Open societies, in contrast, must balance many competing interests and voting factions, meaning that free market supporters have limited power to enact their preferred policies, meaning they rarely can be implemented in a “pure” form.

If you publish a cookbook, you should get a portion of the sales of the cookbook itself, and no one should be allowed to distribute copies of it for free to undermine your sales.

What you don't get is a portion of the revenues of restaurants that use your recipes!

When people say “selling at a loss” they mean negative unit economics. No one ever means this much more expansive definition you’ve invented.

Importantly, people who either thought they had better information (and were sadly wrong) or people who were simply gambling. It’s not like prediction markets are taking money from orphanages.

Yes, that's what I said, but you're missing the point: Uber provided them with a better alternative than they would have had otherwise. It made them better off, not worse off!

> This is extremely realistic. This is already real. In particular, this is the gig economy. For example, if you consider how Uber works: in practical terms, the Uber drivers work for an algorithm, and the algorithm works for the executives who run Uber.

There seems to be a tacit agreement in polite society that when people say things like the above, you don't point out that, in fact, Uber drivers choose to drive for Uber, can choose to do something else instead, and, if Uber were shut down tomorrow, would in fact be forced to choose some other form of employment which they _evidently do not prefer over their current arrangement_!

Do I think that exploitation of workers is a completely nonsensical idea? No. But there is a burden of proof you have to meet when claiming that people are exploited. You can't just take it as given that everyone who is in a situation that you personally would not choose for yourself is being somehow wronged.

To put it more bluntly: Driving for Uber is not in fact the same thing as being uploaded into a computer and tortured for the equivalent of thousands of years!

So yeah, take my $13.99/month

Can we not glorify mass executions on HN please? Bluesky is available if that's your thing.

More: https://caseyhandmer.wordpress.com/2019/10/25/space-debris-p...

What I mean is a theory that allows you to categorize any given task according to whether it requires "thinking" or not, not literally cataloging all conceivable tasks.

The first category is what I'd call "the simplifying metaphor", in which it is claimed that AIs are actually "just" something very simple, and therefore do not think.

- "AIs just pick the most likely next token"

- "AI is just a blurry jpeg of the web" (Ted Chiang)

- "AIs are just stochastic parrots"

The problem with all of these is that "just" is doing an awful lot of work. For instance, if AIs "just" pick the most likely next token, it is going to matter a lot _how_ they do that. And one way they could do that is... by thinking.

There are many different stochastic processes that you could use to try to build a chat bot. LLMs are the only one so far that actually works well, and any serious critique has to explain why LLMs work better than (say) Markov chains despite "just" doing the same fundamental thing.

The second category of argument is "AIs are dumb". Here, skeptics claim that because AI fail at task X, they aren't thinking, because any agent capable of thought would be able to do task X. For instance, AIs hallucinate, or AIs fail to follow explicit instructions, and so on.

But this line of argument is also very poor, because we clearly don't want to define "thinking" as "a process by which an agent avoids all mistakes". That would exclude humans as well. It seems we need a theory that splits the universe of intellectual tasks into "those that require thinking" and "those that don't", and then we need to show that AI is good only at the latter, while humans are good at both. But unless I missed it no such theory is forthcoming.