the most persuasive lie is the one you believe yourself
If someone really believes it, then I don't think they're operating in "bad faith". If the hidden motive is hidden to the speaker, that hiding doesn't come with intent.
It doesn't matter whether you said it was red because you were consciously lying or because you're wearing rose-colored glasses
It definitely matters. It completely changes how you should be trying to convince that person or behave around them.
It's different to believe a dumb argument than to intentionally lie, and honestly, humans are pretty social and honest. We mostly operate in good faith.
Agreed. LLMs will make mass surveillance (literature, but also phone calls, e-mails, etc) possible for the first time ever. And mass simulation of false public beliefs (fake comments online, etc). And yet Meta still thinks it's cool to open source all of this.
It's quite concerning. Given that we can't really roll back ML progress... Best case is probably just to make well designed encryption the standard. And vote/demonstrate where you can, of course.
I suppose one thing you could do here is pretend you can fit infinite rounds of the game into a finite time. Then Linda has a choice to make: she can either maximize expected wealth at for all finite , or she can maximize expected wealth at , the timestep immediately after all finite timesteps. We can wave our hands a lot and say that making her own bets would do the former and making Logan's bets would do the latter, though I don't endorse the way we're treating infinties here.
If one strategy is best for , it's still going to be best at as t goes to infinity. Optimal strategies don't just change like that as n goes to infinity. Sure you can argue that p(won every time) --> 0, but also that number is being multiplied by an extremely large infinity, so you can't just say that it totals to zero (in fact, 1.2, which is her EV from a single game, raised to infinity is infinity, so I argue as n goes to infinity, her EV goes to infinity, not 0, and not a number less than the EV from Logan's strategy).
Linda's strategy is always optimal with respect to her own utility function, even as n goes to infinity. She's not acting irrationally or incorrectly here.
The one world where she has won wins her $2**n, and that world exists with probability 0.6**n.
Her EV is always ($2**n)*(0.6**n), which is a larger EV (with any n) than a strategy where she doesn't bet everything every single time. Even as n goes to infinity, and even as probability approaches 1 that she has lost everything, it's still rational for her to have that strategy because the $2**n that she won in that one world is so massive that it balances out her EV. Some infinities are much larger than others, and ratios don't just flip when a large n goes to infinity.
Yes, losing worlds also branch, of course. But the one world where she has won wins her $2**n, and that world exists with probability 0.6**n.
So her EV is always ($2**n)*(0.6**n), which is a larger EV (with any n) than a strategy where she doesn't bet everything every single time. I argue that even as n goes to infinity, and even as probability approaches one that she has lost everything, it's still rational for her to have that strategy because the $2**n that she won in that one world is so massive that it balances out her EV. Some infinities are much larger than others.
I don't think it's correct to say that as n gets large her strategy is actually worse than Logan's under her own utility function. I think hers is always best under her own utility function.
it seems like the vast majority of people don't make their lives primarily about delicious food
That's true. There are built-in decreasing marginal returns to eating massive quantities of delicious food (you get full), but we don't see a huge number of - for example - bulimics who are bulimic for the core purpose of being able to eat more.
However, I'd mention that yummy food is only one of many things that are brains are hard-wired to mesa-optimize for. Social acceptance and social status (particularly within the circles we care about, i.e. usually the circles we are likely to succeed in and get benefit from) are very big examples that much of our behavior can be ascribed to.
reward optimization might be a convergent secondary goal, it probably won't be the agent's primary motivation.
So I guess, reflecting this to humans, would you argue that most human's primary motivations aren't motivated mostly by various mesa-objectives our brains are hardwired to have? In my mind this is a hard sell, as most things humans do you can trace back (sometimes incorrectly, sure) to some thing that was evolutionary advantageous (mesa-objective that led to genetic fitness). The whole area of evolutionary biology specializes in coming up with (hard to prove and sometimes convoluted) explanations here relating to both our behavior and physiology.
