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:

$(X\to Y)\to P\left[Y|Z\right]\ge P\left[X|Z\right]$

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/