I’m going to provocatively call the first strategy mistake theory, and the second conflict theory.
I think that’s very confusing. The relevant distinctions are not in your essay at all—they’re about how much each side value’s the other side’s desires, and whether they think there IS significant difference in sum based on cooperation, and what kinds of repeated interactions are expected.
Your thesis is very biased toward mistake theory, and makes simply wrong assumptions about most of the conflicts that this applies to.
Indeed, the mistake theory strategy pushes the obviously good plan of making things better off for everyone.
No, mistake theorists push the obviously bad plan of letting the opposition control the narrative and destroy any value that might be left. The outgroup is evil, not negotiating in good faith, and it’s an error to give them an inch. Conflict theory is the correct one for this decision.
The reason I’m thinking about this is that I want a theory of non-zero-sum games involving counterfactual reasoning and superrationality. It’s not clear to me what superrational agents “should” do in general non-zero-sum games.
Wait, shouldn’t you want a decision theory (including non-zero-sum games) that maximizes your goals? It probably will include counterfactual reasoning, but may or may not touch on superrationality. In any case, social categorization of conflict is probably the wrong starting point.
Is this in reaction to something? I’ve seen some Zoom security hype, but nothing serious enough that it’s going to hurt them. What do you think will happen to them?
There are definitely alternatives to them, none as simple and cheap. Which answers the question of “why not”—there’s no profit in it. My prediction is that someone with a very sophisticated advertising and personal-data business model will have a product out soon that competes (or they’ll just buy Zoom). Facebook and Google would be front-runners for it.
In fact, apparently Facebook has launched group video chat in the last few days. Haven’t looked at it yet.
Note that supervision of complex knowledge work is _ALMOST_ as difficult in an office. There’re plenty of ways to slack off while physically present—watching netflix is out, but that’s not the risk. Reading Less Wrong all day looks like work, at first glance. And the solutions are the same. First,
the people who supervise the work are usually not programmers themselves
is simply a mistake. At least in the big tech companies I’ve looked at, managers were almost always engineers before they transitioned to the dark side. And there are 1-2 levels of management that bridge the evaluations from the line-level “able to evaluate daily work of programmers” to the senior management “able to evaluate a team’s business-impact output”.
Second, as long as you have SOME employees who are actively invested in the work, they’ll tell you who they want to work with and who they don’t, and why. This isn’t perfect, and some will lie or misinterpret things, but it’s enough of a pointer for managers to more actively look into.
Within normal constraints and timeframes, this is absolutely true—speculators are performing an important role in predicting and propagating demand. For short-term events which are ALREADY visible to suppliers (and somewhat less so to consumers) speculation has less information value, and more disruptive impact by their normal-value of shifting demand forward. In these situations, they shift a temporary demand into a much higher peak than it otherwise would be.
In other words, speculators are valuable usually, because usually they’re flattening the curve. They’re harmful in some exceptional circumstances because they cause the spike to be artificially higher than it otherwise would be.
Note that it’s NEVER this black and white. It’s certainly true that there are both benefits and harms to different constituencies in all cases, and where you net out will depend on what you’re focusing on.
Hard to separate government from cultural/behavioral issues—they reinforce each other. But variance in behaviors regionally (differences in how quickly governments signaled action and how well populations complied) seems likely to be a significant driver of variation of outcomes.
Wild guesses: 30% from different patterns of trade and interaction with the broader infected world, 25% from different social structures and living situations (types of corner store and shopping/entertainment mechanisms), 45% from behavioral differences and reaction time. I don’t think I can defend these guesses, and would be interested to hear other perspectives and missing causes of variation.
Note that we don’t actually know yet if NYC is all that much worse off than San Francisco. It looks that way currently, but a lot can change in a few weeks.
With noticeably different governance and social reactions in different locations, I wonder if this situation will spur migration in the coming few years. At what point is it worth moving to somewhere with more sane (still broken; nowhere is perfect) government and social behaviors, even if it’s more distant from your personal networks?
Seattle and the Bay Area are looking pretty good compared to New York and Florida (this could reverse over the next few months, but it’s unlikely that by end of year there’ll be no difference in terms how we evaluate their reactions and outcomes).
Similarly for urban vs more spread-out locations. Especially as many of us learn that we CAN be fairly productive anywhere there’s internet service, I wonder if more of us will opt to be around fewer strangers standing so close all the time.
I predict not much movement—people have a learned helplessness about governments, and easily forget that they have choices. And the advantages of cities remain powerful. And, importantly, most people don’t actually have quite as much future financial and social freedom as LW readers tend to.
