You are intentionally being uncharitable, and in your rush, you ignored the first two words of my statement. I'm glad large tech monopolies got yet another giveaway from our congress, and if that's a flag you want to wave, be my guest; but, I still stand by my assertion.
It's extremely odd to characterize all modern management as Taylorism from the outset. The post seems to be flogging a strawperson argument and concluding with a summary of what I think is a fairly broad consensus about what modern management of knowledge workers actually looks like: finding competent people, setting rich context and providing frequent and actionable feedback.
The way this is phrased, I expected to learn there was some benefit to a low amount of fraud, as such. There is not. There is a benefit to a high amount of trust, which necessitates accepting some amount of fraud.
The optimal amount of crime in a society is non-zero because a society with zero crime would be a dystopian police state where innocent people sometimes get caught up in the justice system's net to make sure it catches all of the criminals.
The classic principle of Anglosphere common law is that its better to let 10 criminals get away with it than to convict 1 innocent person. The same idea applies to fraud because overzealous fraud prevention causes problems for legitimate users whose actions incorrectly get detected as possible fraud. The benefit to tolerating a low amount of fraud is that your product won't be hostile to your legitimate users. The benefit to tolerating a low amount of crime is that you will live in a free society rather than a dystopian tyranny. Freedom is good and it is worth giving up quite a bit of safety for the sake of being free.
I said this somewhere else, but there’s 2 things at play here:
- A utopia where people don’t defect in prisoners dilemmas (most types of crimes like shoplifting: the store won’t have to hire loss prevention and cashiers, and you pay less for their reduced costs) is ideal, but:
- Such a utopia doesn’t and can’t exist because defection individually increases utility at the cost of everybody else. Hence cashiers, loss prevention, KYC, etc.
Thus the real world is a careful optimisation problem where we have to search for an equilibrium at which society as a whole benefits the most. People can argue all day about where this is, because the trade offs involved are non-obvious:
- More surveillance means, all else being equal, less crime, but police officers can defect too and only arrest minorities and use said surveillance for something else, etc.
The problem is walking through a very high-dimensional search space, and we humans are had at it. There’s no real solution though, because individual incentives don’t line up to solve it.
I’d argue that the optimal amount of crime is zero but the optimal amount of possibility of crime should be non-zero. That’s a necessary escape hatch out of a police state or authoritarian government. After all, the resistance against the Nazis was technically criminal at that time, even though now we’d all agree it was a good thing it occurred anyway.
It is especially important nowadays because unlike back then where technology was limited and surveilling 100% of the population was impossible, it is very much possible today and is already being done in certain places such as China.
Does he mention this somewhere? Last time I spoke to him, he was working on Stripe Press, his interest in fraud and spam prevention long predates his work at Stripe.
If you define crime as violating the anarchist non-aggression principle, then it makes more sense. The only problem is that the state would be the largest offender.
Nazi laws weren't moral, as it's not moral today to demand half of my profits or I go to jail.
You just picked your own idea of morality and decided to elevate it above others: you chose the "anarchist non-aggression principle" as somehow morally superior to other ideas about how crimes should be defined, and decided that with that definition, targeting zero crimes makes more sense.
But the whole point is that we will never universally agree on a morality because society's overall preferences shift over time. So targeting zero crimes never makes sense.
> ts better to let 10 criminals get away with it than to convict 1 innocent person.
is arguably false. it forgets that 10 criminals had 10 or more victims. If you optimize for the least number of victims then it's easily possible that convicting a few innocent people has a net positive in lowering the total number of victims including the victims of being wrongly convicted
to put it another way, perfect is the enemy of good. In this case if in pursuit of perfection of having zero wrongly convicted you end up causing more victims of criminals then you've arguably failed
I also believe that it’s better to let 10 criminals get away with it than it is to wrongly convict 1 innocent person. And I’m fairly sure that all the innocent people who were unfortunate enough to go through the court system would agree with me.
