Why Is Behavioral Economics So Popular?
nytimes.com
nytimes.com
Also, TED and TEDx for popularizing pseudo intellectual garbage.
https://www.vox.com/science-and-health/2018/9/19/17879102/br...
Over the long term, facts win out because facts tend not to change. People will moan and complain and twist and excuse and blame, but facts just don't give up being facts. Facts don't get tired or change their mind. It might take 10 years or a hundred or a thousand. Truth is patient like that.
Unfortunately, that doesn't really solve any problems in the short term before people start dying.
Pun intended?
For example - the legalised abortion and crime effect. I'm sure you can think of plenty more.
I think these stories are like crack to "rational" people. They have all the thrill of a good conspiracy theory, feel rebellious and anti-establishment, yet they're backed up by "real science". And you get to sound clever when you tell your friends about them. I know I'm a sucker for them.
I wonder what this is and why it is so prevalent (and maybe how it made our species/specific cultures successful).
You can list a large number of groups that wrap up their identity and value systems around being opposed to or having knowledge that counters their perception of "the majority". It is both incredibly attractive and a way to signal your value by going against the grain in some way or another, in some field or another.
Some philosopher/pyschologist/neurologist/evolutionary biologist could probably do a very compelling analysis about the human need to rebel or obey.
One of the societal ills of the 21st century is that we're running out of big clear cut things to rebel against but are continuing to rebel with the same intensity while directing it somewhat aimlessly all over the place, and now mostly just at each other's rebellion itself. Political parties in America these days are less anchored in particular issues and more about believing strongly in something your opponent is against and making sure your team wins.
Yeah but the key phrase is clear cut. We have plenty of big institutions and one can see them do terrible things. It's just they fade into each and so challenging a single one becomes a dubious interest. Health care is a mess but blaming say, insurance companies in particular, is problematic. The environment and global warming are huge problems but blaming single institutions misses the point, etc.
Moreover, large institutions are adept at harnessing issues-as-social-signal and directing them according to their interests. One can fight all this but such a fight doesn't follow the path of least resistance. And boy, are people trained, today, to follow that path, whether in rebellion or conformity.
For example, slavery up to 150 years ago vs. segregation up to 50 years ago vs. subtle often unconscious racism today.+ Fighting to abolish slavery is a lot simpler than fighting for racial equality. It is not that there are not problems, but there are not so many obvious problems with obvious solutions today.
+ I'm trying to make a broad point here not perfectly depict the history of racism in America, forgive any unjust implications
I think this attitude is the key problem: fuck blame. Seriously, who cares? There absolutely are concrete things we can do about healthcare and climate change and so on, but not if we collectively think that blaming this or that institution is going to motivate people to fix the problem.
Being contrarian in this manner is proof that you're smarter than everyone else, plus you get to take a jab at the pretend smarty-pantses. I bet this same effect is why political opinions are so difficult to change.
Or we're getting much better at the PR processes that muddy up any public discussion of problems and you lack the history education to know how rare actual clear cut historical political problems were.
Do you really think it is more likely that everyone else is virtue signaling than that you have a status quo bias from living in a culture that pushes that message (and I'm guessing you are quite successful as well?).
When has the majority been right about any complex issue anyway? What a bunch of reactionary anti-intellectual nonsense.
There was a "study" about drug testing welfare applicants in Florida a few years ago where the authors claimed that it only caught a handful of people and cost more than the money saved.
I looked up the numbers and found that applications took a historic plunge when the law went into effect, and an equally large increase after the law was suspended. It was a huge multi-stage funnel where the study only looked at one stage after thousands of applicants had already self-selected for drug-freeness. Applications went down by thousands, and payouts by millions.
Basically if you hired a data scientist who told you this about some funnel you were analyzing, like a purchase or sign-up flow, you would fire this person within five minutes. But people repeated this gotcha story everywhere.
I haven't been able to find monthly figures for before, during, and after -- so I, too, would like to see kwillet's data.
