Sherrinford

Economist.

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A list of some beliefs of which I changed my subjective probabilities because of FTX (in one direction or the other):

  • "When rich EA community people give money to political candidates, fear that they just want to buy influence so as to avoid regulation is misplaced."
  • "The EA community is very good at understanding and managing risks, including low-probability high-effect risks"
  • "when success stories are too good to be true, they aren't true."
  • "crypto is a good thing."
  • "People in general understand risk diversification."

In the latest episode, the Bayesian conspiracy podcast people discuss moral behavior in the context of FTX and in that context treat the claim that the FTX thing is evidence that you shouldn't trust people who look kind of weird as a totally normal part of a conversation. Could we maybe just slightly slow down all these discussions?

So if I understand you correctly, some techies in the lw and ea communities have put some money in there and due to the strong increase of crypto prices, the worth of their crypto assets had increased a lot. Now that a lot of it is dust in the wind, these people have lost a lot, but if it had only grown from a small-ish amount, they are not really worse off than they would have been with conservative investements, right?

I am asking because I still don't fully understand posts like this. I think I understand the "job security" part and also would understand if it was about the monetary loss to important EA causes, both because SBF gave money to EA. But the text explicitly mentions "personal savings" even before job security, and does not explicitly mention EA causes.

Several posts in this or the ea forum seem to suggest that it's kind of standard among people in the community to have invested a large share of their personal wealth into crypto, and in ftx in particular.

Why should this be assumed? Are there statistics on that?

I used to believe that most people have a diversified portfolio, both inside and outside of the communities. Isn't that the case?

In the world you describe, both readers and newspapers would know that that statement was nonsense, and nobody would take it seriously.

I don't see why that should be the case, given the similarity to exchanging ideas on how to avoid paywalls. In real life, people don't tell each other that it's okay to ignore the "please pay", because people don't "need" that advice, they just do ignore the "please pay".

Or in a world where people did somehow take it seriously, the newspapers would go bankrupt after losing all their network effects because people wouldn't encounter articles from search engines or word of mouth.

I guess that's why many newspaper websites paywall their articles nowadays. 

That's my whole point. The business model of a newspaper crucially depends on there being free ways to read its content, and getting people to pay for it anyway. And once a business model depends on a "paywall" which is in fact a fiction or lie, I do think that bears on the morality of circumventing it. A newspaper can't call people bad for circumventing a paywall when it could've made the paywall secure but intentionally chose not to.

Sorry, I don't understand they point. The existence of the paywall clearly signals to people that the newspaper does not want them to read the content for free, whether or not the newspaper also decides to make it technically possible to read it such that indexing works etc.

This also bears on the notion of laws and enforceability: If you say "you can't read this unless you pay", and then don't take the slightest steps (as in your original comment) or sufficient steps (as in the case of intentionally soft paywalls) to enforce this rule, then to what extent does this rule even really exist?

In my example, the newspaper did not tell people that they can't read it if they did not pay, but that they are not allowed to read it if they don't pay. So in this world, people are morally expected to follow the wish of the content creator in order to make a more efficient economy possible (i.e., one where enforcement costs are not necessary). In real world, something similar exists, for example the "please support me" of people writing a substack (or the usual pop-up on wikipedia or here: https://taz.de/-Nachrichten-im-Ukraine-Krieg-/!5892878/)

Thanks for the answer but I don't see how that touches the morality of bypassing paywalls. The morality would be the same if there were no technical paywall at all but the newspaper told people explicitly on page 1 that you are only allowed to read it if you paid, and there were a community of people telling each other "you can just click 'continue' and that's okay".

The actual costs of producing the newspaper are sunk. So the only relevant part would be the opportunity costs of seeling the paper to someone. So for my question you can assume that in the kiosk there are more newspapers than will be sold that day.

It seems the abstract of the study you link does not mention spies?

Maybe another reason why it might not have been such a great fitness advantage is that activity was effectively constrained by daylight availability?

This may be called something like the "low-probability forecaster reputation problem".

People in the village were not necessarily wrong ex-ante to dismiss the warnings. They of course should not update much about forecasting abilities on not seeing a wolf after low-probability warnings. But they cannot know the accuracy of the forecasts. And if someone is an expert in certain low-probability events and nothing else, you cannot judge ability a lot based on the few forecasts. You need to examine the models used for forecasting, but what tells you that is a good use of your time? There are crackpots everywhere.

Therefore, people try to get bets or forecasts for things that are implied by the lp forecaster's model but happen more often and earlier. If your model implies big grey wolves for tonight with 15% chance, should we already see dead sheep by noon? If your model implies war between states x and y next year, what should we see next month that would not be expected by people with different models?

If you really specialize in forecasting low-probability events only and cannot show any evidence to show your model is right, then that is a tragedy. But it is understandable that people do not update based on your forecast.

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