Answers.Body: <blockquote>
    <p>Is randomness (either true randomness or simulated randomness) necessary for AI</p>
  </blockquote>
  
  <p>It depends on how you define Artificial Intelligence.  If you regard it strictly as an intentionally created construct which demonstrates utility, then no.  (For instance, <a href="https://en.wikipedia.org/wiki/Nimatron" rel="nofollow noreferrer">Nimatron</a>, potentially the first functioning AI, beat most human competitors at NIM.  But Nimatron was classical AI, entirely rules based with no learning.) That said:</p>
  
  <ul>
  <li><strong>Randomness has proved a useful component in machine learning, and any feasible AGI would likely require ML.</strong>  </li>
  </ul>
  
  <p>Given sufficient computing power, aka time and space, it would absolutely be possibly to brute force anything, including AGI, but the resulting algorithm would be "brittle", unable to "compute" anything not previously defined. A learning algorithm, presented a problem outside of its domain of knowledge may initially degrade in performance, but it can learn from those outcomes, and gradually improve performance.</p>
  
  <p><em>IBM brute forced Chess with <a href="https://en.wikipedia.org/wiki/Deep_Blue_(chess_computer)#Design" rel="nofollow noreferrer">Deep Blue</a>, but Chess is a strictly narrow problem that turned out not to require general intelligence.  AGI requires human level performance in all tasks engaged in by humans, which, even if they could be broken down to a set of individual narrow problems, it's an ever expanding set of problems.</em></p>
  
  <blockquote>
    <p>Does it mean "intelligence comes from randomness"? </p>
  </blockquote>
  
  <p>Not if the definition of intelligence is rooted in utility because deterministic processes can demonstrate utility. </p>
  
  <ul>
  <li><strong>In statistical AI, the intelligence arises from the analysis of random search or the fitness of the genetic algorithm, not the randomness per se.</strong>  </li>
  </ul>
  
  <p>In other words, if you have the randomness without the analysis, every decision is an unqualified guess. </p>
  
  <p><em>My sense is that it is free will that would arise from randomness—effects unrelated to causes—because without true randomness, the universe and everything in it is purely deterministic.</em></p>
  
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Answers.CreationDate: 2019-09-23T23:49:11.127Z
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Answers.LastEditDate: 2019-09-24T00:19:48.940Z
Answers.UserDisplayName: DukeZhou
Answers.Body: <p>Yes, randomness is necessary to achieve generality in theory. Right now AIs we have are on the basis of seeking pattern and use them to predict future moves or outcomes. If we don't include randomness in data then machine might consider that as pattern and behave according to that (Which will be bias for us).
  Generating random numbers is a different story in itself and won't be a criterion alone to judge. While this might be one of the conditions for sure.</p>
  
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Answers.CreationDate: 2019-09-23T21:12:42.833Z
Answers.Text: Brute force (exhaustion) would not more limited than random composition--in both cases there would still be the same number of potential configurations. Only the approach to forming them is different. (See "The Library of Babel")  But there is still the "needle in the haystack" problem, and the statistical approach has proven effective where brute force is insufficient.
Answers.UserDisplayName: DukeZhou
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Answers.CreationDate: 2019-09-23T23:50:50.370Z
Answers.Text: Why it will be a limited number of stories to come up with? Given word 0 and word 1 we can generate all (which is infinite) binary stories without randomness.
Answers.UserDisplayName: lambda
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Answers.UserDisplayName: Rajat Paliwal
Answers.Body: <ol>
  <li><p>It might be too philosophical answer, but maybe first we need to answer the question whether a human way of thinking or his creativeness includes random elements. For example if an author writing a book uses some randomness in developing some side thread or some episodic character and I would say, that yes - sometimes we think up of something random.</p></li>
  <li><p>Some algorithms uses randomness at their basis, for example evolutionary algorithms for generating first population.</p></li>
  </ol>
  