This is heavily slanted, but I believe their numbers are factual.
source on why this is shoddy science?
> It was a good test to attempt. But Messrs Foote and Goetz have inspected the authors' computer code and found the controls missing. In other words, Messrs Donohue and Levitt did not run the test they thought they had—an “inadvertent but serious computer programming error”, according to Messrs Foote and Goetz.
> Fixing that error reduces the effect of abortion on arrests by about half, using the original data, and two-thirds using updated numbers. But there is more. In their flawed test, Messrs Donohue and Levitt seek to explain arrest totals (eg, the 465 Alabamans of 18 years of age arrested for violent crime in 1989), not arrest rates per head (ie, 6.6 arrests per 100,000). This is unsatisfactory, because a smaller cohort will obviously commit fewer crimes in total. Messrs Foote and Goetz, by contrast, look at arrest rates, using passable population estimates based on data from the Census Bureau, and discover that the impact of abortion on arrest rates disappears entirely. “I am simply not convinced that there is a link between abortion and crime,” Mr Foote says.
>The effect of legalized abortion reported by Donohue and Levitt (2001) is largely unaffected, so that abortion accounts for a 29% decline in violent crime (elasticity 0.23), and similar declines in murder and property crime. Overall, the phase-out of lead and the legalization of abortion appear to have been responsible for significant reductions in violent crime rates."
According to your link it doesn't appear to be shobby science.
The rebuttal to the Foote and Goetz criticism of a programming error is this:
> Donohue and Levitt subsequently published a response to the Foote and Goetz paper.[12] The response acknowledged the mistake, but showed that with different methodology, the effect of legalized abortion on crime rates still existed.
That's troubling to me. They had a hypothesis, and when the experiment didn't confirm that hypothesis, they simply tried a different methodology that might still show it. That feels like moving the goalposts to me.
It's also representative of the negative feeling I had all the time when reading their book: after all their praise of rigorous scientific methods and of not confusing correlation with causation, they follow that up with making those same mistakes themselves. (And I guess the reason that rubbed me wrong is because that is interjected with continuous praise all the time of Levitt. That in turn probably makes me more likely to criticise, so perhaps you should take my criticism with a grain of salt...)
Also, I think it's important to note that these stories are not actually anti-establishment, even if they have such an appearance; they don't offend any powerful interests. In fact, they're often quite the opposite (consider that Malcolm Gladwell wrote an entire book arguing that being disabled or growing up poor or whatever else is actually an advantage! The people most likely to take exception to that thesis do not have bylines in the New York Times, nor do they have the editor's personal phone number)
Basically, being "rebellious, anti-establishment" means denying/rejecting everything about how the society works and searching for an alternative. Being "smart" means understanding exactly how the society actually works instead of how it's "claimed" to work under propaganda and falsehoods, and maybe using the mechanism to your advantage as much as possible. They are very, very different things.
Once they burned through those folks, they turned to cranks/homeopaths/etc
Until I started seeing stuff like this https://www.youtube.com/watch?v=w8J5BWL8oJY
TED talks were never the best source of information, but at least they weren't actively misleading.
ted-X on the other hand.....
https://www.youtube.com/watch?v=_ZBKX-6Gz6A
Though from a public speaking point of view, it's well worth studying (both actual TED talks and this satire) to help make legitimate talks more polished. There's an exchange of emotions that goes on during great talks, and that really helps drive home points.
Once these talks became more about the delivery style than actual substance, it kinda devalued the whole TED branding.
Biases are are not always errors. They can be cognitive shortcuts and optimizations that may be reasonable heuristic.
There Is More to Behavioral Economics Than Biases and Fallacies http://behavioralscientist.org/there-is-more-to-behavioral-s...
