*The last two bullet points. Meta-consciousness and self-consciousness
notfnofn
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I meant if you had any suggested rewords, because there don’t seem to be any perfect definitions of these concepts.
“Easy problems of consciousness” is an established term that is a bit better-defined than consciousness. By transcending, I just meant beyond what can be explained by solving the easy problems of consciousness
This was actually what I meant by a version of panpsychism that seemed to be the natural conclusion of humans having subjective experiences, but a conclusion I want to see if I can avoid.
I tried some different definitions of consciousness while writing this point, until settling on “able have subjective experiences that transcend the ‘easy problems of consciousness’”
Do you have any suggestions for making this more precise?
I’d like to explore these in more depth, but for now I’ll just reduce all the angles you provided to the helpful summaries/applications you provided. I’ll call the perspective of going from adult human to zygote the “physical history” and the perspective of going up the ancestral tree as the “information history” (for simplicity, maybe we stop as soon as we hit a single-celled organism).
Sentience: This feels like a continuous thing that gets less and less sophisticated as we go up the information history. In each generation, the code gets a little better at using the laws of physics and chemistry to preserve itself. Of course if one has a threshold for what counts as sentience, it will cross it at some point, but this still strikes me as continuous.
Wakefulness: This would strike me as a quantized thing from both the information and physical history perspective. At some point in both histories, the organism/cell would pick up some cyclic behavior.
Intentionality: I’d need to look more at this, because my interpretation of your first sentence doesn’t make sense with the second.
Phenomonal, Self-Consciousness, Meta-Consciousness: Definitely quantized in both perspectives
When I was thinking of subjective experience, I think the only concepts here that are either weaker or stronger than what I had in mind are the last two. For the rest, I think I can both imagine a robot that satisfies the conditions and imagine a conscious being that does not satisfy the condition.
But the last two still feel too strong. I will think more about it.
That’s a bit of a long read, and both your endorsement and the title seem too strong to be believable. If a few more people endorse that it’s worth reading, I’ll give it a go!
Very nice! Notice that if you write as , and play around with binomial coefficients a bit, we can rewrite this as:
which holds for as well, in which case it becomes the derivative product rule. This also matches the formal power series expansion of , which one can motivate directly
(By the way, how do you spoiler tag?)
This is true, but I’m looking for an explicit, non-recursive formula that needs to handle the general case of the kth anti-derivative (instead of just the first).
The solution involves doing something funny with formal power series, like in this post.
Here’s a puzzle I came up with in undergrad, based on this idea:
Let be a function with nice derivatives and anti-derivatives (like exponentials, sine, or cosine) and be a polynomial. Express the th anti-derivative of in terms of derivatives and anti-derivatives of and .
Can provide link to a post on r/mathriddles with the answer in the comments upon request
Suppose we don’t have any prior information about the dataset, only our observations. Is any metric more accurate than assuming our dataset is the exact distribution and calculating mutual information? Kind of like bootstrapping.
For the second paragraph, we’re assuming this AI has not made a mistake in predicting human behavior yet after many, many trials in different scenarios. No exact probability. We’re also assuming perfect levels of observation, so we know that they pressed a button, bombs are heading over, and any observable context behind the decision (like false information).
The first paragraph contains an idea I hadn’t considered, and it might be central to the whole thing. I’ll ponder it more.
I didn’t get around to providing more clarity. I’ll do that now:
Both parties would click the button if it was clear that the other party would not click the button in retaliation. This way they do not have to worry about being wiped off the map.
The two parties would both prefer a world in which only the other party survives to a world without any humanity.
We know that the other party will click the button if and only if they predict with extremely high confidence that we will not retaliate. Our position is the same.
It’s extremely beautiful, and seems like it would serve as a nice introduction to the website that isn’t subject to the same random noise as the front page.
I really like ‘leastwrong’ in the url and top banner (header?), but I could see how making ‘The LeastWrong’ the actual title could rub off on some as pretentious.
Thanks for your answer; this explains why I was not able to find any related discussion on this. I read this article recently: https://www.lesswrong.com/posts/c3wWnvgzdbRhNnNbQ/timeless-decision-theory-problems-i-can-t-solve and misremembered it as a defense of evidential decision theory, instead of a different decision theory altogether.
So from a timeless decision theory perspective, is it correct to say that one would press the button? And from both EDT/CDT perspectives, one would not press the button (assuming they value the other country staying alive over no country staying alive)?
I’m not sure if these kind of comments are acceptable on this site, but I just wanted to say thank you for this sequence. I doubt I will significantly change my life after reading this, but I hope to change it at least a little in this direction.
Viewing myself as a reinforcement learning agent that balances policy improvement (taking my present model and thinking about how to tweak my actions to optimize rewards assuming my model is correct) and exploration (observing how the world actually responds to certain actions to update the model), I have historically spent far too much time on policy improvement.
This sequence provides a nice set of guidelines and methods to pivot gears and really think about what it even means to improve ones model of the world, in a way that seems… fun? fulfilling? I hope to report back on this in a few months and say how it’s gone; there is a high probability that I fall back into old habits, but I hope I do not.
In case it hasn’t crossed your mind, I personally think it’s helpful to start in the setting of estimating the true mean of a data stream. A very natural choice estimator for is the sample mean of the which I’ll denote . This can equivalently be formulated as the minimizer of .
Others have mentioned the normal distribution, but this feels secondary to me. Here’s why—let’s say , where is a known continuous probability distribution with mean 0 and variance 1, and are unknown. So the distribution of each has mean and variance (and assume independence).
What must be for the sample mean to be the maximum likelihood estimator of ? Gauss proved that it must be , and intuitively it’s not hard to see why it would have to be of the form .
So from this perspective, MSE is a generalization of taking the sample mean, and asking the linear model to have gaussian errors is necessary to formally justify MSE through MLE.
Replace sample mean with sample median and you get the mean absolute error.
Is there no way to salvage it via a Nash bargaining argument if the odds are different? Or at least, deal with scenarios where you have x:1 and 0:1 odds (i.e. you can only bet on heads)?
Are there any other nice decision problems that are low? A quick search only reveals existence theorems.
Intuitive guess: Can we get some hierarchy from oracles to increasingly sparse subsets of the digits of Chaitin’s constant?