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Answers.CreationDate: 2019-09-23T21:10:31.047Z
Answers.Text: All machine learning algorithms that have proven effective seem to use the statistical approach, which definitely involves randomness.  So not just genetic algorithms, NNs in all of their flavors, native Bayes, et al.
Answers.UserDisplayName: DukeZhou
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Answers.Text: I think the randomness we observe in human decision may not be true randomness, it may just be a function taking history, environment as arguments which is too complicated that it behaves like random function.
Answers.UserDisplayName: lambda
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Answers.UserDisplayName: GKozinski
Body: <p>Is randomness (either true randomness or simulated randomness) necessary for AI? If true, does it mean "intelligence comes from randomness"? 
  If not, can a robot lacking the ability to generate random numbers be called an artificial general intelligence?</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2019-09-23T12:33:25.117Z
Comments.Text: What do you mean by "necessary for AI"? I know it may seem obvious, but I think you should be more explicit and clear.
Comments.UserDisplayName: nbro
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Comments.CreationDate: 2019-09-23T19:30:53.930Z
Comments.Text: This is a good core question, in that the statistical approach to AI, which allows machine learning, has eclipsed GOFAI, but it might be useful to elaborate a little in the question.  Pseudo-random number generation may not be entirely sufficient, in that, given sufficient time/iterations, it would result in unintended bias.
Comments.UserDisplayName: DukeZhou
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Comments.CreationDate: 2019-09-25T09:48:35.763Z
Comments.Text: Even if the claim - *randomness being necessary for AI*- is true, how does the question *does it mean intelligence comes from randomness*  follow?
Comments.UserDisplayName: naive
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Comments.CreationDate: 2019-09-25T09:53:33.937Z
Comments.Text: Being able to generate random numbers does not imply intelligence, not even close to it. Intelligence might follow from the *why* of random number generation. That *why* is generally coded in the models for AI such as in neural networks by a human - and that is for weights and bias initialization which in turn is essential for solving the optimization problem using gradient descent.
Comments.UserDisplayName: naive
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2020-02-27T15:48:03.503Z
Comments.Text: we're probably missing words here. randomness is the apparent lack of pattern or predictability in events. the more predictable something is, the dumber it becomes. of course just a bunch of random numbers doesn't make anything intelligent. it's much to the opposite: randomness is an artifact of intelligence. but if while we're reverse engineering intelligence (making ai) we can in practice see it does need rng to exist, then there's evidently something there between randomness and intelligence that's not just artifacts. could we call it chaos? rather continue there: https://cregox.net/random
Comments.UserDisplayName: cregox
Tags: <philosophy><randomness>
Title: Is randomness necessary for AI?
UserDisplayName: lambda
ThreadText: # Is randomness necessary for AI?
  
  (Asked by: username_0 on 2019-09-23)
  
  Is randomness (either true randomness or simulated randomness) necessary for AI? If true, does it mean "intelligence comes from randomness"?
  If not, can a robot lacking the ability to generate random numbers be called an artificial general intelligence?
  
  **Tags:** philosophy, randomness
  
  > **Comments:**
  > **username_1**: What do you mean by "necessary for AI"? I know it may seem obvious, but I think you should be more explicit and clear.  
  > **username_2**: This is a good core question, in that the statistical approach to AI, which allows machine learning, has eclipsed GOFAI, but it might be useful to elaborate a little in the question.  Pseudo-random number generation may not be entirely sufficient, in that, given sufficient time/iterations, it would result in unintended bias.  
  > **username_3**: Even if the claim - *randomness being necessary for AI*- is true, how does the question *does it mean intelligence comes from randomness*  follow?  
  > **username_3**: Being able to generate random numbers does not imply intelligence, not even close to it. Intelligence might follow from the *why* of random number generation. That *why* is generally coded in the models for AI such as in neural networks by a human - and that is for weights and bias initialization which in turn is essential for solving the optimization problem using gradient descent.  
  > **username_4**: we're probably missing words here. randomness is the apparent lack of pattern or predictability in events. the more predictable something is, the dumber it becomes. of course just a bunch of random numbers doesn't make anything intelligent. it's much to the opposite: randomness is an artifact of intelligence. but if while we're reverse engineering intelligence (making ai) we can in practice see it does need rng to exist, then there's evidently something there between randomness and intelligence that's not just artifacts. could we call it chaos? rather continue there: https://username_4.net/random  
  
