A higher quality intelligence than us might, among other things, use better heuristics and more difficult analytical concepts than we can, recognize more complex relationships than we can, evaluate its expected utility in a more consistent and unbiased manner than we can, envision more deeply nested plans and contingencies than we can, possess more control over the manner in which it thinks than we can, and so on.
A more general intelligence than us might simply have more hardware dedicated to general computation, regardless of what it does with that general ability.
I am trying to turn this concept of Quality Intelligence into something more precise.
Here are some items from history which most people will think of as improvements in quality intelligence.
I am thinking about quality with the context of collective intelligence. The concept of AGI = the intelligence of a single human I do not find useful for predicting a recursively improving system, for reasons we can look at later.
Development of symbolic language from pictographs
Development of the number zero
Development of set theory
Invention of calculus
Development of Newton’s method for approximating functions
Invention of Bayes’ Rule
Matrix theory
Closed-form solutions to many kinnds of partial differential equations
Procedural programming languages
Approximations to vast numbers of functions using Newton’s method on computers (Quality or Quantity?)
These are advances in reasoning and improve intelligence quality.
I am not sure whether to chalk up the following to advances in quality intelligence, or not:
Formulation of gravity
Development of the periodic table
General relativity
Demonstration of nuclear fission
Development of the transistor
Discovery of DNA
Development of the microprocessor (Quality or quantity, or both?)
Mechanisms of transcription and translation within the cell.
Certainly, figuring all of these things out about the real world advanced our ability to solve practical problems. I am inclined to consider the distinction between them and the discoveries in logic, computer programming and applied math somewhat arbitrary.
In practice for “quality” we normally have a yardstick for performance which is being improved continuously (e.g. success probability, quality of a solution to an optimization problem, ability to win in a game), while for generality there is often no such yardstick. At best this seems like a difference of degrees rather than a difference in kind though.
I don’t know if there is some more convincing distinction. I can’t think of any arguments that depend on a distinction.
Perhaps a more general intelligence can do well in a wider variety of circumstances, whereas a higher quality intelligence can do better in those circumstances, by seeing better solutions etc rather than just being faster.
Bostrum unsatisfactorily defines quality superintelligence in a self referencing circle by vastly qualitatively smarter (p56). It would have been better to name the ability to solve problems of vastly higher complexity.
Intelligence of higher generality covers more domains.
You can improve in intelligence by generalizing (‘My intelligence improved in generality’), or by further investing in what you’re good at (‘My intelligence improved without improving in generality’). It seems like we could mean two different things by ‘generalizing’.
Suppose four skills exist, A,B,C,D; and my skill level can either be low (0), mediocre (1), high (2), or very high (3). If I start off with A=0, B=1, C=2, D=2, then ‘generalizing’ might mean improving A or B more than I improve C or D. Alternatively, ‘generalizing’ might mean improving in more skills, rather than in just one. On the former conception, ‘raise A to 2’ increases my intelligence’s generality more than ‘raise C to 3 and D to 3’; on the latter conception, the reverse is true. There’s plug-the-gaps generalization, where you try to get rid of your weak points; but there’s also spread-the-love generalization, where you try to find self-improvements that will impact your problem-solving ability in as diverse a range of problems as possible.
‘Qualitative intelligence improvements’ seems like a grab-bag for ‘all the kinds of intelligence improvements that we don’t usually measure in any simple and direct way’. We routinely talk about, e.g., the speed, number, and computing power of computers, in terms of simple numerical values; we don’t routinely do the same for computers’ language-processing abilities, so that goes in the ‘qualitative’ bag, at least for the moment. Improving in qualitative intelligence could take almost any form; it seems like a less natural category than ‘generality’.
What’s the difference between intelligence being ‘higher quality’, and being more ‘general’?
A higher quality intelligence than us might, among other things, use better heuristics and more difficult analytical concepts than we can, recognize more complex relationships than we can, evaluate its expected utility in a more consistent and unbiased manner than we can, envision more deeply nested plans and contingencies than we can, possess more control over the manner in which it thinks than we can, and so on.
A more general intelligence than us might simply have more hardware dedicated to general computation, regardless of what it does with that general ability.
I am trying to turn this concept of Quality Intelligence into something more precise.
Here are some items from history which most people will think of as improvements in quality intelligence.
I am thinking about quality with the context of collective intelligence. The concept of AGI = the intelligence of a single human I do not find useful for predicting a recursively improving system, for reasons we can look at later.
Development of symbolic language from pictographs Development of the number zero Development of set theory Invention of calculus Development of Newton’s method for approximating functions Invention of Bayes’ Rule Matrix theory Closed-form solutions to many kinnds of partial differential equations Procedural programming languages Approximations to vast numbers of functions using Newton’s method on computers (Quality or Quantity?) These are advances in reasoning and improve intelligence quality.
I am not sure whether to chalk up the following to advances in quality intelligence, or not: Formulation of gravity Development of the periodic table General relativity Demonstration of nuclear fission Development of the transistor Discovery of DNA Development of the microprocessor (Quality or quantity, or both?) Mechanisms of transcription and translation within the cell.
Certainly, figuring all of these things out about the real world advanced our ability to solve practical problems. I am inclined to consider the distinction between them and the discoveries in logic, computer programming and applied math somewhat arbitrary.
In practice for “quality” we normally have a yardstick for performance which is being improved continuously (e.g. success probability, quality of a solution to an optimization problem, ability to win in a game), while for generality there is often no such yardstick. At best this seems like a difference of degrees rather than a difference in kind though.
I don’t know if there is some more convincing distinction. I can’t think of any arguments that depend on a distinction.
Perhaps a more general intelligence can do well in a wider variety of circumstances, whereas a higher quality intelligence can do better in those circumstances, by seeing better solutions etc rather than just being faster.
Goertzel 2006, p43
Bostrum unsatisfactorily defines quality superintelligence in a self referencing circle by vastly qualitatively smarter (p56). It would have been better to name the ability to solve problems of vastly higher complexity.
Intelligence of higher generality covers more domains.
You can improve in intelligence by generalizing (‘My intelligence improved in generality’), or by further investing in what you’re good at (‘My intelligence improved without improving in generality’). It seems like we could mean two different things by ‘generalizing’.
Suppose four skills exist, A,B,C,D; and my skill level can either be low (0), mediocre (1), high (2), or very high (3). If I start off with A=0, B=1, C=2, D=2, then ‘generalizing’ might mean improving A or B more than I improve C or D. Alternatively, ‘generalizing’ might mean improving in more skills, rather than in just one. On the former conception, ‘raise A to 2’ increases my intelligence’s generality more than ‘raise C to 3 and D to 3’; on the latter conception, the reverse is true. There’s plug-the-gaps generalization, where you try to get rid of your weak points; but there’s also spread-the-love generalization, where you try to find self-improvements that will impact your problem-solving ability in as diverse a range of problems as possible.
‘Qualitative intelligence improvements’ seems like a grab-bag for ‘all the kinds of intelligence improvements that we don’t usually measure in any simple and direct way’. We routinely talk about, e.g., the speed, number, and computing power of computers, in terms of simple numerical values; we don’t routinely do the same for computers’ language-processing abilities, so that goes in the ‘qualitative’ bag, at least for the moment. Improving in qualitative intelligence could take almost any form; it seems like a less natural category than ‘generality’.