Claude Shannon: Tinkerer, Prankster, and Father of Information Theory (2016)

> At the banquet, the meeting’s organizers somehow persuaded Shannon to address the audience. He spoke for a few minutes and then—fearing that he was boring his audience, he recalled later—pulled three balls out of his pockets and began juggling.

Shannon was famous for his entropy.

I think it’s a different thing but an interesting analog. In conventional information theory you can add another channel. I guess the social media metaphor is like crowded wifi or if I’m being clever alohanet... question is, how do we add another channel here?if you’re talking about social discourse rather than a physical medium are we talking about the necessity of class hierarchy? Is this what the Tower of Babel was about?

> Doesn't that feel like a repeat with whats happening in social media and news media these days? Or is it just different things.

Maybe. It can feel like this, but applying mathematical models to social phenomena is tricky. You have to map formal parameters to fuzzy, poorly understood factors. How do you define, precisely, what is a "channel" on a social network? What is "signal", and what is "noise"? People can and do prove anything by using slightly different (or inconsistent) definitions here, getting the numbers to line up just like they want them to.

My understanding is that a better way to approach such mapping would be to shove in probability distributions in place of hard-to-map exact parameters - abstracting away choices and measurements lets you see the wider context here. This pushes the problem to defining the appropriate distributions, but I think that's more tamper-proof. Unfortunately, the results may come out next to useless - e.g. probability distributions so wide you could sail a carrier strike group through them.

I'd love to know what's considered the correct, robust approach to such problems.

I think the social media issue has more to do with the heavy application of ML curation to feeds and ads creating feedback loops where people are really talking to themselves using a computer rather than other people who might confront them.

Your analogy doesn't sound far off from what information theory describes. Still, we need to be cautious of applying information theory to areas in which it might be over extended and may not be suitable. Claude Shannon himself was aware of this trend and wrote his essay "The Bandwagon" [1] urging caution and diligence in applying information theory to different fields.

[1]. https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=1056774

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.

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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".

The timing is a little less funny if you know that I listened to the podcast shortly before finding the IEEE article.

The podcast was great! I would think that many on HN would find it interesting.

It was so endearing to head about Shannon spending his time as an illustrious academic learning to juggle, then unicycle, then both at the same time.

I also enjoyed "A Mind at Play".

I had forgotten (or never fully appreciated) what Shannon did and what other early pioneers did in computing. I have a better appreciation for all of them now.

One other highlight was Shannon's early childhood and using electrified fencing to communicate with others in his farmland neighborhood.

Here's a very so-so promo site for The Bit Player. I saw it about a year ago (Curiosity Stream) and thought it was pretty decent. I somewhat sheepishly admit that, for a while, I thought that they had somehow interviewed the real Claude Shannon.

https://thebitplayer.com/

Although not devoted to Claude Shannon, Jim Al-Khalili's documentary "The Story of Information" does discuss Shannon's significant contributions and is how I first became aware of Claude Shannon.

https://topdocumentaryfilms.com/story-information/

Nothing I've read about Shannon suggests that he felt "cursed" in his later life. Is there some reason to think otherwise, or is this just assuming that anybody who does something big early feels sad about it later?