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#4868·Tyler Mills, about 10 hours agoThis may be too subjective, but I've always really disliked end-of-line hyphenation, of the kind currently used here. I find it pretty disruptive to the flow of reading, AND a source of visual clutter. That's a heavy cost for the supposed benefit of a justified margin, but we don't seem to be getting that benefit here either; the margin still appears jagged. A justified margin itself is unnecessary, if you ask me, but it can in any case be accomplished the other way, where small spaces are distributed between words in each line as needed. To me the latter method of the two is better for readability, no contest. I would advocate for the third/default method, here (jagged margin, no funny business), since justified margins seems needlessly formal.
Removed hyphenation
This may be too subjective, but I've always really disliked end-of-line hyphenation, of the kind currently used here. I find it pretty disruptive to the flow of reading, AND a source of visual clutter. That's a heavy cost for the supposed benefit of a justified margin, but we don't seem to be getting that benefit here either; the margin still appears jagged. A justified margin itself is unnecessary, if you ask me, but it can in any case be accomplished the other way, where small spaces are distributed between words in each line as needed. To me the latter method of the two is better for readability, no contest. I would advocate for the third/default method, here (jagged margin, no funny business), since justified margins seems needlessly formal.
#4860·Knut Sondre Sæbø revised 3 days agoI think tractibility lacks the open-ended capacity to reformulate what counts as a problem, a solution, and relevant data. Creativity is (at least partially) the ability to reformulate the problem space itself, not by ironing out implications of existing theories. An AI and computational systems is already good at ironing out the implications in our language and existing knowledge systems. But that's search within a given space, not the creation of a new one. Creativity seems to work on a higher level. It's operating at the level of problem framing, which requires things like relevance. An AI can't create new relevance, because its weights are a statistical compression of what humans have already found relevant. It inherits a pre-given frame.
I might be confused about what you mean by tractible. But it seems to me that tractability can't do the work the bounty asks. Tractability is formally defined relative to a fixed problem space. But universal creativity is (at least partially) the capacity to restructure the space, to change what counts as a problem, a solution, and relevant data.
I agree that tractability is related to a given problem space, and that creativity is about reshaping the problem space, among other things. Given that I've been thinking of the problem space as the space of all explanations, I'm not sure where I stand... Maybe the "space of all explanations" framing is wrongheaded, because a mind never has any actionable knowledge of that space? We can discuss the space of all explanations in some sense, but we can't organize or describe it in any substantive way...
Also, per #4865, you helped me remember that personhood could involve intractable algorithms, but ones which only ever run with small inputs, since that can still be perfectly practical. Whether or not that means the whole person is a tractable algorithm or not, I'm not sure.
Between these points I think this is enough for you to claim the bounty, because it does argue that personhood "should not be defined in terms of tractability", per the bounty terms (italics mine, here). Tractability does not help explain personhood. Or, in any case, it doesn't seem like this line of discussion will be very fruitful (but this could itself be mistaken).
#4864·Tyler MillsOP, about 11 hours agoI think I see now, and agree with the above. Partly a semantics issue (yes, I'm thinking of an algorithm in the "formal" CS sense: an abstract/mathematical finite procedure). The scare quotes were meant to suggest that one could attempt to implement one algorithm, but the implementation may in fact be more closely implementing some other unrelated algorithm, but this is confusing.
At any rate, how ChatGPT summarized it makes sense to me:
"One function → many algorithms can compute it.
One algorithm → many implementations can realize it.
Complexity attaches primarily to algorithms, secondarily to implementations, and not to functions."
"Secondarily" meaning:
Implementations of an algorithm inherit the algorithm’s asymptotic behavior. If an implementation has a different asymptotic behavior than one algorithm, it is effectively a different algorithm.
#4851·Knut Sondre Sæbø revised 3 days agoBy Tractible, do you mean "efficient relative to fixed task"?
Yes, my understanding is that the standard sense of tractable, for some algorithm, is: can be executed in time that grows at worst by a polynomial function of the input size. This is the sense I mean. The fixed task would be: create a given explanation in the space of all possible explanations.
Implementations of a given algorithm can be way more or less efficient in practice, though. Maybe personhood does require intractable algorithms, but ones which only ever run with small inputs... The question of the bounty is whether can we make a case for or against this. But part of the hope is also to learn if this whole framing is mistaken.
