Doomsday is Cancelled…

Posted in Bad Statistics, The Universe and Stuff with tags , on November 25, 2014 by telescoper

Last week I posted an item that included a discussion of the Doomsday Argument. A subsequent comment on that post mentioned a paper by Ken Olum, which I finally got around to reading over the weekend, so I thought I’d post a link here for those of you worrying that the world might come to an end before the Christmas holiday.

You can find Olum’s paper on the arXiv here. The abstract reads (my emphasis):

If the human race comes to an end relatively shortly, then we have been born at a fairly typical time in history of humanity. On the other hand, if humanity lasts for much longer and trillions of people eventually exist, then we have been born in the first surprisingly tiny fraction of all people. According to the Doomsday Argument of Carter, Leslie, Gott, and Nielsen, this means that the chance of a disaster which would obliterate humanity is much larger than usually thought. Here I argue that treating possible observers in the same way as those who actually exist avoids this conclusion. Under this treatment, it is more likely to exist at all in a race which is long-lived, as originally discussed by Dieks, and this cancels the Doomsday Argument, so that the chance of a disaster is only what one would ordinarily estimate. Treating possible and actual observers alike also allows sensible anthropic predictions from quantum cosmology, which would otherwise depend on one’s interpretation of quantum mechanics.

I think Olum does identify a logical flaw in the argument, but it’s by no means the only one. I wouldn’t find it at all surprising to be among the first “tiny fraction of all people”, as my genetic characteristics are such that I could not be otherwise. But even if you’re not all that interested in the Doomsday Argument I recommend you read this paper as it says some quite interesting things about the application of probabilistic reasoning elsewhere in cosmology, an area in which quite a lot is written that makes no sense to me whatsoever!


Farewell to Blackberry…

Posted in Uncategorized with tags , , , on November 24, 2014 by telescoper

I’m not really a great one for gadgets so I rarely post about technology. I just thought I’d do a quick post because the weekend saw the end of an era. I had been using a Blackberry smartphone for some time, the latest one being a Blackberry Curve, and even did a few posts on here using the WordPress App for Blackberry. I never found that particular bit of software very easy to use, however, so it was strictly for emergencies only (e.g. when stuck on a train). Other than that I got on pretty well with the old thing, except for the fact that there was no easy way to receive my work email from Sussex University on it. That has been a convenient excuse for me to ignore such communications while away from the internet, but recently it’s become clear that I need to be better connected to deal with pressing matters.

Anyway a few weeks ago I got a text message from Vodafone telling me I was due a free upgrade on my contract so I decided to bite the bullet, ditch the Blackberry and acquire an Android phone instead. I’m a bit allergic to those hideously overpriced Apple products, you see, which made an iPhone unthinkable.  On Saturday morning I paid a quick visit to the vodafone store in Cardiff and after a nice chat – mainly about Rugby (Wales were playing the All Blacks later that day) and the recent comet landing – I left with a new Sony Xperia Z2. I feel a bit sorry for turning my back on Blackberry; they really were innovators at one point, but they made some awful business decisions and have been left behind by the competition. Incidentally, the original company Research In Motion (RIM) was doing well enough 15 years ago to endow the PeRIMeter Institute for Theoretical Physics in Waterloo, Ontario, which was one of the reasons for my loyalty to date. The company is now called Blackberry Limited and has recently gone through major restructuring in its struggle for survival.

The Xperia Z2 is a nice phone, with a nice big display, generally very easy to find your way around, and with a lot more apps available than for Blackberry. I’ve got my Sussex email working and got Twitter, Facebook and WordPress installed; the latter is far better on Android than on Blackberry. The only thing I don’t like is the autocorrect/autocomplete, which is wretched, and which  I haven’t yet figured out how to switch off. The other thing is that it’s completely waterproof, but I haven’t taken it into the shower yet.

I feel quite modern for a change – my old Blackberry did make me feel like an old fogey sometimes – but since I’ve now signed up for another two years of contract before my next upgrade, there’s plenty of time for technology to overtake me again.



