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Disagree: even in your formulation, no 'quick jump' is needed. Your statement A:"The longer something has been around, the longer it will be around" is not the

• PaulDavisThe1st 4y ago
  The real meaning of the Lindy effect is: the more something has been continued to be around due to be continuously and repeatedly selected from a pool of similar other somethings, the longer it will likely continue to be so. Because this is a statistical effect (longer lived things are drawn from a pool of things, some of which are not long lived), you cannot invert it trivially. If there is no selection process, then the Lindy effect is either meaningless, or decomposes to an assertion that the current thing is the only way to do something.
  • feral 4y ago
    Ok, so let's say discuss your formulation instead: Why can't we 'invert' it, just because it's statistical effect? Yes, in your formulation, some of the new things in the pool will go on to live a long time, while others will be selected out. But so what? We are talking about the expected lifetime of an item in the pool, conditioned only on it's age. There's no fundamental problem making a statement that this expected lifetime is short for new things, even if some fraction of those new things will last a long time, right? After all, we don't know any one individual item that's been around a long time will last a lot longer. We only know we expect it to. Because even long lived items have finite lifetime, hence they'll eventually die (and when they do it'll be really surprising, because they've been around so long; but it will happen eventually.) And so the statement is always talking about expected lifetime, whether for items that have already lasted a long or short time. (Hence I still don't think there's really any logical 'inversion' here.)
    • PaulDavisThe1st 4y ago
      > There's no fundamental problem making a statement that this expected lifetime is short for new things, even if some fraction of those new things will last a long time, right? Everything that's new in the pool might be better than everything that's old. All you can say about the old stuff is that it was better (by some metric(s)) than anything it had to compete with so far. But you can't say anything about the new stuff. Sure, statistically it is likely that it will some blend of bad, middling and good, but you don't actually know the mix, or which term describes which items, until after the selection process (i.e. time) has taken place.
      • feral 4y ago
        Absolutely there are real situations where the new stuff is going to last longer than the old stuff, even the old stuff that's been through a selection process. E.g. modern manufacturing techniques have improved overall longevity of all 2022 models. But I think you are outside the Lindy effect model at that point. To put this in the example of the original post: The author says visual studio code is expected to last less time than VIM. You could counter by saying: "hey, maybe, uh, the rise of Product Management as a discipline has meant that modern software overall will have longer lifetimes, and hence it's not fair to guess that VIM will outlive VSCode". And that'd be a fine position. But imo the right way to frame that isn't "the author did an incorrect logical inversion of the Lindy effect model"; rather it would be "I don't think the Lindy effect model applies to this domain". (No one is saying the Lindy model is universal.) I guess you could say you want to apply it only within a given year of software; so, we're happy to look backwards and apply the Lindy model to software written in 2011, but we've no idea how to think about the lifespan of software written in 2022, and aren't allowed make any inferences from software written before 2022. That's fine, but that's an additional constraint we've added, is outside the Lindy model, and, really, we're in "all models are wrong, some are useful" territory here, where I'd ask "is it really useful to throw away all that previous data? Wouldn't it be a better starting point to use the lifetimes of previous years as at least a prior?" And if you grant that, then I think theres no logical error here.
      • coldtea 4y ago
  • kilobit 4y ago
    Exactly. Suppose a piece of software remains around for another year with probability p, and for the sake of this example, that p is constant. Then if the software has been around for one year, the expected value of p is 50%. But if the software has been around for ten years, the expected value of p jumps to 0.5^(1/10) ≈ 93.3%. In this way, if a piece of software has been around for longer, then it has a greater chance of sticking around. In fact, the expected number of years it has left is indeed equal to the number of years it has already been around, as stated in the article. In practice this mechanism is more complicated, as all software is influenced by a changing environment, but this same idea is still at the core.
    • kuboble 4y ago
      > Then if the software has been around for one year, the expected value of p is 50%. But if the software has been around for ten years, the expected value of p jumps to 0.5^(1/10) ≈ 93.3%. This reasoning is incorrect. You have to take the distribution of p into account. In a world where almost every software has p=0.5 the software which has been around for 10 years is likely to have been lucky and not to have higher p.
  • skykooler 4y ago
    Old things that are still around are generally longer lived things. New things may or may not be longer lived. This means that if you sample old things that are still around, they are more likely on average to be longer lived than new things, because the short lived new things have not been weeded out yet.
    • Tyr42 4y ago
      It's like how the music of the 80s or whatever decade seems better when reviewing, as you can just listen to the albums which stood the test of time. And you forget about all the trash music.
    • leoff 4y ago
      But one can think of a counter example where all the new music are very high quality and will stay around for a long time (not saying this is likely to happen). Then the statement "the shorter something has been around, the shorter it will be around" is false.
  • rawoke083600 4y ago
    Make sense ! If you squint just enough you have also evolution there :)
• jgtrosh 4y ago
  The logical contrapositive to A is A' “if something dies off soon, there's a good chance it was a recent fad“. A makes sense, and A' makes equal sense, but B is claiming stuff about new tools for which we have no way of guessing the future.
