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One key insight of Shannon's is that to study information as he did, you need to remove "meaning". You could measure the information content of anything and it doesn't matter what the symbols mean. Paradoxically, a random sequence of characters of the same length as this message would contain more information than this message that I am writing. --- The connection you draw to social media is cute, and I think it could help as an analogy in some cases. The Bit Player (2018 movie) makes a similar cute analogy to robust communication in marriage, that rather than saying the same message louder (yelling) or repeating the message (nagging), you should find many different ways to say the same message. And you could add an error-correcting code like "I love you". I personally think it's a cute (not disparaging) way to think about communication among humans, but note that we still need to rely heavily on meaning, to decide what it even means to say the same message with different words. What goes on with social media can be seen through lenses such as decision theory, and game theory, and graph theory, ..., and I think those fields have more to offer from the get-go than information theory. In any case, I personally would lean heavily on social science to try to get a better understanding of social situations, and to consider possible "interventions". In particular, I do not think the kinds of communication errors that occur between humans are the same as e.g. bit flips. And to go back to the original point, it's tempting to conflate "information" (as in information theory) with "knowledge", or "understanding", or "truth". |
Ted Chiang could probably write a plausible future with that as a writing prompt.