Autumn: A Dirge

Posted in Poetry with tags , on November 24, 2014 by telescoper


The warm sun is failing, the bleak wind is wailing,
The bare boughs are sighing, the pale flowers are dying,
And the Year
On the earth her death-bed, in a shroud of leaves dead,
Is lying.
Come, Months, come away,
From November to May,
In your saddest array;
Follow the bier
Of the dead cold Year,
And like dim shadows watch by her sepulchre.


The chill rain is falling, the nipped worm is crawling,
The rivers are swelling, the thunder is knelling
For the Year;
The blithe swallows are flown, and the lizards each gone
To his dwelling;
Come, Months, come away;
Put on white, black, and gray;
Let your light sisters play –
Ye, follow the bier
Of the dead cold Year,
And make her grave green with tear on tear.


by Percy Bysshe Shelley (1792-1822)



Warning! Offensive Image…

Posted in Politics with tags , , , on November 21, 2014 by telescoper

van No reasonable person could possibly take offence at that tweet from Emily Thornberry, yet she has had to resignfrom the Shadow Cabinet because of it. It is beyond belief how pathetic British politics and the British media have become.

Hubble Images With Music By Herschel

Posted in History, Music, The Universe and Stuff with tags , , on November 20, 2014 by telescoper

Too busy for a full post today, so here’s a little stocking filler. The, perhaps familiar, pictures are taken by the Hubble Space Telescope but the music is by noted astronomer (geddit?) Sir William Herschel – the Second Movement of his Chamber Symphony In F Major, marked Adagio e Cantabile. Although best known as an astronomer Herschel was a capable musician and composer with a style very obviously influenced by his near contemporary Georg Frideric Handel. Although music of this era puts me on a High Harpsichord Alert, I thought I’d share this example of music for those of you unfamiliar with his work…

Marginal Notes – Are You For Or Against?

Posted in Books, History with tags , , , , on November 19, 2014 by telescoper

At the weekend I was listening to a programme on Radio 3 part of which was about the rise of the foreeign language phrasebook over the last three or four centuries. It was a fascinating discussion, not least because it reminded me of an old Victorian English-Hindi phrasebook I found in a bookship in Pune (India). The book was intended for the use of well-to-do British ladies  and the phrases presumably chosen to reflect their likely needs as they travelled about India. I opened the book at random and found a translation of “Doctor, please help me. I am suffering from severe constipation”. In my experience as a Westerner travelling in India, constipation was the least of my worries…

Anyway, the real point of posting about this is that some of the old phrasebooks which were used to illustrate the programme had been heavily annotated by their owners. That reminded me of an discussion I’ve had with a number of people about whether they like to scribble in the margins of their books, or whether they believe this practice to be a form of sacrilege.

I’ll put my cards on the table  straightaway. I like to annotate my books – especially the technical ones – and some of them have extensive commentaries written in them. I also like to mark up poems that I read; that helps me greattly to understand the structure. I don’t have a problem with scribbling in margins because I think that’s what margins are for.Why else would they be there?

This is a famous example – a page from Newton’s Principia, annotated by Leibniz:


Some of my fellow academics, however, regard such actions as scandalous and seem to think books should be venerated in their pristine state.  Others probably find little use for printed books given the plethora of digitial resources now available online or via Kindles etc so this is not an issue..

I’m interested to see what the divergence of opinions is in with regard to the practice of writing in books, so here’s a poll for you to express your opinion:

German Tanks, Traffic Wardens, and the End of the World

Posted in Bad Statistics, The Universe and Stuff with tags , , , , , , , on November 18, 2014 by telescoper

The other day I was looking through some documents relating to the portfolio of courses and modules offered by the Department of Mathematics here at the University of Sussex when I came across a reference to the German Tank Problem. Not knowing what this was I did a google search and  a quite comprehensive wikipedia page on the subject which explains the background rather well.

