Or more simply:
Player 1 makes a move for White.
Player 2 has the option to switch colors.
Play continues with Reversed Armageddon, where White wins ties.
I think this would work so long as Player 1 is capable of making a bad enough first move to cancel out White’s huge advantage from both going first and winning draws. (And ideally there would be more than one move that’s about that bad, so that the opening doesn’t always start the same way.)
“There exists a place in your cognition that feels like an expectation but actually stores an action plan that your body will follow, and you can load plans into it.” is a valuable insight and I’m not sure I’ve seen it stated quite in that form elsewhere.
Do you have more you could say about how cognition works, or reliable references to point at?
Everything I’ve read is either true but too specific or low level to be useful (on the science end) or mixed with nonsense (on the meditation end), and my own mind is too muddled to easily distinguish true facts about how it works from almost-true facts about how it works. This makes building up a reliable model really hard.
I believe you’re looking for A Half-Built Garden. Thought provocing hard sci-fi book about motherhood, community, gender, ecology, and aliens. I highly recommend it, in general and especially given your desired genre.
The market named “This Market Will Resolve No At The End Of 2025” will resolve to No at the end of 2025. Like it says in its title. What’s unclear about this?
The fact that you so naturally used the word “version” here (it was essentially invisible, it didn’t feel like a terminology choice at all) suggests that “version” would be a good term to use instead of “lens”. Downside being that it’s a sufficiently common word that it doesn’t sound like a Term of Art.
Let’s apply some data to this!
I’ve been in two high-stakes bad-vibe situations. (In one of them, someone else initially got the bad vibes, but I know enough details to comment on it.) In both cases, asking around would have revealed the issue. However, in both cases the people who knew the problematic person well, had either a good impression of them, or a very bad impression of them. Because there’s a pattern where someone who’s problematic in some way is also charismatic, or good at making up for it in other ways, etc. So my very rough model of these situations is that there were a bunch of people you could have asked about them and gotten “looks fine” with 60% probability or “stay the fuck away” with 40% probability. If you have only have a few data points of this variety, you’d want to trust your vibes because false negatives can be very costly.
stick to public spaces for a first date, do a web search for the person’s name, establish boundaries and stick to them, be prepared with concrete plans to react to signs of danger, etc.
These mitigations would do nothing against a lot of real relationship failures. Imagine that everything goes swimmingly for the first year. Then you start to realize that even though everything your partner has been doing makes sense on the surface, if you step back and look at the big picture their actions tend to have the effect of separating you from your friends and blaming yourself for a lot of things, and it just doesn’t seem healthy. When you finally decide to break up, it’s an extremely painful process because: (i) your partner is better at weaving stories than you, and from their perspective you’re the problematic person (ii) your friends all know your partner, and they’ve made a good impression, (iii) you will continue to see them at social events, and (iv) even after all of this, you don’t think they ever purposefully acted maliciously toward you.
Or in the words of Sean Carroll’s Poetic Naturalism:
There are many ways of talking about the world.
All good ways of talking must be consistent with one another and with the world.
Our purposes in the moment determine the best way of talking.
A “way of talking” is a map, and “the world” is the territory.
The orthogonality thesis doesn’t say anything about intelligences that have no goals. It says that an intelligence can have any specific goal. So I’m not sure you’ve actually argued against the orthogonality thesis.
And English has it backwards. You can see the past, but not the future. The thing which just happened is most clear. The future comes at us from behind.
Here’s the reasoning I intuitively want to apply:
where X = “you roll two 6s in a row by roll N”, Y = “you roll at least two 6s by roll N”, and Z = “the first N rolls are all even”.
This is valid, right? And not particularly relevant to the stated problem, due to the “by roll N” qualifiers mucking up the statements in complicated ways?
Where’s the pain?
Sure. For simplicity, say you play two rounds of Russian Roulette, each with a 60% chance of death, and you stop playing if you die. What’s the expected value of YouAreDead at the end?
With probability 0.6, you die on the first round
With probability 0.4*0.6 = 0.24, you die on the second round
With probability 0.4*0.4=0.16, you live through both rounds
So the expected value of the boolean YouAreDead random variable is 0.84.
Now say you’re monogamous and go on two dates, each with a 60% chance to go well, and if they both go well then you pick one person and say “sorry” to the other. Then:
With probability 0.4*0.4=0.16, both dates go badly and you have no partner.
With probability 20.40.6=0.48, one date goes well and you have one partner.
With probability 0.6*0.6=0.36, both dates go well and you select one partner.
So the expected value of the HowManyPartnersDoYouHave random variable is 0.84, and the expected value of the HowManyDatesWentWell random variable is 0.48+2*0.36 = 1.2.
Now say you’re polyamorous and go on two dates with the same chance of success. Then:
With probability 0.4*0.4=0.16, both dates go badly and you have no partners.
With probability 20.40.6=0.48, one date goes well and you have one partner.
With probability 0.6*0.6=0.36, both dates go well and you have two partners.
So the expected value of both the HowManyPartnersDoYouHave random variable and the HowManyDatesWentWell random variable is 1.2.
Note that I’ve only ever made statements about expected value, never about utility.
