It's unfortunate that these questions are being dodged. Do we actually have control over the feedback mechanisms, or will they find ways to assert themselves despite our attempts to control them? Which distribution is more "fair" than a Pareto distribution, and why? These are good questions, and it's disappointing we aren't facing them head-on.
It's actually not Pareto's but more like "Normal Distribution" and that is something embedded in Nature/Society that one can't change or eradicate. It's just the way things work, the natural dynamics.
Well, I personally haven't consented to socializing the cost of anything. I'm not sure what the ethical grounds are for imposing this on me, and in so doing dilluting available accuracy of data about people.
These feedback loops you're referring to, what order are you proposing for your chicken and your egg? What's causing what in your view?
A lot of real world cases have imbalanced reward functions. Autonomous vehicles are another example. I don’t doubt regulation systems on spacecraft are similar.
The authors' point seems to be "if you ask people questions whose real answers correspond to informal statistical judgments, then they will give the right answers."
This isn't really that informative, but the strongest form of this argument is "informal statistics is better in a lot of real-world cases." This sounds to me quite a bit like the case the behavioral economists make -- that these intuitions aren't crazy, or stupid, but they do exist. They were constructing tests specifically to isolate them, and succeeded.
A further point is that these kinds of situations when intuitions are challenged happen regularly. I don't know what behavioral economics says specifically about causes, but it seems to me they take a fairly neutral view: such situations can occur by chance, due to hostile intent, or by mistake. Whether the outcome is positive or negative depends as well. The point of "nudge policy" (opposition to which seems to be the main point of the article) is to see about making these situations positive -- that is, arranging the world through policy such that making intuitive considerations actually yields positive outcomes. I don't think the authors' argue successfully for the point that since everyone is rationale and no-one ever gambles when presented with the opportunity, that therefore arranging policy such that intuitive choices yield positive outcomes is unwarranted interference.
I'm not sure if I would call the system actively irrational. It's extremely well-measured, as scientists are good at measuring things.
The academic job market is hyper-efficient and gets close to a Pareto distribution very quickly. I agree that economics programs don't do a good enough job teaching about the implications of systems which distribute outcomes according to a Pareto distribution (which are many).
Right observation, wrong conclusion. I would conclude that the pareto principle is just a force of nature and it always yields it's ugly head no matter the effort to beat it down
Also robustness costs, -- many heuristics that get poked at by champions of behavioral economics are behaviors that tend to give improved results when reasoning with noisy inputs (and, in particular, inputs with unknown levels of noise or even malicious distortions) compared to a formal decision theory that doesn't handle low quality inputs well.
These limitations are only a concern when people attempt to suggest that behavioral economics is telling us to rework how we live our lives. Generally such claims are unjustified extrapolations from very basic studies which in no way support the pop-economics advice. Like if someone did some experiments and determined that submersing people in water often killed the test subjects, then other people ran to the presses recommending that no one drink anymore because water was proven to kill in scientific studies... :)
It was apparently worth a prize to explain more rigorously why behaviors often deviate from an underlying assumption of maximizing expected value. And, yes, some of the economics community was quite resistant to the idea that the answer was anything more than people are stupid. (That may be a bit of an exaggeration but there was quite a bit of resistance in economics to behavioral economics being a field of serious inquiry.)
While I love reading about insights from behavioral economics I don't completely understand the internet obsession over psychological biases, mental models and other related topics in this cluster.
I'm often trying to understand how to actually apply this kind of knowledge into my daily life. I think Kahneman has himself said you can't protect yourself from it even if you are aware of the biases.
A lot of the interest in these topics seems disproportionate relative to their applicability.
Also they claim the body of evidence doesn’t find support for loss aversion. But a meta analysis on the topic does in fact find support for loss aversion (albeit the magnitude is probably smaller than originally thought):
- people enthusiastically lining up to get the latest sneaker / iPhone.
- mildly enthusiastic grocery shopping.
- overpriced medical drugs due to a monopoly.
- taxation.
- outright theft at gunpoint
2. Insightful, thanks. I think one variable the model doesn’t account for is time (which is not multiplicative and scarce).
Money and power can be multiplicative so maybe most of us are playing the non-multiplicative game of spending our time to make money, while the rich are leveraged time to play multiplicative games where they spend money to make more money and happened to win a bunch of times.
Yes, I am deeply pessimistic about human nature. When weaker men at the lower levels of companies see what happens to strong men at the top, what is the likely outcome? What would natural reinforcement learning tell them on how to maximize their reward/minimize their penalty, given their very limited options?
(Going meta for a second: I'm sorry this took me so long to notice, but I think this might have become a political discussion. I had believed we were principally discussing mathematical fairness as it applies to markets, with maybe some colorful/relaxed examples to keep thing interesting, but that the examples were all relating back to mathematical fairness. Sorry for being dense :/)
> This is not by any means a dismissal, as it provides valuable insight into the behavior of human society, but viewing it as the beginning and end of economics will place massive limitations on any analysis.
My personal interest in economics has roughly nothing to do with understanding human behavior -- I'm interested in incentive structures/mechanism design, mathematical fairness, agency, decision theory, optimal play, optimally exploitative play, cooperation/coordination/defection in partial information games, etc. This is to say that, for me, economics becomes uninteresting as soon as you worry if human behavior matches the model. Econs are so much cooler than humans! It's much more fun to ask what they would do, and what can be done to improve their outcomes.
Yes, I am familiar, especially as it relates to faulty decision making in professional life (base rate neglect, availability bias, etc). I don't think he's considered to be part of the field, but I've also found George Polya's How to Solve it to be related here. He explicitly discusses heuristic search for math proofs, and how this can amount to a blind spot.
> It is a simple conclusion that follows from three premises
(This was what made me realize what had happened). My disagreement is with respect to the question of "can a fair game be created within an unfair game, even in a context where you can't correct historical unfairness?" -- to that I say yes (with my earlier caveats about physical limits of fairness in our world).
Perhaps now that I've explained more about my background and perspective, you can consider this thread (https://news.ycombinator.com/item?id=13442034) again from the perspective of "Will capitalism survive the robot revolution?" -- the econs I love will (I hope/expect) finally be a reasonable model of economic behavior. Therefore I hope capitalism will survive, since that would ensure I got to live in a good/fair world. If you are aware of some way in which a capitalist system, when populated by robots/econs, could be improved with respect to fairness, I'm skeptical but quite interested.
Re: the political question you asked. If there were a way to say for sure if wealth was unearned I'd absolutely support confiscating it, if not I'm skittish and afraid of causing more harm than good.
I think the issue is with reward signals. Monotonic reward signals like the ones from normal employment are not anywhere like the ones we received as hunters and gatherers in the wild.
Starting your own business, like I have, is one way to get back to the possibility of variable reward signals. But it's terrifying and you basically can't have a family in the US because of healthcare. Then there's also the possibility of 0 reward signals with seemingly undecipherable error signals. It also isn't anywhere near the same distribution.
Economics is hard. Behavioral economics is having a hard time right now with many of the core hypothesis (loss aversion) and key interventions (priming) turning out to be experimentally not-reproducible.
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