For example, you could argue that us posting hopefully smart things here is giving our brains happy juice relating to social status / intelligence signaling / social interaction, which in our evolutionary history increased the probability that we would find high quality partners to make lots of high quality babies with. I guess, if mesa-objectives aren't the primary drivers of us humans - what is, and how can you be sure?
"I'll give you £1 now and you give me £2 in a week". Will she accept?
In the universe where she's allowed to make the 60/40 doubled bet at least once a week, it seems like she's always say yes? I'm not seeing the universe in which she'd say no, unless she's using a non-zero discount rate that wasn't discussed here.
| I'm not sure I've ever seen a treatment of utility functions that deals with this problem?
Isn't this just discount rates?
the way we're treating infinties here
Yeah, that seems key. Even if the probability that Linda will eventually get 0 money approaches 1, that small slice of probability in the universe where she has always won is approaching an infinity far larger that Logan's infinity as the number of games approaches infinity. Some infinities are bigger than others. Linear utility functions and discount rates of zero necessarily deal with lots of infinities, especially in simplified scenarios.
Linda can always argue that in every universe where she lost everything, there's more (6 vs 4) universes where her winnings were double what they would have been had she not taken that bet.
There’s no escaping it: After enough backup steps, you’re traveling across the world to do cocaine.
But obviously these conditions aren’t true in the real world.
I think they are a little? Some people do travel to other countries for easier and better drug access. And some people become total drug addicts (perhaps arguably by miscalculating their long-term reward consequences and having too-high a discount rate, oops), while others do a light or medium amount of drugs longer-term.
Lots of people also don't do this, but there's a huge amount of information uncertainty, outcome uncertainty, and risk associated with drugs (health-wise, addiction-wise, knowledge-wise, crime-wise, etc), so lots of fairly rational (particularly risk-averse) folks will avoid it.
Button-pressing will perhaps be seen as a socially-unacceptable, risky behavior that can lead to long-term poor outcomes by AI, but I guess the key thing here is that you want, like, exactly zero powerful AIs to ever choose to destroy/disempower humanity in order to wirehead, instead of just a low percentage, so you need them to be particularly risk-averse.
Delicious food is perhaps a better example of wireheading in humans. In this case, it's not against the law, it's not that shunned socially, and it is ***absolutely ubiquitous***. In general, any positive chemical feeling we have in our brains (either from drugs or cheeseburgers) can be seen as (often "internally misaligned") instrumental goals that we are mesa-optimizing. It's just that some pathways to those feelings are a lot riskier and more uncertain that others.
And I guess this can translate to RL - an RL agent won't try everything, but if the risk is low and the expectation is high, it probably will try it. If pressing a button is easy and doesn't conflict with taking out the trash and doing other things it wants to do, it might try it. And as its generalization capabilities increase, its confidence can make this more likely, I think. So you should therefore increasingly train agents to be more risk-averse and less willing to break specific rules and norms as their generalization capabilities increase.
Why, exactly, would the AI seize[6] the button?
If it is a advanced AI, it may have learned to prefer more generalizable approaches and strategies. Perhaps it has learned the following features:
If you have trained it to take out the trash and clean windows, it will have been (mechanistically) trained to favor situations in which all three of these features occur. And if button pressing wasn't a viable strategy during training, it will favor actions that lead specifically to 2 and 3.
However, I do think it's conceivable that:
In reality (at least initially in the timeline of current AI --> superintelligent AI) I think if the button isn't pressable during training:
Anyways, I think there are lots of reasons to think that an AI might eventually try and press (or seize) the button. But I do totally agree that reward isn't this instant-wireheading feedback mechanism, and even when a model is 'aware' of the potentially to hack that reward (via button-pressing or similar), it is likely to prefer sticking to its more traditional actions and goals for a good long while, at least.
Winner = first correct solution, or winner = best / highest-quality solution over what time period?