Probability of at least two success: ~26%
My point is that in some situations, “two successes” doesn’t make sense. I picked the dating example because it’s cute, but for something more clear cut imagine you’re playing Russian Roulette with 10 rounds each with a 10% chance of death. There’s no such thing as “two successes”; you stop playing once you’re dead. The “are you dead yet” random variable is a boolean, not an integer.
If you’re monagamous and go to multiple speed dating events and find two potential partners, you end up with one partner. If you’re polyamorous and do the same, you end up with two partners.
One way to think of it is whether you will stop trying after the first success. Though that isn’t always the distinguishing feature. For example, you might start 10 job interviews at the same time, even though you’ll take at most one job.
However it is true that doing something with a 10% success rate 10 times will net you an average of 1 success.
For the easier to work out case of doing something with a 50% success rate 2 times:
25% chance of 0 successes
50% chance of 1 success
25% chance of 2 successes
Gives an average of 1 success.
Of course this only matters for the sort of thing where 2 successes is better than 1 success:
10% chance of finding a monogamous partner 10 times yields 0.63 monogamous partners in expectation.
10% chance of finding a polyamorous partner 10 times yields 1.00 polyamorous partners in expectation.
EDIT: To clarify, a 10% chance of finding a monogamous partner 10 times yields 1.00 successful dates and 0.63 monogamous partners that you end up with, in expectation.
IQ over median does not correlate with creativity over median
That’s not what that paper says. It says that IQ over 110 or so (quite above median) correlates less strongly (but still positively) with creativity. In Chinese children, age 11-13.
And for a visceral description of a kind of bullying that’s plainly bad, read the beginning of Worm: https://parahumans.wordpress.com/2011/06/11/1-1/
I double-downvoted this post (my first ever double-downvote) because it crosses a red line by advocating for verbal and physical abuse of a specific group of people.
Alexej: this post gives me the impression that you started with a lot of hate and went looking for justifications for it. But if you have some real desire for truth seeking, here are some counterarguments:
Yeah, I think “computational irreducibility” is an intuitive term pointing to something which is true, important, and not-obvious-to-the-general-public. I would consider using that term even if it had been invented by Hitler and then plagiarized by Stalin :-P
Agreed!
OK, I no longer claim that. I still think it might be true
No, Rice’s theorem is really not applicable. I have a PhD in programming languages, and feel confident saying so.
Let’s be specific. Say there’s a mouse named Crumbs (this is a real mouse), and we want to predict whether Crumbs will walk into the humane mouse trap (they did). What does Rice’s theorem say about this?
There are a couple ways we could try to apply it:
We could instantiate the semantic property P with “the program will output the string ‘walks into trap’”. Then Rice’s theorem says that we can’t write a program Q that takes as input a program R and says whether R outputs ‘walks into trap’. For any Q we write, there will exist a program R that defeats it. However, this does not say anything about what the program R looks like! If R is simply print('walks into trap'), then it’s pretty easy to tell! And if R is the Crumbs algorithm running in Crumb’s brain, Rice’s theorem likewise does not claim that we’re unable tell if it outputs ‘walks into trap’. All the theorem says is that there exists a program R that Q fails on. The proof of the theorem is constructive, and does give a specific program as a counter-example, but this program is unlikely to look anything like Crumb’s algorithm. The counter-example program R runs Q on P and then does the opposite of it, while Crumbs does not know what we’ve written for Q and is probably not very good at emulating Python.
We could try to instantiate the counter-example program R with Crumb’s algorithm. But that’s illegal! It’s under an existential, not a forall. We don’t get to pick R, the theorem does.
Actually, even this kind of misses the point. When we’re talking about Crumb’s behavior, we aren’t asking what Crumbs would do in a hypothetical universe in which they lived forever, which is the world that Rice’s theorem is talking about. We mean to ask what Crumbs (and other creatures) will do today (or perhaps this year). And that’s decidable! You can easily write a program Q that takes a program R and checks if R outputs ‘walks into trap’ within the first N steps! Rice’s theorem doesn’t stand in your way even a little bit, if all you care about is behavior after a fixed finite amount of time!
Here’s what Rice’s theorem does say. It says that if you want to know whether an arbitrary critter will walk into a trap after an arbitrarily long time, including long after the heat death of the universe, and you think you have a program that can check that for any creature in finite time, then you’re wrong. But creatures aren’t arbitrary (they don’t look like the very specific, very scattered counterexample programs that are constructed in the proof of Rice’s theorem), and the duration of time we care about is finite.
If you care to have a theorem, you should try looking at Algorithmic Information Theory. It’s able to make statements about “most programs” (or at least “most bitstrings”), in a way that Rice’s theorem cannot. Though I don’t think it’s important you have a theorem for this, and I’m not even sure that there is one.
There’s a simpler explanation. You say yourself that the answer to this original question is 1/2:
and that the answer to this slightly different question is 1/3:
People disagree about the answer to the Sleeping Beauty problem because those questions are nearly identical and easy to confuse. And because in almost all circumstances the answer to questions that vary this way is the same, so you don’t need to distinguish them.
Bit of a side note, but personally the distinction I like to draw is between the probability that the coin landed heads or tails (which happens on Sunday, exactly once, and has two possible events, giving the answer 1⁄2), and the probability that Beauty observes heads (which happens on Monday or maybe Tuesday, and has three possible events, giving the answer 1⁄3).