> A widespread misconception is that biases explain or even produce behavior. They don’t—they describe behavior. The endowment effect does not cause people to demand more for a mug they received than a mug-less counterpart is prepared to pay for one. It is not because of the sunk cost fallacy that we hang on to a course of action we’ve invested a lot in already. Biases, fallacies, and so on are no more than labels for a particular type of observed behavior, often in a peculiar context, that contradicts traditional economics’ simplified view of behavior.
>The conversation around biases is almost uniformly negative: they screw up our decision making, or undermine our health, wealth, and happiness. However, biases evolved with us, and for good reasons...
It's first and foremost a heuristic -- a reasonably good way to generate good behavior. Secondarily, in certain specific situations, it causes non-optimal behavior.
[1] ( https://www.amazon.com/Heuristics-Biases-Psychology-Intuitiv... )
A critic of the work of Daniel Kahneman and Amos Tversky, Gigerenzer argues that heuristics should not lead us to conceive of human thinking as riddled with irrational cognitive biases, but rather to conceive rationality as an adaptive tool that is not identical to the rules of formal logic or the probability calculus. He and his collaborators have theoretically and experimentally shown that many so-called cognitive fallacies are better understood as adaptive responses to a world of uncertainty—such as the conjunction fallacy, the base rate fallacy, and overconfidence.[4]
https://en.wikipedia.org/wiki/Gerd_Gigerenzer
His books are well worth a read.
Nassim Taleb also has a similar criticism in that he says that Kahneman and Tversky essentially said that humans don't act according to theoretical rules but instead have their own heuristics that have been derived from dealing with an uncertain world throughout history:
https://twitter.com/nntaleb/status/883689826335281153?lang=e...
For the large majority of our history, we've not been rational in the least. HN had a good discussion [0] on the Medieval Mindset [1] earlier in the summer. For ~1000 years in the Medieval period, the main mindsets were not rationality vs. irrationality, right vs. less-wrong vs. wrong, etc. But more Pious vs Impious, Cruel vs Kind, The Ideal vs the Real, etc. The people were no less people, but their heads weren't ours.
What economic theories will come next, what new ways of thinking, what new mindsets? We're so focused on the rational, the 'right' answers, these days. But life, as we all know, is VERY stochastic ( a fancy word for random ). Maybe new mindsets about the randomness, bounded and given standards of deviation, will be a new paradigm, not just in economics, but in everything we do.
[0] https://news.ycombinator.com/item?id=17058487
[1] https://coinsandscrolls.blogspot.com/2017/09/thinking-mediev...
Why do people say this. This was never true. The Wealth of Nations is basically a compendium on human behavior, and that was 200 years ago.
For instance, the priming experiments cannot be reproduced.
> This result confirms Kahneman’s prediction that priming research is a train wreck and readers of his book “Thinking Fast and Slow” should not consider the presented studies as scientific evidence that subtle cues in their environment can have strong effects on their behavior outside their awareness.
https://replicationindex.wordpress.com/2017/02/02/reconstruc...
Like you mention the replication crisis should be really leaving most of all psychology results, not only past but also present, in serious doubt -- let alone anything contingent on those past results. But again the problem is that when new research comes out that confirms our biases, we don't expend the energy to challenge it.
And it seems that many in science are more concerned with themselves than their science - something that the replication crisis provides a great deal of evidence for. People aren't putting out trash science by accident. They need to publish, and trash science is what gets published. And the replication crisis hasn't changed this. There seems to have been, at best, token efforts to try to more fully ensure the truthfulness of what's being published. So we continue to believe what we want to believe, with science increasingly falling victim to the act of starting at a conclusion and working your way backwards.
Combine that with non-reporting of negative results and you basically have a huge pile of bullshit.
For example: You have a drug that 100% helps in a certain context (of what the problem is and the person's genetics plus maybe even epigenetics, and maybe even things like what they eat and what environment they are exposed to).