#4849·Dennis Hackethal, 4 days ago"Complexity" in the sense of growth behavior with input size?
Yes.
I can see how an "implementation" of one algorithm in practice can accidentally change it to another algorithm.
Not sure why you put that in scare quotes. You might be right in the CS sense where ‘algorithm’ refers to an abstract procedure whereas ‘implementation’ is concrete code realizing that algorithm. (Though as a disclaimer, I don’t have a CS degree. My experience with programming is fully on-the-job.)
My point is more that two different implementations that compute the same function can have different big O. In that case, they’re usually considered different algorithms, even if the high-level goal is the same.
Regardless, the structure of the program is by far the most important factor determining performance characteristics. If you were saying that complexity is independent of implementation only insofar as the implementation truly implements the same algorithm, then I agree. So I’m not sure whether I should mark this as a counter-criticism. For now I won’t, pending new evidence.
I think I see now, and agree with the above. Partly a semantics issue (yes, I'm thinking of an algorithm in the "formal" CS sense: an abstract/mathematical finite procedure). The scare quotes were meant to suggest that one could attempt to implement one algorithm, but the implementation may in fact be more closely implementing some other unrelated algorithm, but this is confusing.
At any rate, how ChatGPT summarized it makes sense to me:
"One function → many algorithms can compute it.
One algorithm → many implementations can realize it.
Complexity attaches primarily to algorithms, secondarily to implementations, and not to functions."
Nice work on #4856. Sounds like you’re one of the few who get DD’s stance re creativity.
I don’t think you’re in the Veritula Telegram channel yet. Email me if you want to be: dh@dennishackethal.com
#4856·Knut Sondre Sæbø, 3 days agoI think the core of universal creativity isn't about efficiency, it's the open-ended capacity to restructure what counts as a problem, a solution, and relevant data. Creativity is (at least partially) the ability to reformulate the problem space itself, not by ironing out implications of existing theories. An AI and computational systems is already good at ironing out the implications in our language and existing knowledge systems. But that's search within a given space, not the creation of a new one. Creativity seems to work on a higher level. It's operating at the level of problem framing, which requires things like relevance. An AI can't create new relevance, because its weights are a statistical compression of what humans have already found relevant. It inherits a frame; it doesn't generate one.
I think this shows that tractability can't do the work the bounty asks. Tractability is defined relative to a fixed problem space. But universal creativity is (at least partially) the capacity to restructure the space, to change what counts as a problem, a solution, and relevant data.
#4823·Tyler MillsOP, 7 days agoAgreed on both counts, but I think the bountied idea survives this...
Recognizing and criticizing ideas could be a requisite for tractably synthesizing any possible explanation (I suspect as much).
Tractability is a consequence of creativity. It's a little like saying the difference between you and a rock, is that you can move faster.
I think tractibility lacks the open-ended capacity to reformulate what counts as a problem, a solution, and relevant data. Creativity is (at least partially) the ability to reformulate the problem space itself, not by ironing out implications of existing theories. An AI and computational systems is already good at ironing out the implications in our language and existing knowledge systems. But that's search within a given space, not the creation of a new one. Creativity seems to work on a higher level. It's operating at the level of problem framing, which requires things like relevance. An AI can't create new relevance, because its weights are a statistical compression of what humans have already found relevant. It inherits a frame; it doesn't generate one.
I think this shows that tractability can't do the work the bounty asks. Tractability is defined relative to a fixed problem space. But universal creativity is (at least partially) the capacity to restructure the space, to change what counts as a problem, a solution, and relevant data.
I think tractibility lacks the open-ended capacity to reformulate what counts as a problem, a solution, and relevant data. Creativity is (at least partially) the ability to reformulate the problem space itself, not by ironing out implications of existing theories. An AI and computational systems is already good at ironing out the implications in our language and existing knowledge systems. But that's search within a given space, not the creation of a new one. Creativity seems to work on a higher level. It's operating at the level of problem framing, which requires things like relevance. An AI can't create new relevance, because its weights are a statistical compression of what humans have already found relevant. It inherits a pre-given frame.