It seems that during the latter stages of World War 2 the Western Allies made sustained efforts to determine the extent of German tank production, and approached this in two major ways, namely  conventional intelligence gathering and statistical estimation with the latter approach often providing the more accurate and reliable, as was the case in estimation of the production of Panther tanks  just prior to D-Day. The allied command structure had thought the heavy Panzer V (Panther) tanks, with their high velocity, long barreled 75 mm/L70 guns, were uncommon, and would only be encountered in northern France in small numbers.  The US Army was confident that the Sherman tank would perform well against the Panzer III and IV tanks that they expected to meet but would struggle against the Panzer V. Shortly before D-Day, rumoursbegan to circulate that large numbers of Panzer V tanks had been deployed in Normandy.

To ascertain if this were true the Allies attempted to estimate the number of Panzer V  tanks being produced. To do this they used the serial numbers on captured or destroyed tanks. The principal numbers used were gearbox numbers, as these fell in two unbroken sequences; chassis, engine numbers and various other components were also used. The question to be asked is how accurately can one infer the total number of tanks based on a sample of a few serial numbers. So accurate did this analysis prove to be that, in the statistical theory of estimation, the general problem of estimating the maximum of a discrete uniform distribution from sampling without replacement is now known as the German tank problem. I’ll leave the details to the wikipedia discussion, which in my opinion is yet another demonstration of the advantages of a Bayesian approach to this kind of problem.

This problem is a more general version of a problem that I first came across about 30 years ago. I think it was devised in the following form by Steve Gull, but can’t be sure of that.

Imagine you are a visitor in an unfamiliar, but very populous, city. For the sake of argument let’s assume that it is in China. You know that this city is patrolled by traffic wardens, each of whom carries a number on their uniform.  These numbers run consecutively from 1 (smallest) to T (largest) but you don’t know what T is, i.e. how many wardens there are in total. You step out of your hotel and discover traffic warden number 347 sticking a ticket on your car. What is your best estimate of T, the total number of wardens in the city? I hope the similarity to the German Tank Problem is obvious, except in this case it is much simplified by involving just one number rather than a sample.

I gave a short lunchtime talk about this many years ago when I was working at Queen Mary College, in the University of London. Every Friday, over beer and sandwiches, a member of staff or research student would give an informal presentation about their research, or something related to it. I decided to give a talk about bizarre applications of probability in cosmology, and this problem was intended to be my warm-up. I was amazed at the answers I got to this simple question. The majority of the audience denied that one could make any inference at all about T based on a single observation like this, other than that it  must be at least 347.

Actually, a single observation like this can lead to a useful inference about T, using Bayes’ theorem. Suppose we have really no idea at all about T before making our observation; we can then adopt a uniform prior probability. Of course there must be an upper limit on T. There can’t be more traffic wardens than there are people, for example. Although China has a large population, the prior probability of there being, say, a billion traffic wardens in a single city must surely be zero. But let us take the prior to be effectively constant. Suppose the actual number of the warden we observe is t. Now we have to assume that we have an equal chance of coming across any one of the T traffic wardens outside our hotel. Each value of t (from 1 to T) is therefore equally likely. I think this is the reason that my astronomers’ lunch audience thought there was no information to be gleaned from an observation of any particular value, i.e. t=347.

Let us simplify this argument further by allowing two alternative “models” for the frequency of Chinese traffic wardens. One has T=1000, and the other (just to be silly) has T=1,000,000. If I find number 347, which of these two alternatives do you think is more likely? Think about the kind of numbers that occupy the range from 1 to T. In the first case, most of the numbers have 3 digits. In the second, most of them have 6. If there were a million traffic wardens in the city, it is quite unlikely you would find a random individual with a number as small as 347. If there were only 1000, then 347 is just a typical number. There are strong grounds for favouring the first model over the second, simply based on the number actually observed. To put it another way, we would be surprised to encounter number 347 if T were actually a million. We would not be surprised if T were 1000.