  ---
  
  ## 3 answers
  
  ### Answer by username_2 on 2019-09-23. Score: 3
  
  > Is randomness (either true randomness or simulated randomness) necessary for AI
  
  It depends on how you define Artificial Intelligence. If you regard it strictly as an intentionally created construct which demonstrates utility, then no. (For instance, [Nimatron](https://en.wikipedia.org/wiki/Nimatron), potentially the first functioning AI, beat most human competitors at NIM. But Nimatron was classical AI, entirely rules based with no learning.) That said:
  
  * **Randomness has proved a useful component in machine learning, and any feasible AGI would likely require ML.**
  
  Given sufficient computing power, aka time and space, it would absolutely be possibly to brute force anything, including AGI, but the resulting algorithm would be "brittle", unable to "compute" anything not previously defined. A learning algorithm, presented a problem outside of its domain of knowledge may initially degrade in performance, but it can learn from those outcomes, and gradually improve performance.
  
  *IBM brute forced Chess with [Deep Blue](https://en.wikipedia.org/wiki/Deep_Blue_(chess_computer)#Design), but Chess is a strictly narrow problem that turned out not to require general intelligence. AGI requires human level performance in all tasks engaged in by humans, which, even if they could be broken down to a set of individual narrow problems, it's an ever expanding set of problems.*
  
  > Does it mean "intelligence comes from randomness"?
  
  Not if the definition of intelligence is rooted in utility because deterministic processes can demonstrate utility.
  
  * **In statistical AI, the intelligence arises from the analysis of random search or the fitness of the genetic algorithm, not the randomness per se.**
  
  In other words, if you have the randomness without the analysis, every decision is an unqualified guess.
  
  *My sense is that it is free will that would arise from randomness—effects unrelated to causes—because without true randomness, the universe and everything in it is purely deterministic.*
  
  
  ---
  
  ### Answer by username_5 on 2019-09-23. Score: 2
  
  Yes, randomness is necessary to achieve generality in theory. Right now AIs we have are on the basis of seeking pattern and use them to predict future moves or outcomes. If we don't include randomness in data then machine might consider that as pattern and behave according to that (Which will be bias for us).
  Generating random numbers is a different story in itself and won't be a criterion alone to judge. While this might be one of the conditions for sure.
  
  > **Comments:**
  > **username_2**: Brute force (exhaustion) would not more limited than random composition--in both cases there would still be the same number of potential configurations. Only the approach to forming them is different. (See "The Library of Babel")  But there is still the "needle in the haystack" problem, and the statistical approach has proven effective where brute force is insufficient.  
  > **username_0**: Why it will be a limited number of stories to come up with? Given word 0 and word 1 we can generate all (which is infinite) binary stories without randomness.  
  
  ---
  
  ### Answer by username_6 on 2019-09-23. Score: 1
  
  1. It might be too philosophical answer, but maybe first we need to answer the question whether a human way of thinking or his creativeness includes random elements. For example if an author writing a book uses some randomness in developing some side thread or some episodic character and I would say, that yes - sometimes we think up of something random.
  2. Some algorithms uses randomness at their basis, for example evolutionary algorithms for generating first population.
  
  > **Comments:**
  > **username_2**: All machine learning algorithms that have proven effective seem to use the statistical approach, which definitely involves randomness.  So not just genetic algorithms, NNs in all of their flavors, native Bayes, et al.  
  > **username_0**: I think the randomness we observe in human decision may not be true randomness, it may just be a function taking history, environment as arguments which is too complicated that it behaves like random function.  
  
  ---
  
  