I might be confused about what you mean by tractible. But it seems to me that tractability can't do the work the bounty asks. Tractability is formally defined relative to a fixed problem space. But universal creativity is (at least partially) the capacity to restructure the space, to change what counts as a problem, a solution, and relevant data.
I think the core of universal creativity isn't about efficiency, it's the open-ended capacity to restructure what counts as a problem, a solution, and relevant data. Creativity is (at least partially) the ability to reformulate the problem space itself, not by ironing out implications of existing theories. An AI and computational systems is already good at ironing out the implications in our language and existing knowledge systems. But that's search within a given space, not the creation of a new one. Creativity seems to work on a higher level. It's operating at the level of problem framing, which requires things like relevance. An AI can't create new relevance, because its weights are a statistical compression of what humans have already found relevant. It inherits a frame; it doesn't generate one.
I think this shows that tractability can't do the work the bounty asks. Tractability is defined relative to a fixed problem space. But universal creativity is (at least partially) the capacity to restructure the space, to change what counts as a problem, a solution, and relevant data.
I think tractibility lacks the open-ended capacity to reformulate what counts as a problem, a solution, and relevant data. Creativity is (at least partially) the ability to reformulate the problem space itself, not by ironing out implications of existing theories. An AI and computational systems is already good at ironing out the implications in our language and existing knowledge systems. But that's search within a given space, not the creation of a new one. Creativity seems to work on a higher level. It's operating at the level of problem framing, which requires things like relevance. An AI can't create new relevance, because its weights are a statistical compression of what humans have already found relevant. It inherits a frame; it doesn't generate one.
I think this shows that tractability can't do the work the bounty asks. Tractability is defined relative to a fixed problem space. But universal creativity is (at least partially) the capacity to restructure the space, to change what counts as a problem, a solution, and relevant data.
#4856·Knut Sondre Sæbø, 3 days agoI think the core of universal creativity isn't about efficiency, it's the open-ended capacity to restructure what counts as a problem, a solution, and relevant data. Creativity is (at least partially) the ability to reformulate the problem space itself, not by ironing out implications of existing theories. An AI and computational systems is already good at ironing out the implications in our language and existing knowledge systems. But that's search within a given space, not the creation of a new one. Creativity seems to work on a higher level. It's operating at the level of problem framing, which requires things like relevance. An AI can't create new relevance, because its weights are a statistical compression of what humans have already found relevant. It inherits a frame; it doesn't generate one.
I think this shows that tractability can't do the work the bounty asks. Tractability is defined relative to a fixed problem space. But universal creativity is (at least partially) the capacity to restructure the space, to change what counts as a problem, a solution, and relevant data.
An interesting example from cognitive science is the Mutilated Chessboard Problem, which asks whether a board with two same-coloured corners removed can be tiled by dominoes. As a tiling problem the search space is combinatorially explosive. But reframe it as a colour problem and the answer is easy. Every domino covers one black and one white square, and you have unequal numbers of each. The solution came not from searching harder, but from seeing the problem differently.
#4694·Tyler MillsOP revised 22 days agoBy this standard, a random number generator has universal creativity as well, and is therefore a person. So there must be a standard for personhood other than: able to generate any possible explanation. Such as: can do that tractably.
I think the core of universal creativity isn't about efficiency, it's the open-ended capacity to restructure what counts as a problem, a solution, and relevant data. Creativity is (at least partially) the ability to reformulate the problem space itself, not by ironing out implications of existing theories. An AI and computational systems is already good at ironing out the implications in our language and existing knowledge systems. But that's search within a given space, not the creation of a new one. Creativity seems to work on a higher level. It's operating at the level of problem framing, which requires things like relevance. An AI can't create new relevance, because its weights are a statistical compression of what humans have already found relevant. It inherits a frame; it doesn't generate one.
I think this shows that tractability can't do the work the bounty asks. Tractability is defined relative to a fixed problem space. But universal creativity is (at least partially) the capacity to restructure the space, to change what counts as a problem, a solution, and relevant data.
This also admits of the distinction between AI and AGI (and "universal creativity") as being whether the system is capable of creating knowledge ex nihilo, as argued by Deutsch. Only universal creativity could create knowledge from nothing. Bounded creativity must start with something.