However, clinical trial studies don't go very deep in separating different kinds of people. We just don't know enough, we don't know how to even measure most thing, and when we do it's extremely costly. And since we don't understand the mechanism - if we did we didn't have to go through the trials - they are needed because even we have _a_ mechanism we are not sure what else the drug does in the body, or about follow-up and higher order effects - we would not know what to look for anyway. Plus, without full understanding of the mechanism it's hard to combine the new "knowledge" with other knowledge. The experiment you gained the data from is very specific and results are hard to generalize.
So the result is the drug will be a complete failure, because we are unable to tell which people would benefit.
That's always the problem: When you don't have a very good understanding of the mechanism and all the consequences you have to be lucky that the population you study is more or less the correct one. You don't even know when you got the wrong one. If the drug - but same in any other field that uses statistics - fails for 95% of people you may still have a hit for a sub-population (it's not as easy as "it's the other 5%" of course).
There are people working specifically on looking closer at some "failed drugs". They have been able to find a few "miracle drugs" that way. They only help certain people (they use genetic testing) but when they do they do great. But they failed their initial clinical trials big time.
Over the years I have gotten much more skeptical of all statistics based "knowledge". Reading those studies always leaves a strange taste in my mouth. Something doesn't feel right. It does not taste like knowledge. I see the relevance given that it often is the only way to make practical progress of course.
Good point, but this kind of subgroup analysis also runs into the multiple comparisons problem. If you test all kinds of subgroups (or just do a lot of any kind of tests), chances are good that you will run into false positives. In such scenarios, it becomes more probable than not that a given positive result is in fact false. Combine that with the base-rate fallacy (the good majority of drug trials yield null results, but this is not taken into account) and you are in really bad shape.
There was a replication study a while ago that tried to replicate IIRC 50 or so "landmark" cancer studies, and only came up with significant results in 6 cases.
Bayesian methods go a long way towards solving these issues, but there is no cure for low-power studies. They just can't tell you much, and will lead you heavily astray if you don't properly account for multiple comparisons, etc.
>Over the years I have gotten much more skeptical of all statistics based "knowledge". Reading those studies always leaves a strange taste in my mouth. Something doesn't feel right. It does not taste like knowledge. I see the relevance given that it often is the only way to make practical progress of course.
Clinical studies of new drugs have uncertainty. Thus any decision-making based on results must take this uncertainty into account. You can't get away from statistics here. The bad feeling in your mouth may be from the unintuitive and usually inappropriate use of P-values and null-hypothesis statistical tests. The vast majority of researchers are actually completely mistaken on what P-values even mean. Most think that they are "the chance of a false positive" or something similar, which is completely wrong.
Bayesian methods help here, because they are the only valid way of combining past information with new information.
As I said, the issue is statistics based "knowledge". What you just said just continues down that path, so of course it does not solve the problem, actually makes it worse because now we throw more randomness at randomness and get random matches - but still not one bit more understanding.
You can't get away from statistics. You can only replace bad statistics with good. If you ignore these statistical aspects of an experiment such as multiple comparisons, then your reasoning is even worse!
You can't just "decide" to not use "statistics based knowledge" any more than you can decide that your experiment is not subject to uncertainty or error. You could say that, but that doesn't make it true.
Bayesian statistics are much more intuitive, however. Baye's theorem is actually the generalization of contrapositivity (If A implies B, then not A implies not B) to situations where we are not certain of A and B.
You seem to be saying that nothing is gained with statistics knowledge, and attempting to use better statistics is just throwing "randomness upon randomness." If this isn't true, then you are being unclear. All of your criticisms about statistics are very vague, and do not cite any specific problems.
I gain understanding from "statistics-based knowledge." If you do not, then that is a problem you should solve by reading more about these issues.
Bernays comes up a lot in counter-cultural circles, but it's always bugged me that I've never seen any validating evidence that his techniques were actually effective, beyond "he came up with the idea of 'freedom torches' and smoking went up among women."
His techniques sound interesting, and they feel like they'd be effective, but I had trouble finding any solid research that validated the idea that his techniques were effective at anything other than making himself famous.
