Thank you for making and publishing this! It's interesting to see some more of the background and process that goes into works like HPMOR, both for the sake of appreciation of the work, and for reference in my own story-crafting.
1Isn't the counterfactual trolley problem setup backwards? It should be counterfactual Omega giving you the better setup (not tying people to the tracks) if it predicts you'll take the locally "worse" option in the actual case, not the other way around, right?
Because with the current setup you just don't pull and Omega doesn't tie people to tracks.
1As an example of differentiating different kinds of footnotes, waitbutwhy.com uses different appearances for “interesting extra info” notes vs “citation” notes.
Both kinds also appear as popups when interacted with (certainly an advantage of the digital format).
1Somehow I missed that bit.
That makes the situation better, but there’s still some issue. The refund is not earning interest, but you liabilities are.
Take the situation with owing $25 million. Say that there’s a one year time between the tax being assessed and your asset going to $0 (at which time you claim the refund). In this time the $25 million loan you took is accruing interest. Let’s say it does so at a 4% rate per year, when you get your $25 million refund you therefore have $26 million in loans.
So you still end up $1 million in debt due to “gains” that you were never able to realize.
Scenario: you have equity worth (say) $100 million in expectation, but of no realized value at the moment.
You are forced to pay unrealized gains tax on that amount, and so are now $25 million in the hole. Even if you avoid this crashing you immediately (such as by getting a loan), if your equity goes to $0 you’re still out for the $25 million you paid, with no assets to back it.
The fact that this could be counted as a prepayment for a hypothetical later unrealized gain doesn’t help you, you can’t actually get your money back.
But if UDT starts with a broad prior, it will probably not learn, because it will have some weird stuff in its prior which causes it to obey random imperatives from imaginary Lizards.
I don’t think this necessarily follows? For there to be a systematic impact on UDT’s behavior there would need to be more Lizard-Worlds that reward X than Anti-Lizard-Worlds that penalize X, so this is only a concern if there is reason to believe that there are “more” worlds (in an abstract logical-probability sense) that favor a specific direction.
Clearly this could still potentially cause problems, but (at least to me) it doesn’t seem like the problem is as ubiquitous as the essay makes it out to be.
My benchmark for thinking about the experience machine: imagine a universe where only one person and the stuff they interact with exist (with any other “people” they interact with being non-sapient simulations) and said person lives a fulfilling life. I maintain that such a universe has notable positive value, and that a person in an experience machine is in a similarly valuable situation to the above person (both being sole-moral-patients in a universe not causally impacting any other moral patients).
This does not preclude the possibility of improving on that life by e.g. interacting with actual sapient others. This view is fully compatible with non-experience-machine lives having much more value than experience-machine ones, but it’s a far cry from the experience-machine lives having zero value.
You can’t just trivially scale up the angular resolution by bolting more sensors together (or similar methods). It gets more difficult to engineer the lenses and sensors to meet super-high specs.
And aside from that, the problem behaves nonlinearly with the amount of atmosphere between you and the plane. Each bit of distortion in the air along the way will combine, potentially pretty harshly limiting how far away you can get any useful image. This may be able to be worked around with AI to reconstruct from highly distorted images, but it’s far from trivial on the face of it.
The quote seems to be from Vorkosigan Saga.
per Tvtropes.