Also, not every crime must have a victim. There are a million victimless crimes.
Yes, it’s also debatable whether those should even be crimes (in my opinion - no), but the argument that 1 crime = at least 1 victim is flat out false.
also you too made the exact same error. you discounted the victims of the criminals. yes the 1 innocent wrongly convicted is bad but what about all the innocents that are victims of the criminals. You absolutely have to add those innocents to your total of how many innocents you helped
if you catch 10 serial killers and 1 happens to be innocent you still saved 9-18-27 lives in exchange for one innocent. If because of over zealousness of zero innocents being caught you only catch 5 serial killers you saved 1 extra life and forfeited 5 to 15 others
You arguably believe what I'm saying. no law enforcement can be perfect so it's guaranteed that innocent people will be mistakenly convicted. The only logical conclusion is if you truly believe there must be zero innocents convicted then you believe law enforcement should not exist since there will never be perfect law enforcement
it doesn't forget that. it implies that you shouldn't optimize for the least number of victims. it's cool to disagree with that and think about why or why not, but please actually engage with the idea rather than just assuming they didn't think it through at all.
> The optimal amount of crime in a society is non-zero because a society with zero crime would be a dystopian police state where innocent people sometimes get caught up in the justice system's net to make sure it catches all of the criminals.
At this point you're just playing with the definition of crime. I would argue that it is criminal to deprive an innocent person of their freedom, and challenge that your proposed scenario is actually "zero crime".
Secondly, you talk of catching "all of the criminals". In a "zero crime" environment there are no criminals - by definition if there is a criminal, then a crime has been committed at some point.
All that said I agree with your larger point - the cost of freedom is that people are not constrained before the fact from committing crime, and that's a good thing on the whole.
We don’t need there to be a benefit to a low amount of fraud to optimize for it. Optimization is a purely mathematical exercise [1]. Once we construct the problem with a chosen set of constraints then we apply mathematical techniques to solve it. Of course, many types of optimization problems (especially non-linear or non-convex) can be extremely difficult to solve optimally without relaxing some constraints or settling for approximations to the optimal solution.
But, besides that, the task of interpreting the results and of potentially selecting new constraints or even a new objective function is a separate matter. Perhaps we should be seeking to maximize trust rather than minimize fraud in society. But then we have to ask ourselves: “what would that look like?”
There does not need to be a set of constraints for optimisation to be defined. You can talk about optimisation on an unconstrained domain, for example all of ℝ⨯ℝ. But there DOES need to be a measure function that measures what you are optimising for. The benefit of fraud would be one such function you could optimise for, and that seems to be what GP is after. The pure amount of fraud is a different one, which seems to be what you are interested in.
Even without trust, you will reach an optimal amount because preventing fraud tends to become more expensive than the fraud itself, once you cover the simple and easy cases
The benefit to a low level of fraud is that people are still looking out for fraud, so the society is more robust. If there was no fraud, and someone just invent fraud (it will happen), the damage could be devastating.
they would have to be Moriarty level like in their inventiveness, most people start low and then expand their inventiveness with experience, the low early frauds would establish the new invention in the society.
This is lacks a strong causal analysis. We still don't understand why polls are consistently undershooting Trump support. Given the performance of polls in 2018, it seems highly correlated to Trump's presence on the ballot, and unclear if it will recur in a future presidential election. Ascribing better analysis to markets than polls requires us to ask "how?", and there isn't a clear mechanism.
FWIW I am also unconvinced by the article's thesis that prediction markets "beat" polls. But I'm not sure I agree with your premise that we need to ascribe causality if markets beat polls. The "point" of markets is that they work in mysterious ways: the combination of financial incentives and the wisdom of the crowd coalesce to price things correctly. You might be able to point out why a specific market participant has a specific opinion and makes a specific bet, but doing so for the entire market is a fool's errand.
In aggregate the polls were off by an entirely normal amount. What you can't do is predict how they will fair in a future election, because the pollsters themselves change strategy every time. It's as likely to be off in the other direction come 2024.