(* Don't get me wrong – I love Curtis's films, as art. But it bugs me how they usually present a flood of information presented as fact, with little to know citation or corroboration. If they were just art, it wouldn't bug me, but a lot of people seem to swallow the films' conclusions wholesale.)
It’s not limited to marketing either, management theory is full of this too.
Almost all of Frederick Winslow Taylor’s work and reputation was built on unverified case studies and anecdotes. (A great book on this is ‘The management myth’.)
So really over-simplify: "If you want people to do X, don't just tell them to do X or order them or try to convince them, use psychology to understand which Y's and Z's you can tell them about that will statistically lead many people to do X".
He was just the guy who said "Hey, this emerging scientific field can be really useful in manipulating people even though it is early days!"
So with the benefit of hindsight, yes, he presented faulty research - but he didn't (and couldn't) have known it at the time.
(Of course, if the lesson is that the entire field should be considered skeptically, I don't think I'd disagree)
People acted like I was insane.
> I still believe that actions can be primed, sometimes even by stimuli of which the person is unaware. There is adequate evidence for all the building blocks: semantic priming, significant processing of stimuli that are not consciously perceived, and ideo-motor activation. I see no reason to draw a sharp line between the priming of thoughts and the priming of actions. A case can therefore be made for priming on this indirect evidence. But I have changed my views about the size of behavioral priming effects – they cannot be as large and as robust as my chapter suggested.
(Discussed on HN: https://news.ycombinator.com/item?id=15228712)
Of course marketing schemes for "act now or lose out" won't work. I don't currently experience the opportunity and therefore losing out exerts no power over me. However, losing a mug when I already own the mug would demand a higher price from me. I would agree with Dr. Thaler that the inertia thing is a minor point about terminology.
Call it loss aversion or call it inertia. Marketing schemes that include the word "loss" in their pitch are not using the same strategy that behavioral economists are talking about here.
Prior to being introduced to behavioral economics my exposure to economics was very quantitative, while this model is necessary it's incomplete. A lot of economics seems to assume that the actors are equally rational beings but in the real world that's just not the case. Behavioral economics seems to bring actual human experience into economics.
This is a huge misconception. Economics doesn't assume that actors are perfectly rational actors, any more than physics assumes that interactions always take place inside a frictionless vacuum. It's just one model that's used as a starting point to understand mechanical interactions.
Physics does this all the time, too. You can, indeed must, be wrong about all the microscopic details... but despite that, you can often get the correct macroscopic model.
The unfortunate part is that most models in economics have lousy predictive power.
At the undergrad level, it often does. I had a friend who had just become an assistant professor in economics. He was teaching an undergrad class, and wanted to pose a few scenarios to them. While preparing his lecture notes, he called me up and gave me the scenarios and asked how I would behave. These were not "hard" or "wild" scenarios. Mostly day to day stuff.
I gave my answers. On several of them, he told me I was giving irrational answers. This was a problem for him, because if his students answered likewise, they wouldn't support the points he was trying to make in the lecture.
He and I had a similar outlook on life. So I asked him: "Would you behave differently from me?"
Him: "No"
Me: "So what is the value of the economic model you're teaching if even you would not behave the way the theory indicates you would?"
As an aside, and this always comes up when we talk about rationality and economics. The disconnect is often that basic economics courses have a narrow view of people's motives and desires. It is often simplified to "optimizing for money" or "optimizing for time". Rarely things like "optimizing for mental stress". Pretty much everything someone does is for some perceived gain. That gain is often not what economists teach it is.
Even introductory economics classes don't do this. One anecdote about a friend of yours who's an inexperienced instructor notwithstanding, if you look at any of the most widely-used and reputed introductory textbooks for undergraduates, you'll see discussion of rationality and the ways in which those assumptions can be relaxed.
Just as people study Newtonian mechanics under idealized circumstances before they learn about friction and Van der Waals forces, people learn about the outcomes of rational behavior first, but it's ludicrous to judge an entire field by an outsider's perception of the topics covered during the first few weeks of an introductory course.