It’ll be interesting to see if it takes some focus off of finance measures. I predict not, as that’s the aggregate lens that almost everyone in power looks through.
But the fundamental problem is that there is no actual measurement of human satisfaction, and financial productivity diverges hugely from anything we’d rationally want to optimize. GDP is paperclips.
To take a dirt-simple example, person A and person B are neighbors. Person A sells bread to person B for $10/week, and pays person B $10/week to mow their lawn. Gross Neighboorhood Product is $1040/year. Now something comes along to disrupt this, and each one has to mow their own lawn and bake their own bread. It takes longer, doing things they are less skilled at, but still gets done. But it’s an enormous financial loss—measured productivity goes to $0!
Employee focus (having punctuated behaviors separating work from personal time)
Tax advantages for employers to own workspaces and fixtures rather than employees
Not clear that “can be done remotely” is the right metric. We won’t know if “can be done as effectively (or more effectively) remotely” is true for some time.
I’d expect not. Overall, productivity is going down mostly because of upheaval and mismatch in supply chains and in efficient ways for labor to use capital. So return to well-situated capital and labor is up, but amount of capital and labor that is well-situated is down. Pure undifferentiated capital has a lower return, plus rising nominal prices means seeking returns is the main motivation, not avoiding risk.
TIPS seem like useful things to have in your portfolio, but rates are lagging quite a bit, so either the market disagrees with me, or the safety value is so high that people are willing to lose value over time. I think stocks will be OK—the last 40 years has seen a lot of financial and government backstops that mean we’re pretty good at protecting the rich on this front, and if you can’t beat ‘em, join ’em. Cash or the like is probably a mistake. I have no good model for Bitcoin or Gold, but my gut says they’ll find a way to lose value against consumer prices. Real Estate (especially where there’s not a large population-density premium) seems pretty sane.
Note: I am not a superforcaster, and have no special knowledge or ability in this area. I’m just pointing out mechanisms that could move things the other direction that the obvious.
Seattle-area groceries are mixed—some doing well at social distancing (have 6-foot spacers marked for a line outside, and letting in limited shoppers, with more going in only after some come out), some not so much, especially at peak times. Early morning (before 7) or late morning (after opening rush, before 11) seem quietest. Employees and shoppers about 30% likely to wipe down basket and cart between uses, about 20% surgical mask usage, haven’t seen a N95+ in a while. I feel pretty good with double-mask and nitrile gloves, and wiping down handles before use with a chlorine or alcohol wipe.
Driving is pretty safe, alone. It’s probably worth going by a few different stores to find the one you’re most comfortable with before going in. If you’re walking or using public transport, your options are more limited.
The best plan for your food stockpile is to replenish and use it. Keep 3-5 weeks, shop when you’re down to 3.5, buying up to 5.
The saddest part is how many students will miss it. Does Open University publish aggregate scores or details of pass/fail rates?
This probably gives the test author too much credit, but they MIGHT be trying to test whether a student can ignore the irrelevant details and just do the calculation.
Reference classes feel pretty hard to define
There’s the rub. And markets are anti-inductive, so even if we had good examples, we should expect this one to follow a different path.
Remember the impact of the 1957 Asian Flu (116K killed in the US, 1.1M worldwide) or the 1968 Hong Kong Flu (only a bit less)? Neither does anyone else. I do not want to be misinterpreted as “this is only the flu”—this is much more deadly and virulent. And likely more than twice as bad as those examples. But not 10x as bad, as long as we keep taking it seriously.
The changes in spending and productivity are very likely, IMO, to cause both price and monetary inflation. Costs will go up. People will have less stuff and the average lifestyle will likely be worse for a few years. but remember that stocks are priced in NOMINAL dollars, not inflation-adjusted. It’s quite believable that everything can slow down WHILE prices and stock values rise.
Mostly my comment was a response to the word “underrated” in the title. We wouldn’t know how it’s rated, because, by it’s nature, it’s going to be less proselytized. A quibble, to be sure, but “underrepresented” is probably more accurate.
Note that if someone assigns probabilities to these models, and conditional outcomes based on what they say publically, materialism is far more beneficial to express than solipsism, even if one finds solipsism more likely.
In the case where materialism and some form of causality is true, then you have some impact by publicly supporting it and pushing other people toward it. If instead, solipsism is true, and you push these hallucinations you call “other people” toward it, you get no benefit.
Much like other questions of free will and causality, as long as I assign some chance that it’s real and I have choices that matter, I should behave as if that’s certain. Even if I privately am not convinced, there’s no benefit to acting that way.
