5 ms·

Unfortunately, the reason why it seems like arguing about the definition of a word is that there are there are more concepts at play here than we have words to

Unfortunately, the reason why it seems like arguing about the definition of a word is that there are there are more concepts at play here than we have words to describe them. When people talk about information as in information theory, what they're talking about is devoid of actual semantic contact, but when normal people people talk about information, that normally implies some sort of semantic content.

yters 7y ago
Information theory addresses semantics through mutual information. 'Meaning' entails reference, and when A refers to B they have mutual information. Mutual information is how Shannon measures the carrying capacity of a channel.
- westoncb 7y ago
  This is still just talking about a property of information that resembles one aspect of what's meant by "meaning". This is all still purely structural and independent of semantic content. The example given above about alternate interpretations of the same bit string on a USB drive gets at the problem. Semantics is about the process of interpreting data into something "meaningful" to some particular system (e.g. a human). It's essentially an importing process: converting data to a format that some system knows how to operate on (i.e. "understands). To keep it brief, meaning (or "information" in the non-jargon sense) is about a relation between some data and a system which that data operates on (or the system operates on the data, depending on how you look at it). "information" from information theory is an intrinsic property of data[0]: the information content doesn't change based on what's interpreting it. (At least that's my understanding.) [0] I'm using "data" here to refer to something like a serialization of a system into a form where information-theoretical analysis can be applied to it (e.g. like a bit string).
  - yters 7y ago
    Like I mentioned previously, there are objective sufficient criteria to identify meaning. Even if the interpretive context is subjective. So, we can guarantee true positives, even if we cannot guarantee true negatives.
    - westoncb 7y ago
      > there are objective sufficient criteria to identify meaning You have just shifted the problem by now using a very specific, narrow definition of "meaning" rather than doing so with "information". The objective sufficient criteria to identify meaning only work because this definition of meaning refers to an intrinsic property of a system; however, the common usage of "meaning" involves a relation between multiple systems.
      - yters 7y ago
        Not sure what you are saying. Informative content has both intrinsic (randomness deficiency, entropy, kolmogorov sufficient statistic) and relational properties (also randomness deficiency, mutual information, algorithmic mutual information) that can be objectively and quantitatively measured.
        westoncb 7y ago
        Intrinsic/relational may not be the best way of getting at it after all. It would likely regress into an equally involved question on defining "system". So let me try another approach. We need to distinguish between information and the "semantic content" of information. Here are the definitions I have in mind: - Data: an arbitrary string - Information: a numeric property of some data: INFO(d) - Mutual information: a numeric property of two pieces of data: MI(d1, d2) - Semantic content: the particular "effect on a system"[0] that results when the system internalizes the data: SC(s, d) ('s' denotes the system.) My understanding is that you're claiming MI == SC. There are certain ways we could fiddle with my usage of 'system' above so that it can just be 'data,' too (e.g. representing the system as a string, as with Turing Machines that operate on string reps of Turing Machines). In which case we can at least say that MI and CS both have domains like (data X data), so there is some similarity there. But, even just the fact that MI is going to evaluate to a single numeric quantity, while SC evaluates to an "effect on a system" (i.e. following a state transition), implies that they're referring to different things. I think it's also clear that it would be possible for MI(d1, d2) to evaluate to the same number as MI(d3, d4), even though SC(d1, d2) !== SC(d3, d4), since all the informational relations could be equivalent (between (d1, d2) and (d3, d4)), and yet the particular state transitions followed could differ. [0] We can make this more precise. For instance, in the language of automata theory it would be something like following a particular state transition. Edit: I should clarify one implicit thing here: this hinges on an assumption that my definition of "semantic content" would be a satisfactory match to common usage of the phrase for most people. Happy to hear an alternate that also captures common usage, and I can expand on my choice of def.

yters 7y ago

Information theory addresses semantics through mutual information. 'Meaning' entails reference, and when A refers to B they have mutual information. Mutual information is how Shannon measures the carrying capacity of a channel.

westoncb 7y ago
This is still just talking about a property of information that resembles one aspect of what's meant by "meaning". This is all still purely structural and independent of semantic content. The example given above about alternate interpretations of the same bit string on a USB drive gets at the problem. Semantics is about the process of interpreting data into something "meaningful" to some particular system (e.g. a human). It's essentially an importing process: converting data to a format that some system knows how to operate on (i.e. "understands). To keep it brief, meaning (or "information" in the non-jargon sense) is about a relation between some data and a system which that data operates on (or the system operates on the data, depending on how you look at it). "information" from information theory is an intrinsic property of data[0]: the information content doesn't change based on what's interpreting it. (At least that's my understanding.) [0] I'm using "data" here to refer to something like a serialization of a system into a form where information-theoretical analysis can be applied to it (e.g. like a bit string).
- yters 7y ago
  Like I mentioned previously, there are objective sufficient criteria to identify meaning. Even if the interpretive context is subjective. So, we can guarantee true positives, even if we cannot guarantee true negatives.
  - westoncb 7y ago
    > there are objective sufficient criteria to identify meaning You have just shifted the problem by now using a very specific, narrow definition of "meaning" rather than doing so with "information". The objective sufficient criteria to identify meaning only work because this definition of meaning refers to an intrinsic property of a system; however, the common usage of "meaning" involves a relation between multiple systems.
    - yters 7y ago
      Not sure what you are saying. Informative content has both intrinsic (randomness deficiency, entropy, kolmogorov sufficient statistic) and relational properties (also randomness deficiency, mutual information, algorithmic mutual information) that can be objectively and quantitatively measured.
      - westoncb 7y ago
        Intrinsic/relational may not be the best way of getting at it after all. It would likely regress into an equally involved question on defining "system". So let me try another approach. We need to distinguish between information and the "semantic content" of information. Here are the definitions I have in mind: - Data: an arbitrary string - Information: a numeric property of some data: INFO(d) - Mutual information: a numeric property of two pieces of data: MI(d1, d2) - Semantic content: the particular "effect on a system"[0] that results when the system internalizes the data: SC(s, d) ('s' denotes the system.) My understanding is that you're claiming MI == SC. There are certain ways we could fiddle with my usage of 'system' above so that it can just be 'data,' too (e.g. representing the system as a string, as with Turing Machines that operate on string reps of Turing Machines). In which case we can at least say that MI and CS both have domains like (data X data), so there is some similarity there. But, even just the fact that MI is going to evaluate to a single numeric quantity, while SC evaluates to an "effect on a system" (i.e. following a state transition), implies that they're referring to different things. I think it's also clear that it would be possible for MI(d1, d2) to evaluate to the same number as MI(d3, d4), even though SC(d1, d2) !== SC(d3, d4), since all the informational relations could be equivalent (between (d1, d2) and (d3, d4)), and yet the particular state transitions followed could differ. [0] We can make this more precise. For instance, in the language of automata theory it would be something like following a particular state transition. Edit: I should clarify one implicit thing here: this hinges on an assumption that my definition of "semantic content" would be a satisfactory match to common usage of the phrase for most people. Happy to hear an alternate that also captures common usage, and I can expand on my choice of def.