Most of the time GPS offers an optimized shortest fastest way to reach a destination. Yet, often I may prefer a familiar route, or an 'easy' one (e.g long straight runs), or a 'scenic' ('cause it's that time of year) or some other irrational choice.
Then would just absorb any resulting inefficiency as a fact of life (chalk it up in Debit column, if at all).
So ultimately it's kind of optimizing for personal satisfaction (at the moment). Sticking to a rational discipline does bring satisfaction too.
None of those is an irrational choice.
But to an external observer (say, who's going to the same destination) such choice does not follow common reasoning (arriving at the shortest).
Gains of such choice are intangible (indeed personal satisfaction is subjective). At the same time, the 'loss' is very specific and measureable (extra time, fuel etc.)
Thus in the context of a common measure such choice could be seen as irrational, especially when a rationally optimized choice is equally available.
Even when models in economics don't assume rational behaviour, they tend to lean pretty heavily on assumptions of optimising behaviour - which, for me, isn't much more convincing.
Richard Thaler's Misbehaving is a good read on how this developed. I had Thaler as a professor for a couple of classes in the early 80s and I found some of the insights from early-on behavioral economics some of the more useful things I learned in my MBA.
Probably because people got sick of a guy with a formulae lecturing them about how human's aught behave as opposed to developing functional models of how humans do behave
https://en.wikipedia.org/wiki/Ultimatum_game
The Nash Equilibrium of this game is to offer the other person $0...unless you incorporate the idea that humans may care about more than pure monetary payoffs in their mental gymnastics.
Kinda like when that friend from undergrad studying business told you that paying anything more your minimum tax bill was 'irrational'
I'm an Economics PhD and former professor and most of the research isn't taken very seriously. Everyone acknowledges that people don't behave "rationally", but no one yet has been able to figure out how to build these behavioral assumptions into a working model that is actionable.
To improve predictability or to better the management of resources in human societies?
Indirectly, it's a question about the optimization goal that the mainstream models are trying to achieve.
Now we just need a revolution in economics comparable to the cognitive psychology movement that got that field beyond Skinnerian behaviorism.
and in the article: "It reflects the widespread perception that behavioral economics combines the cleverness and fun of pop psychology with the rigor and relevance of economics."
The author is using behavioral economics to argue against behavioral economics.
The main purpose seems to be to crap on Thaler for dismissing his critique of loss aversion instead of embracing his hypothesis on the buy-side. This neither discredits behavioral economics, nor makes a clear case for how academe related to marketing would better humanity or its understanding.
Most of behavioral economy is not seriously tested, because the endpoint is not "tricking the mouse" but positioning yourself as a trickster educator, a place that cannot be blamed.
One of classic cons.
Many of the popularly-cited experiments both in behavioral economics and in psychology involve misleading or deceiving the experimental subjects, and many more simply conceal their objectives. The assumption that the suckers never caught on and the results should be interpreted accordingly is seldom questioned. In some cases, the assumption is verified by asking the subjects about their motivations post-mortem, ignoring the long-standing axiom of applied behavioral economics (business) that there are two reasons anyone does anything, the one they will tell you and the real one.
The null hypotheses in these experiments ought to be (1) the subjects know or can figure out what the experimenters are looking for, and (2) the subjects are there because they want to help the experimenters.
Consider the subject who is paid a small sum to participate and interacts with a either a researcher who must publish or perish or one who will put another batch of subjects through a similar rigmarole next year if they cannot get their dissertation accepted this year. What does motivational psychology say about the behavior of such a subject? Is such a search for truth better than a congressional committee?
That is...actually, a good point, and exactly describes something I'd noticed.
One of the problems with economics is the assumption of the "perfectly rational actor", which sometimes leads to economic's descriptive vs. prescriptive issue: someone will create a massively complicated scheme that maximizes some positive value under a certain set of assumptions and then assume that people actually behave like that.