Most of the admittedly very early analysis I've read is basically it's low trust voters.
Low trust voters are hard to poll because they don't trust pollsters, they don't pick up their phone for strangers.
6 years ago this didn't matter because they were as likely to be Republican as Democratic. But that changed with Trump who appeals to these types of voters.
Then this election democrats suddenly increased their civic engagement which lead to them being much more likely to talk to pollsters. Skewing the results.
I know these are young comments, but I'm fascinated by the downvote patterns I'm seeing here. I didn't think of anything in your comment as remotely controversial; I thought it was the consensus best-guess of why polls are underperforming, as described by very mainstream sources like the NYT.
That would explain change over time, but it has problem with why the problem disappears in between 2016 and 2018 and returns in 2020, so even if it is accurate, it seems to be incomplete.
I think the explanation is basically they corrected for the first problem that happened in 2016 in 2018, but the second problem didn't appear until 2020.
lack of trust of polling. also there are risks of outing oneself as a Trump supporter in blue areas outweigh the risks of outing oneself as a Biden supporter in red areas.
There are a lot of replies here asking about correlation with non-racial factors such as economics or crime. The fact of the matter is that Blacks in America are poorer, suffer higher rates of unemployment, lower educational attainment and are forced to live in higher crime areas as the result of decades of racist housing policies and centuries of oppression. This is reflecting that legacy. Black people pay many different taxes merely for being Black in America, this is just another in a long list. As another example, Black people pay higher tax rates due to higher relative property assessments (https://www.washingtonpost.com/business/2020/07/02/black-pro...).
> Blacks in America are poorer, suffer higher rates of unemployment, lower educational attainment and are forced to live in higher crime areas as the result of decades of racist housing policies and centuries of oppression.
How do they fare in other countries, with different histories?
The OP was edited in response to this, but I'm still mystified. I'm not making a particular claim about anything other than the experience of Black people in America, so I don't see how the question is relevant.
How is it not relevant? When studying any phenomenon, why blind yourself to all data except that from the US? Comparing with other countries is the first thing you'd do when looking at public transport or healthcare, so what makes this case different?
The problem being, the countries with major numbers of people of African descent are, you guessed it right, in Africa and completely different economically from United States of America.
What such a comparison would prove? That poor people in a rich country are on average better off than people in a poor country?
Propose a good reference group please. I'd only mildly hazard a guess that perhaps South Africa might be a good comparison, since it's not a particularly poor country and has sizable numbers of blacks. Secondary, France, but it has a very different economical system and has not had obvious racial divides in near past.
Prove? No, what can be learned. If you want to fix healthcare, you look at countries with working healthcare systems and see what you can copy. Same here.
And there's plenty of countries with black populations even outside Africa - the France and South Africa you mentioned, then there's also the UK, Sweden, half a million in Germany, a million in Spain, Jamaica, and I'm going to guess a large number of South American. 1.4 million in Mexico, 300 thousand in India (https://en.wikipedia.org/wiki/Siddi), and I'm sure I missed plenty.
It's the height of US exceptionalist hubris to think nothing can be learned from all these countries.
What can be learned is that pay and employment is stratified by ethic group. However, UK not as strongly as US or South Africa, and very differently.
Still haven't found data for France, probably have to look for it in French.
For UK, my suspicion is that type of employment for Bangladeshi/Pakistani/Chinese workers is higher vs lower paying jobs.
This probably does not quite fit the employment structure for blacks in the USA at all. But if it does, the question is then: why blacks are denied access to well paying professional jobs?
In British case, the racial differences are mostly caused due to first generation immigrant biases, such as language barrier or cultural fit. (Esp. see salaries of older Indian descent.) This should not matter for USA. If it does, then why is US black culture, extant for many generations, being biased against?
Agreed. There's very little evidence to support the claims about what is discussed here is what made Stripe successful. Intuitively many of the claims seem true but where is the data?