• 867-5309 4y ago
  >If someone tells you "the longer a distance is, the more time it takes to walk it", that is exactly the same as "the shorter a distance is, the less time it takes to walk it"; there's no logical leap there. that's comparing A->B with A->B. comparing A->B with B->A would yield "the less time a distance takes to walk, the shorter that distance must be"
  • deleted 4y ago
    [deleted]
  • thaumasiotes 4y ago
    > that's comparing A->B with A->B Yes, that's the point. feral (your parent comment) has accurately observed that Etheryte (your grandparent comment) has mislabeled A->B as B->A. But feral is completely correct that "the more time something has already been around, the longer its future expected lifespan is" is exactly the same claim as "the less time something has already been around, the shorter its future expected lifespan is". Etheryte is making a pretty bizarre error; he seems to be under the impression that "a < b" is the opposite of "b > a".
• remram 4y ago
  Your logic is wrong. You could go to the Wikipedia page for contraposition and learn about this, rather than arguing in comments. To use your own example: You have to take a long time to walk a long distance. That doesn't mean you have to take a short time to walk a short distance.
  • mfcl 4y ago
    I think you are taking the Lindy effect too seriously. You basically only know one thing about something, which is how long it has been around. The things that come to life and die that you observe will be, on average, in the middle of their life. So if something has been around for five years, given no more information, your best bet is that it'll be around for another five years. One year? Another one year. Hopefully this explains well why the Lindy effect also says that something that's been around for a shorter period of time is more likely to disappear sooner.
    • deleted 4y ago
      [deleted]
    • remram 4y ago
      But this is not the only thing you observe. You can see many more things about those new products than simply the amount of time they have been around. You can see Notion come out, and go "wow, I find this good and I think it will keep being around and good for a while". Like the GP said, the fact that it is young doesn't mean it is doomed, or even that it is not good. The Lindy effect says nothing in that direction.
      • feral 4y ago
        > go "wow, I find this good and I think it will keep being around and good for a while". Sure, you can have a much richer model of the world than the Lindy model provides. >fact that it is young doesn't mean it is doomed, or even that it is not good. The Lindy effect says nothing in that direction. No; it says that young things are less likely to last than old things. If the average expectancy is small, sure it doesn't guarantee any one thing is doomed (some aren't) but it absolutely does tell you that most of them aren't going to last long. Imagine a friend tells you that they know someone who is planning to become a professional rock star when they leave school. They are probably not going to make it, because most people who try don't. You can't be sure, because some people do become rockstars. But it's not an error to be sceptical of their chances. If you hear they are still gigging after 3 years, even if they haven't made it yet, you are probably a tiny bit less sceptical. That all makes sense, right?
• Ygg2 4y ago
  The statement is A=>B. A implies B e.g. long life, implies longer life remaining. The moment you negate A, both positive B and negative B, satisfy implication. I.e. you can't claim shorter life implies shorter life remaining. For that to hold you need equivalency, not implication. Here is an example. Rain implies streets are wet. Does no rain implies streets are dry? No. There could be a flood or street cleaning, or a pipe burst.
  • thaumasiotes 4y ago
    You have somehow failed to understand what is being claimed. The Lindy effect says that entities with longer realized lifespans have longer expected future lifespans. In other words, if one thing has been around for 5 years, and another thing has been around for 3 years, then we know three things: 1: The first thing's expected future lifespan is f(5) years. 2: The second thing's expected future lifespan is f(3) years. 3: f(5) is greater than f(3). Etheryte claims, in a gross error, that this does not imply that the expected future lifespan of shorter-lived things is shorter than that of longer-lived things. This is ridiculous; the claim Etheryte denies is a simple restatement of the Lindy effect. For our two objects of ages 5 and 3 years, the "new" claim would tell us the following three things: 1': The expected future lifespan of the first thing is f(5) years. 2': The expected future lifespan of the second thing is f(3) years. 3': f(3) is less than f(5). But 1' is exactly the same claim as 1, 2' is exactly the same claim as 2, and 3' is exactly the same claim as 3. No claim has been negated, only repeated.
    • feral 4y ago
      I salute you, Thaumasiotes, great explanation.
    • Ygg2 4y ago
      Ok. But then you just proved Lindy effect is at best probabilistic, and most likely survivorship bias. Because it doesn't hold invariant to time. It's not hard to make a counterexample. E.g. when Windows 3.11 existed for several years and Microsoft published Windows 95. If we were to travel back then and use Lindy effect we would get wrong predictions. Because it's such a simple heuristic it only demonstrates one way effect.
• yowmamasita 4y ago
  I remember a rule in audio speakers which sounds similar to Lindy effect: bad distortion (>=10%) are bad sounding speakers, but the opposite of that isn't true (e.g 0.001% distortion can still be a bad speaker)