Some of what I've read, including by Richard Thaler, who I otherwise rather like, buys into that scenario, saying "no, this is what they do; they behave irrationally". Sure, people aren't by any means perfectly rational, but it's not irrational to not perform a complicated maneuver that's only useful in a specific, odd, circumstance.
There's another interesting bit from the article:
"[In the class mug experiment showing "loss aversion,"] the participants may not have had a clearly defined idea of what the mug was worth to them. If that was the case, there was a range of prices for the mug ($4 to $6) that left the participants disinclined to either buy or sell it, and therefore mug owners and non-owners maintained the status quo out of inertia. Only a relatively high price ($7 and up) offered a meaningful incentive for an owner to bother parting with the mug; correspondingly, only a relatively low price ($3 or below) offered a meaningful incentive for a non-owner to bother acquiring the mug.
"In experiments of our own, we were able to tease apart these two alternatives, and we found that the evidence was more consistent with the “inertia” explanation. Dr. Thaler has dismissed our argument as a “minor point about terminology,” since the deviant behaviors attributed to loss aversion occur regardless of the cause. But a different account for why a behavior occurs is not a minor terminological difference; it is a major explanatory difference. Only if we understand why a behavior occurs can we create generalizable knowledge, the goal of science."
"The deviant behaviors attributed to loss aversion?" Not only is there nothing deviant about the behavior, it's not in any sense "loss aversion". In fact, it's perfectly rational, given limited rationality resources, not to engage the whole engine in an otherwise minor scenario.
>In this respect, behavioural economics can be thought of as endorsing the outsize benefits of psychological “tricks,”...
But it also covers bubbles and crashes which have major effects in the billions/trillons financially and with millions having their jobs and housing effected. It would seem sensible to take that stuff seriously.
In the book, Thaler describes nudges such as placing the fresh fruit in the school lunch line in a more easily reachable location than the junk food. The idea is that kids will be more inclined to choose a piece of fresh fruit if it's in easy reach but the chocolate bar requires bending down, etc.
While such nudges may sometimes be measurably effective, we must also realize that the idea of socially beneficial nudges evokes a sort of utopian paternalism.
The idea behind Nudge paints the picture that there is a light-weight, unobtrusive version of central planning (or central nudging) that can achieve some of the utopian outcomes that planners wish for, but which is less encroaching upon individual freedom.
At what point do situational nudges start to feel like social nudges? What if the chubby kid who wants the chocolate has to humiliate himself by reaching far overhead and fishing around blindly in an out-of-reach bin to find the chocolate while everyone else waits impatiently?
When does spending hours to opt out of helpful services become an inappropriate encumberment?
Google just launched sentence completion in gmail. Combine this with nudges and fuck you won't be corrected to duck you, the typist will see an autocompleted hey I'm feeling really frustrated about what you said right now ready to accept with the tap of a single button.
Nudges are meant as a mechanism of social control. Gal points out wisely that if we rush to judgment about the why of behaviors, then our behavioral economic remedies (nudges, etc.) might be terribly wrongheaded.
> All of them continue to do great object-level work in their respective fields, but it seems like the “moment” for books about rationality came and passed around 2010. Maybe it’s because the relevant science has slowed down – who is doing Kahneman-level work anymore? Maybe it’s because people spent about eight years seeing if knowing about cognitive biases made them more successful at anything, noticed it didn’t, and stopped caring.
[1] http://slatestarcodex.com/2018/09/19/book-review-the-black-s...
I'm aware that doesn't mean it's correct per se, in a hard-science sense, but it does help popularizing the field when every person who reads Predictably Irrational recommends it to other people
A key element of the rational actor model is that there is no way to know anyone else's preferences aside from observing the choices they make. Even asking them directly is not considered an authoritative source, since preferences can change at any time and people don't always know just what they would choose until they're actually confronted with the choice.