I think DD's view is that creativity is problem-solving at a meta level. True knowledge creation occurs when the problem space itself is reformulated, not by ironing out implications of existing theories. An AI is already good at ironing out the implications in our language and existing knowledge systems. But that's search within a given space, not the creation of a new one. Creativity seems to work on a higher level. It's operating at the level of problem framing, which requires things like relevance. An AI can't create new relevance, because its weights are a statistical compression of what humans have already found relevant. It inherits a frame; it doesn't generate one.
This is why tractability can't do the work the bounty asks. Tractability is defined relative to a fixed problem space. But universal creativity is (at least partially) the capacity to restructure the space, to change what counts as a problem, a solution, and relevant data.
This also admits of the distinction between AI and AGI (and "universal creativity") as being whether the system is capable of creating knowledge ex nihilo, as argued by Deutsch. Only universal creativity could create knowledge from nothing. Bounded creativity must start with something.
Moved the criticism of 4694
#4688·Tyler MillsOP, 22 days agoThis also admits of the distinction between AI and AGI (and "universal creativity") as being whether the system is capable of creating knowledge ex nihilo, as argued by Deutsch. Only universal creativity could create knowledge from nothing. Bounded creativity must start with something.
This also admits of the distinction between AI and AGI (and "universal creativity") as being whether the system is capable of creating knowledge ex nihilo, as argued by Deutsch. Only universal creativity could create knowledge from nothing. Bounded creativity must start with something.
I think DD's view is that creativity is problem-solving at a meta level. True knowledge creation occurs when the problem space itself is reformulated, not by ironing out implications of existing theories. An AI is already good at ironing out the implications in our language and existing knowledge systems. But that's search within a given space, not the creation of a new one. Creativity seems to work on a higher level. It's operating at the level of problem framing, which requires things like relevance. An AI can't create new relevance, because its weights are a statistical compression of what humans have already found relevant. It inherits a frame; it doesn't generate one.
This is why tractability can't do the work the bounty asks. Tractability is defined relative to a fixed problem space. But universal creativity is (at least partially) the capacity to restructure the space, to change what counts as a problem, a solution, and relevant data.
By Tractible, do you mean "efficient relative to fixed task"?
By Tractible, do you mean "efficient relative to fixed task"?
#4847·Tyler MillsOP, 4 days agoThis is a good point, related to Dirk's #4813. As far as the bounty goes, I think my response in #4823 applies here as well, however. To refine it:
Recognizing, criticizing, and being able to understand explanations could all be requisites for tractably synthesizing any possible explanation. The bounty regards whether the tractability requirement can be done without.It seems like a mind being able to create, recognize, understand and differentiate (etc.) good explanations are necessary but not sufficient criteria for personhood; if that process is intractable, then beyond a certain amount of current knowledge (considering that as the input to the process), the person effectively cannot continue with it... so that compromises the universality.
They must be able to create, recognize and understand any given explanation, and maintain that ability as their knowledge grows, ad infinitum...
By Tractible, do you mean "efficient relative to fixed task"?
#4848·Tyler MillsOP, 4 days ago"Complexity" in the sense of growth behavior with input size? Further reading is still suggesting to me that this is intrinsic to a given algorithm (or class of them). Intrinsic to the math and logic. Implementations can be faster/slower/hungrier for a given input, but if they have different limiting behavior, aren't they different algorithms? I can see how an "implementation" of one algorithm in practice can accidentally change it to another algorithm.
"Complexity" in the sense of growth behavior with input size?
Yes.
I can see how an "implementation" of one algorithm in practice can accidentally change it to another algorithm.
Not sure why you put that in scare quotes. You might be right in the CS sense where ‘algorithm’ refers to an abstract procedure whereas ‘implementation’ is concrete code realizing that algorithm. (Though as a disclaimer, I don’t have a CS degree. My experience with programming is fully on-the-job.)
My point is more that two different implementations that compute the same function can have different big O. In that case, they’re usually considered different algorithms, even if the high-level goal is the same.
Regardless, the structure of the program is by far the most important factor determining performance characteristics. If you were saying that complexity is independent of implementation only insofar as the implementation truly implements the same algorithm, then I agree. So I’m not sure whether I should mark this as a counter-criticism. For now I won’t, pending new evidence.
#4840·Dennis Hackethal, 7 days agoThe given algorithm has a complexity, independent of [the implementation]
No, the complexity depends on the implementation.
