-prone, and hallucinate things all the time.”
I think a lot of the reason social media is so addictive is the random dopamine injections. People could go to more targeted websites for more of the same humor, but those get old quickly. The random mix of serious info intertwined with joke memes provides novelty and works well together. The ideal for a more intellectual community should probably be more like 90-99% serious stuff, with enough fun stuff mixed in to avoid akrasia kicking in and pulling us toward a more concentrated source.
The implementation implications would be to present short-form stuff between long-form stuff, to break things up and give readers a quick break.