Stockpiling over time, long in advance of a crisis is great (but might be tough to find those investors). Supply has time to adjust and you are not hurting anyone.
Stockpiling in a burst just before a rush, when it’s too late for suppliers to adjust production, is much less clear. You’re accelerating or in some cases creating the shortage, and you’re not changing the short-term supply at all.
you’re not already a manufacturer
Sure, it’s common for a reseller to bundle support, installation services, or warranty with items, in order to justify very large markups. The discount methods work too. A packaging or product change is closer to the manufacturer case—you have to deal with time/cost/capital tradeoffs to change your production rate or inventory size.
As a pure speculator, you’re starting off in a worse spot, because you’re dependent on the manufacturer(s) for supply, and you’ll start with slimmer profit margins, which makes your risk much higher if the shortage doesn’t occur as severely as you expected, or if manufacturers can ramp up faster than you predicted.
You’re also in a morally worse spot—you run the risk that you are creating or amplifying the shortage, not just predicting and smoothing the consumption of rapidly-value-changing products, and not actually increasing supply with the increasing price. If you aren’t solving the problem given in the post (you could make more, but not at your normal prices), you’re not as clearly on the side of good.
Keep in mind that simple models are pretty misleading. There are almost NO manufacturers who aren’t also middlemen for parts of their equipment. They don’t dig up and smelt their own ore, they buy everything (often significant manufactured subcomponents) from other manufacturers. There are few distributors who aren’t adding real value with some amount of warranty/returnability, and delivery or quantity options that the manufacturer doesn’t support. These things really blur the line between producer and middleman.
The fundamental problem that businesses solve is that marginal cost is different from average cost (usually lower, in this case higher). One standard way to address it is price discrimination—find a way to get more willing customers to pay more, by bundling, by slight variation in quality for larger variation in price, or by other things that matter more to customers than to costs.
The obvious business advice for such a manufacturer would be to introduce a new line of premium ventilators, which are mostly the same, but have copper touch surfaces or something. Do this long before any hint of specific emergency—this is normal business practice. Price them at $100K normally, and you probably won’t sell many. Start ramping these up when you predict a surge, and these will be the ones you sell when you’re out of stock of the cheaper ones.
Oh, don’t forget discount policies—you should normally have a list price of $90K, and discount that to various levels based on negotiated delivery and volume commitment. You don’t have to offer discounts for last-minute purchases that weren’t contracted 6 months ago.
(all of these fall under the heading of “allow price gouging”. That’s the right answer for production-side incentives. It’s the WRONG answer for speculators who amplify the shortage by taking away from normal supply, rather than providing new supply. And it’s deucedly hard to tell the difference from outside, so governments tend to just outlaw the whole idea.
I think the trick you’re going for (and I agree with others that these are mostly tricks—fun for conversation, interesting puzzles among friends, but fairly poor for interviews) requires a further restriction than an arbitrary array of Java primitive ints.
This is too close to an answer, so I’ll further obscure it. I used rot-221 for extra secrecy!
I think they need to be contiguous, such that the range is the same as the array size. There is no sort better than O(NlogN) that needs to compare elements to each other.
Wait, you received evidence that didn’t just refute your hypothesis, it reversed it. If you accept that, shouldn’t you also reverse your proposed remedy? Shouldn’t you now argue _IN FAVOR_ of shutting down more completely—it saves lives both directly by limiting the spread of the virus AND indirectly by slowing the economy.
(note: this is intended to be semi-humorous—my base position is that the economic causes and effects are far too complex and distributed to really predict impact on that level, or to predict what policies might improve what outcomes).
I don’t think there are good general solutions to this question—it’s going to vary a lot based on the situation, participants, capabilities, and what they (think they) know of each other. If you want to go deep in your spare time, start with Von Neumann and Nash, work up to Schelling (it’s important to go that far, as you’ll need to include partial-knowledge and precommittment in your thinking). That’s fun reading regardless :)
A mixed strategy of sometimes shooting first, sometimes threatening, sometimes complying, sometimes just not reacting and pretending you’re asleep is probably where you’ll end up. Usually making yourself a worse target (in terms of risk/reward to your opponent) before the confrontation even starts is going to be right, but it’s non-obvious exactly what makes you worse—a sign that says “I’m armed” means “I have valuable guns to steal, and shoot me first so I can’t shoot you”. Solid doors and barred windows are good options to stop the problem before it starts.
In many locales, escalating “unreasonably” is a crime in itself. Also, you probably don’t know whether the looter is unarmed (for the same reasons you didn’t tell them you were armed), so conditional actions (threaten if unarmed, comply if armed) aren’t available to you.