One can extend this argument to the entire range of possible values of T, and ask a more general question: if I observe traffic warden number t what is the probability I assign to each value of T? The answer is found using Bayes’ theorem. The prior, as I assumed above, is uniform. The likelihood is the probability of the observation given the model. If I assume a value of T, the probability P(t|T) of each value of t (up to and including T) is just 1/T (since each of the wardens is equally likely to be encountered). Bayes’ theorem can then be used to construct a posterior probability of P(T|t). Without going through all the nuts and bolts, I hope you can see that this probability will tail off for large T. Our observation of a (relatively) small value for t should lead us to suspect that T is itself (relatively) small. Indeed it’s a reasonable “best guess” that T=2t. This makes intuitive sense because the observed value of t then lies right in the middle of its range of possibilities.

Before going on, it is worth mentioning one other point about this kind of inference: that it is not at all powerful. Note that the likelihood just varies as 1/T. That of course means that small values are favoured over large ones. But note that this probability is uniform in logarithmic terms. So although T=1000 is more probable than T=1,000,000,  the range between 1000 and 10,000 is roughly as likely as the range between 1,000,000 and 10,000,0000, assuming there is no prior information. So although it tells us something, it doesn’t actually tell us very much. Just like any probabilistic inference, there’s a chance that it is wrong, perhaps very wrong.

Which brings me to an extrapolation of this argument to an argument about the end of the World. Now I don’t mind admitting that as I get older I get more and  more pessimistic about the prospects for humankind’s survival into the distant future. Unless there are major changes in the way this planet is governed, our Earth may indeed become barren and uninhabitable through war or environmental catastrophe. But I do think the future is in our hands, and disaster is, at least in principle, avoidable. In this respect I have to distance myself from a very strange argument that has been circulating among philosophers and physicists for a number of years. It is called Doomsday argument, and it even has a sizeable wikipedia entry, to which I refer you for more details and variations on the basic theme. As far as I am aware, it was first introduced by the mathematical physicist Brandon Carter and subsequently developed and expanded by the philosopher John Leslie (not to be confused with the TV presenter of the same name). It also re-appeared in slightly different guise through a paper in the serious scientific journal Nature by the eminent physicist Richard Gott. Evidently, for some reason, some serious people take it very seriously indeed.

So what can Doomsday possibly have to do with Panzer tanks or traffic wardens? Instead of traffic wardens, we want to estimate N, the number of humans that will ever be born, Following the same logic as in the example above, I assume that I am a “randomly” chosen individual drawn from the sequence of all humans to be born, in past present and future. For the sake of argument, assume I number n in this sequence. The logic I explained above should lead me to conclude that the total number N is not much larger than my number, n. For the sake of argument, assume that I am the one-billionth human to be born, i.e. n=1,000,000,0000.  There should not be many more than a few billion humans ever to be born. At the rate of current population growth, this means that not many more generations of humans remain to be born. Doomsday is nigh.

Richard Gott’s version of this argument is logically similar, but is based on timescales rather than numbers. If whatever thing we are considering begins at some time tbegin and ends at a time tend and if we observe it at a “random” time between these two limits, then our best estimate for its future duration is of order how long it has lasted up until now. Gott gives the example of Stonehenge, which was built about 4,000 years ago: we should expect it to last a few thousand years into the future. Actually, Stonehenge is a highly dubious . It hasn’t really survived 4,000 years. It is a ruin, and nobody knows its original form or function. However, the argument goes that if we come across a building put up about twenty years ago, presumably we should think it will come down again (whether by accident or design) in about twenty years time. If I happen to walk past a building just as it is being finished, presumably I should hang around and watch its imminent collapse….

But I’m being facetious.

Following this chain of thought, we would argue that, since humanity has been around a few hundred thousand years, it is expected to last a few hundred thousand years more. Doomsday is not quite as imminent as previously, but in any case humankind is not expected to survive sufficiently long to, say, colonize the Galaxy.

