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General artificial intelligence is inherently impossible, so why discuss its ramifications? No algorithm can create more information than is put into it, yet t

by yters 9y ago

General artificial intelligence is inherently impossible, so why discuss its ramifications? No algorithm can create more information than is put into it, yet the hallmark of human intelligence is the ability to create new information. The two are inherently different beasts.

Danihan 9y ago
>the hallmark of human intelligence is the ability to create new information. What's an example of this "new information" human intelligence creates?
- yters 9y ago
  An example I gave to the other commentator is humans can derive principles of play in these games that AIs are currently dominating. AIs have a very different method of playing, which amounts to memorizing a near perfect tactical response table. It seems like from a limited number of examples of A implying B, humans can infer that A always implies B, and can from there figure out A' implies C which is more favorable.
  - Danihan 9y ago
    I'm not sure that's new information. It's utilizing inferences. Basically, humans are much better at stereotyping / categorizing objects than machines currently are. But that could change (and is changing). Watson, for instance, seems pretty good at making inferences.
    - yters 9y ago
      In general, inference requires the creation of new information, in a Kolmogorov complexity sense. I.e. perfect inference uses Solmonoff induction, and Solomonoff induction is only possible with the ability to enumerate all elegant programs. But infinite Kolmogorov complexity is necessary to enumerate all elegant programs.
heartles 9y ago
This feels to me more like an ideological talking point than a statement with evidence to back it up. Can you explain what you mean when you say that human intelligence can create new information? My first thought is that humans can draw conclusions from information given to them, but that sounds more like deriving information from other information.
- yters 9y ago
  Yes, there is an element of derivation since we cannot create ex nihilo, but we can infer information that is not entirely implicit in a set of data. In the case of games that AIs are dominating, this is apparent in the difference between how AIs play vs how humans play. AIs essentially memorize a gigantic move valuation table, and scan an enormous number of moves, maximizing their tactical advantage. Humans, on the other hand, have learned principles of play and how to apply these to different scenarios, so are better at a strategic level. This is why humans can evaluate a much smaller number of moves. These principles are examples of new information humans have created. In some sense, the principles pre-exist in an abstract plane, as does every idea. However, the concrete actualization of the principle in the human mind and in application is the creation of information: the mutual information between a medium (mind or matter) and the abstract idea is being increased. This general principle inference ability that humans have is not something that can be done algorithmically. Essentially, I am claiming humans are able to violate the data processing inequality.

by yters 9y ago

Danihan 9y ago

>the hallmark of human intelligence is the ability to create new information. What's an example of this "new information" human intelligence creates?

yters 9y ago
An example I gave to the other commentator is humans can derive principles of play in these games that AIs are currently dominating. AIs have a very different method of playing, which amounts to memorizing a near perfect tactical response table. It seems like from a limited number of examples of A implying B, humans can infer that A always implies B, and can from there figure out A' implies C which is more favorable.
- Danihan 9y ago
  I'm not sure that's new information. It's utilizing inferences. Basically, humans are much better at stereotyping / categorizing objects than machines currently are. But that could change (and is changing). Watson, for instance, seems pretty good at making inferences.
  - yters 9y ago
    In general, inference requires the creation of new information, in a Kolmogorov complexity sense. I.e. perfect inference uses Solmonoff induction, and Solomonoff induction is only possible with the ability to enumerate all elegant programs. But infinite Kolmogorov complexity is necessary to enumerate all elegant programs.

heartles 9y ago

This feels to me more like an ideological talking point than a statement with evidence to back it up. Can you explain what you mean when you say that human intelligence can create new information? My first thought is that humans can draw conclusions from information given to them, but that sounds more like deriving information from other information.

yters 9y ago
Yes, there is an element of derivation since we cannot create ex nihilo, but we can infer information that is not entirely implicit in a set of data. In the case of games that AIs are dominating, this is apparent in the difference between how AIs play vs how humans play. AIs essentially memorize a gigantic move valuation table, and scan an enormous number of moves, maximizing their tactical advantage. Humans, on the other hand, have learned principles of play and how to apply these to different scenarios, so are better at a strategic level. This is why humans can evaluate a much smaller number of moves. These principles are examples of new information humans have created. In some sense, the principles pre-exist in an abstract plane, as does every idea. However, the concrete actualization of the principle in the human mind and in application is the creation of information: the mutual information between a medium (mind or matter) and the abstract idea is being increased. This general principle inference ability that humans have is not something that can be done algorithmically. Essentially, I am claiming humans are able to violate the data processing inequality.