# Is the Lindy effect well supported by evidence?

The Lindy effect is the observation that, contrary to the pattern with perishable things like people, the longevity so far is a good predictor of the future longevity. In other words, technologies that have already survived a long time can be expected to continue to survive for a long time (whereas people who are old are likely to die soon).

Taleb argues thus in a recent Wired article:

For a perishable human, every year that elapses reduces his life expectancy by a little less than a year.

The opposite applies to non-perishables like technology and information. If a book has been in print for 40 years, I can expect it to be in print for at least another 40 years. But – and this is the main difference – if it survives another decade, then it will be expected to be in print another 50 years.

He isn't arguing that this is a perfect rule, just a good statistical estimate (so don't be too quick to provide single examples as answers!)

Given that this is a statistical generalization, is the weight of evidence in favour of the idea?

• It sounds like it's just a generalization from some things in experience. So it sounds like it's vacuously true of the kinds of things of which it is true. – Mike Dunlavey Mar 6 '13 at 0:39
• This is a heuristic estimate based on limited information for items that follow certain probability distributions (e.g. the lengths must spread over several magnitudes). It works as a rough estimate where there is no more available info than longevity. (Computer process longevity is another classic example.) It doesn't work where the probability distribution doesn't follow the assumptions. See also Half-Lives, Pareto, Long Tail, Benford's Law, etc. So what does it mean to have a "weight of evidence" behind it? It is easy to find examples that don't fit, but that doesn't invalidate it. – Oddthinking Mar 6 '13 at 8:13
• I'm not sure "good statistical estimate" paints the right picture; my understanding is that this kind of estimation is basically the weakest kind you can do, and it has many ways of failing (e.g. one of the grounding assumptions is that there's nothing particularly special about the current point in time - something which which is difficult to be sure of). So, it's perhaps better than nothing, but not necessarily "good". – Daniel B Mar 6 '13 at 9:23
• Given that some books do eventually go out of print, the Lindy effect cannot be valid in the way suggested for books. The Lindy effect is correct for the first half of the actual lifetime of an item and wrong for the last half of its lifetime. You never know which half you are in. – RedGrittyBrick Mar 6 '13 at 11:55
• @matt_black: Thanks for the clarification (I confess I'm still a bit in the dark). Are you sure stats.stackexchange.com isn't a better home for this question? – RedGrittyBrick Mar 6 '13 at 18:35

It's a model or approximation: which can be applied, more or less usefully, to some (a subset of) things.

It's supported by, for example:

• http://en.wikipedia.org/wiki/Burn-in means that an older/tested component, when it passes its short burn-in period, then has a longer subsequent life expectancy than a young/untested component which has not.

• http://en.wikipedia.org/wiki/Bathtub_curve suggests that the effect would be applicable to components which "don't wear out" ... or for which, the magnitude of the "wear out failures" is insignificant compared to the magnitude of the "infant mortality" failures.

I haven't read his book (Black Swan) but from the article you cited Mr. Taleb isn't even talking about "things", necessarily: for example it's about software, which doesn't "wear out" in a conventional way.

• +1 It's utility (if it has any) applies to collections not individuals. If I have 2000 things of the same type I can divide them into those that are older than the median age and those younger. I can expect that the old group represents robust survivors whose fragile peers have gone. I can predict that at today + median, the ratio of survivors of today's tough old group will exceed survivors of today's mixed young group. This probably applies to light bulbs in an office building. Whether you can benefit from this is moot. Lindy effect = able veterans are tougher than newborn. Obvious? – RedGrittyBrick Mar 6 '13 at 15:06

I can think of two major flaws in the Lindy effect concerning the longevity of non-perishable things:

1. We have witnessed a rapid (almost exponential) rate for advances and developments in technology and sciences in the last century (or in even in the last 50 years). This prevents us from suggesting any rules concerning what kind of technology or theory will last more. (Edit: As a reference to the above claim, one can consider Moore's law, proposed by Gordon E. Moore one of the co-founders of Intel, which asserts the advancements in electronic,specifically chip, industry is too fast that the number of chips doubles every two years. It is now so acceptable in the industry that experts use his theory for their forward-looking planning. See also Vinge's theory about exponentially accelerating changes for other evidences for the above point.)
2. The Lindy effect (and in some extent your question) rely on the assumption that the future can be predicted by the past events. There is certainly no scientific evidence or logical justification for this assumption about general events and consequently for the Lindy effect. Although induction is an accepted logic for scientific theories it is hardly acceptable for predicting future, as a philosopher (C. D. Broad) says "induction is the glory of science and the scandal of philosophy", see also the page Problem of Induction in wikipedia.
• Please provide some references to support your claims. – Oddthinking Mar 6 '13 at 8:07
• I'm not sure of the usual scope of the Lindy effect for broad technologies. Its not obviously wrong, though. The idea of the integrated circuit built on doped silicon is from the 1960s-70s and is reasonably likely to last a while. But the 8086 and the specific semiconductor technologies that built it have mostly gone. – matt_black Mar 6 '13 at 18:09
• As can be seen in the Wikipedia link "advancements in electronic,specifically chip, industry is too fast that the number of chips doubles every two years.", as well as being ungrammatical, is wrong. – Mark Hurd Mar 12 '13 at 5:28
• No, the Lindy effect do not rely on the assumption that future can be predicted. Quite the opposite: it states that it cannot be predicted, and that our only reliable data is the observed lifespan of an object, and the statistical probability that this objects is at its half-life. Suppose you meet an ET tomorrow, you have no idea about its age, you can only guess it is in the middle of its life, because it is the most probable (the middle of a bell curve). – gb. May 8 '13 at 4:37