You may reject this type of argument on the grounds that you do not accept my logic in the case of the traffic wardens. If so, I think you are wrong. I would say that if you accept all the assumptions entering into the Doomsday argument then it is an equally valid example of inductive inference. The real issue is whether it is reasonable to apply this argument at all in this particular case. There are a number of related examples that should lead one to suspect that something fishy is going on. Usually the problem can be traced back to the glib assumption that something is “random” when or it is not clearly stated what that is supposed to mean.

There are around sixty million British people on this planet, of whom I am one. In contrast there are 3 billion Chinese. If I follow the same kind of logic as in the examples I gave above, I should be very perplexed by the fact that I am not Chinese. After all, the odds are 50: 1 against me being British, aren’t they?

Of course, I am not at all surprised by the observation of my non-Chineseness. My upbringing gives me access to a great deal of information about my own ancestry, as well as the geographical and political structure of the planet. This data convinces me that I am not a “random” member of the human race. My self-knowledge is conditioning information and it leads to such a strong prior knowledge about my status that the weak inference I described above is irrelevant. Even if there were a million million Chinese and only a hundred British, I have no grounds to be surprised at my own nationality given what else I know about how I got to be here.

This kind of conditioning information can be applied to history, as well as geography. Each individual is generated by its parents. Its parents were generated by their parents, and so on. The genetic trail of these reproductive events connects us to our primitive ancestors in a continuous chain. A well-informed alien geneticist could look at my DNA and categorize me as an “early human”. I simply could not be born later in the story of humankind, even if it does turn out to continue for millennia. Everything about me – my genes, my physiognomy, my outlook, and even the fact that I bothering to spend time discussing this so-called paradox – is contingent on my specific place in human history. Future generations will know so much more about the universe and the risks to their survival that they won’t even discuss this simple argument. Perhaps we just happen to be living at the only epoch in human history in which we know enough about the Universe for the Doomsday argument to make some kind of sense, but too little to resolve it.

To see this in a slightly different light, think again about Gott’s timescale argument. The other day I met an old friend from school days. It was a chance encounter, and I hadn’t seen the person for over 25 years. In that time he had married, and when I met him he was accompanied by a baby daughter called Mary. If we were to take Gott’s argument seriously, this was a random encounter with an entity (Mary) that had existed for less than a year. Should I infer that this entity should probably only endure another year or so? I think not. Again, bare numerological inference is rendered completely irrelevant by the conditioning information I have. I know something about babies. When I see one I realise that it is an individual at the start of its life, and I assume that it has a good chance of surviving into adulthood. Human civilization is a baby civilization. Like any youngster, it has dangers facing it. But is not doomed by the mere fact that it is young,

John Leslie has developed many different variants of the basic Doomsday argument, and I don’t have the time to discuss them all here. There is one particularly bizarre version, however, that I think merits a final word or two because is raises an interesting red herring. It’s called the “Shooting Room”.

Consider the following model for human existence. Souls are called into existence in groups representing each generation. The first generation has ten souls. The next has a hundred, the next after that a thousand, and so on. Each generation is led into a room, at the front of which is a pair of dice. The dice are rolled. If the score is double-six then everyone in the room is shot and it’s the end of humanity. If any other score is shown, everyone survives and is led out of the Shooting Room to be replaced by the next generation, which is ten times larger. The dice are rolled again, with the same rules. You find yourself called into existence and are led into the room along with the rest of your generation. What should you think is going to happen?

Leslie’s argument is the following. Each generation not only has more members than the previous one, but also contains more souls than have ever existed to that point. For example, the third generation has 1000 souls; the previous two had 10 and 100 respectively, i.e. 110 altogether. Roughly 90% of all humanity lives in the last generation. Whenever the last generation happens, there bound to be more people in that generation than in all generations up to that point. When you are called into existence you should therefore expect to be in the last generation. You should consequently expect that the dice will show double six and the celestial firing squad will take aim. On the other hand, if you think the dice are fair then each throw is independent of the previous one and a throw of double-six should have a probability of just one in thirty-six. On this basis, you should expect to survive. The odds are against the fatal score.