"Complexity" in the sense of growth behavior with input size? Further reading is still suggesting to me that this is intrinsic to a given algorithm (or class of them). Intrinsic to the math and logic. Implementations can be faster/slower/hungrier for a given input, but if they have different limiting behavior, aren't they different algorithms? I can see how an "implementation" of one algorithm in practice can accidentally change it to another algorithm.
#4843·Knut Sondre Sæbø revised 7 days ago"Understanding" isn't just another way of saying "can explain.". Explaining follows from understanding, but isn't synonymous. An RNG could by chance generate a good explanation, but it doesn't understand it, and therefore can't distinguish it from garbage. Understanding involves recognizing that something is a good explanation. It is conscious understanding that makes conjecture and criticism possible. Without it, you have no criticism, only random selection. What do you think of the suggestion that what's lacking from the explanatory universality definition, is an intelligent selection mechanism. A random program can generate any explanation given infinite time, but it will never select which explanation is good.
This is a good point, related to Dirk's #4813. As far as the bounty goes, I think my response in #4823 applies here as well, however. To refine it:
Recognizing, criticizing, and being able to understand explanations could all be requisites for tractably synthesizing any possible explanation. The bounty regards whether the tractability requirement can be done without.
It seems like a mind being able to create, recognize, understand and differentiate (etc.) good explanations are necessary but not sufficient criteria for personhood; if that process is intractable, then beyond a certain amount of current knowledge (considering that as the input to the process), the person effectively cannot continue with it... so that compromises the universality.
They must be able to create, recognize and understand any given explanation, and maintain that ability as their knowledge grows, ad infinitum...
#4839·Dennis HackethalOP, 7 days agoMaybe I’m misunderstanding you, but that’s how standing bounties work already.
When you fund a standing bounty, you set the number of criticisms you’re willing to pay for, and the amount for each.
If that’s something you want to do for your current bounty, you still can, before current funding runs out.
See also “How Do Bounties Work?”
Yeah, I'm not sure why I wrote this... I remember the option for number of criticisms now. I guess it slipped my mind.
#4260·Dennis HackethalOP, 2 months agoA concept or idea with no experiential grounding is meaningless.
Maybe, but that’s different from confusing a parochial factor for a fundamental one.
Could you elaborare? Is the point that physical experience, metaphors and other things that ground ideas don’t constrain the reach of ideas at all or only partially?
"Understanding" isn't just another way of saying "can explain." An RNG could by chance generate a good explanation, but it doesn't understand it, and therefore can't distinguish it from garbage. Understanding involves recognizing that something is a good explanation. It is conscious understanding that makes conjecture and criticism possible. Without it, you have no criticism, only random selection. What do you think of the suggestion that what's lacking from the explanatory universality definition, is an intelligent selection mechanism. A random program can generate any explanation given infinite time, but it will never select which explanation is good.
"Understanding" isn't just another way of saying "can explain.". Explaining follows from understanding, but isn't synonymous. An RNG could by chance generate a good explanation, but it doesn't understand it, and therefore can't distinguish it from garbage. Understanding involves recognizing that something is a good explanation. It is conscious understanding that makes conjecture and criticism possible. Without it, you have no criticism, only random selection. What do you think of the suggestion that what's lacking from the explanatory universality definition, is an intelligent selection mechanism. A random program can generate any explanation given infinite time, but it will never select which explanation is good.
#4808·Tyler MillsOP, 8 days agoMaybe... but "understanding" is too vague, I think. Doesn't understanding mean: can explain? But then this is just "can create any explanation" again. I think the core question is why a random program generator isn't a person, coming from Deutsch's definition of a person as a program that has explanatory universality -- can create any explanation (my thought here is that this definition isn't good enough on its own, given the random generator point).
"Understanding" isn't just another way of saying "can explain." An RNG could by chance generate a good explanation, but it doesn't understand it, and therefore can't distinguish it from garbage. Understanding involves recognizing that something is a good explanation. It is conscious understanding that makes conjecture and criticism possible. Without it, you have no criticism, only random selection. What do you think of the suggestion that what's lacking from the explanatory universality definition, is an intelligent selection mechanism. A random program can generate any explanation given infinite time, but it will never select which explanation is good.