This apparent paradox seems to suggest that it matters a great deal whether the future is predetermined (your presence in the last generation requires the double-six to fall) or “random” (in which case there is the usual probability of a double-six). Leslie argues that if everything is pre-determined then we’re doomed. If there’s some indeterminism then we might survive. This isn’t really a paradox at all, simply an illustration of the fact that assuming different models gives rise to different probability assignments.

While I am on the subject of the Shooting Room, it is worth drawing a parallel with another classic puzzle of probability theory, the St Petersburg Paradox. This is an old chestnut to do with a purported winning strategy for Roulette. It was first proposed by Nicolas Bernoulli but famously discussed at greatest length by Daniel Bernoulli in the pages of Transactions of the St Petersburg Academy, hence the name.  It works just as well for the case of a simple toss of a coin as for Roulette as in the latter game it involves betting only on red or black rather than on individual numbers.

Imagine you decide to bet such that you win by throwing heads. Your original stake is £1. If you win, the bank pays you at even money (i.e. you get your stake back plus another £1). If you lose, i.e. get tails, your strategy is to play again but bet double. If you win this time you get £4 back but have bet £2+£1=£3 up to that point. If you lose again you bet £8. If you win this time, you get £16 back but have paid in £8+£4+£2+£1=£15 to that point. Clearly, if you carry on the strategy of doubling your previous stake each time you lose, when you do eventually win you will be ahead by £1. It’s a guaranteed winner. Isn’t it?

The answer is yes, as long as you can guarantee that the number of losses you will suffer is finite. But in tosses of a fair coin there is no limit to the number of tails you can throw before getting a head. To get the correct probability of winning you have to allow for all possibilities. So what is your expected stake to win this £1? The answer is the root of the paradox. The probability that you win straight off is ½ (you need to throw a head), and your stake is £1 in this case so the contribution to the expectation is £0.50. The probability that you win on the second go is ¼ (you must lose the first time and win the second so it is ½ times ½) and your stake this time is £2 so this contributes the same £0.50 to the expectation. A moment’s thought tells you that each throw contributes the same amount, £0.50, to the expected stake. We have to add this up over all possibilities, and there are an infinite number of them. The result of summing them all up is therefore infinite. If you don’t believe this just think about how quickly your stake grows after only a few losses: £1, £2, £4, £8, £16, £32, £64, £128, £256, £512, £1024, etc. After only ten losses you are staking over a thousand pounds just to get your pound back. Sure, you can win £1 this way, but you need to expect to stake an infinite amount to guarantee doing so. It is not a very good way to get rich.

The relationship of all this to the Shooting Room is that it is shows it is dangerous to pre-suppose a finite value for a number which in principle could be infinite. If the number of souls that could be called into existence is allowed to be infinite, then any individual as no chance at all of being called into existence in any generation!

Amusing as they are, the thing that makes me most uncomfortable about these Doomsday arguments is that they attempt to determine a probability of an event without any reference to underlying mechanism. For me, a valid argument about Doomsday would have to involve a particular physical cause for the extinction of humanity (e.g. asteroid impact, climate change, nuclear war, etc). Given this physical mechanism one should construct a model within which one can estimate probabilities for the model parameters (such as the rate of occurrence of catastrophic asteroid impacts). Only then can one make a valid inference based on relevant observations and their associated likelihoods. Such calculations may indeed lead to alarming or depressing results. I fear that the greatest risk to our future survival is not from asteroid impact or global warming, where the chances can be estimated with reasonable precision, but self-destructive violence carried out by humans themselves. Science has no way of being able to predict what atrocities people are capable of so we can’t make any reliable estimate of the probability we will self-destruct. But the absence of any specific mechanism in the versions of the Doomsday argument I have discussed robs them of any scientific credibility at all.

There are better grounds for worrying about the future than simple-minded numerology.




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