Archive for Stephen Hawking

Le Monde and the replication crisis

Posted in Books, Kids, Statistics with tags , , , , , , , , , , , , , , , on September 17, 2015 by xi'an

An rather poor coverage of the latest article in Science on the replication crisis in psychology in Le Monde Sciences & Medicine weekly pages (and mentioned a few days ago on Andrew’s blog, with the terrific if unrelated poster for Blade Runner…):

L’étude repose également sur le rôle d’un critère très critiqué, la “valeur p”, qui est un indicateur statistique estimant la probabilité que l’effet soit bien significatif.

As you may guess from the above (pardon my French!), the author of this summary of the Science article (a) has never heard of a p-value (which translates as niveau de signification in French statistics books) and (b) confuses the probability of exceeding the observed quantity under the null with the probability of the alternative. The remainder of the paper is more classical, pointing out the need for preregistered protocols in experimental sciences. Even though it mostly states evidence, like the decrease in significant effects for prepublished protocols. Apart from this mostly useless entry, rather interesting snapshots in the issue: Stephen Hawking’s views on how information could escape a black hole, an IBM software for predicting schizophrenia, Parkinson disease as a result of hyperactive neurons, diseased Formica fusca ants taking some harmful drugs to heal, …

Significance and artificial intelligence

Posted in Books, Kids, pictures, Statistics, University life with tags , , , , , , , , , , , , , on March 19, 2015 by xi'an

As my sorry excuse of an Internet provider has been unable to fix my broken connection for several days, I had more time to read and enjoy the latest Significance I received last week. Plenty of interesting entries, once again! Even though, faithful to my idiosyncrasies, I must definitely criticise the cover (but you may also skip till the end of the paragraph!): It shows a pile of exams higher than the page frame on a student table in a classroom and a vague silhouette sitting behind the exams. I do not know whether or not this is intentional but the silhouette has definitely been added to the original picture (and presumably the exams as well!), because the seat and blackboard behind this silhouette show through it. If this is intentional, does that mean that the poor soul grading this endless pile of exams has long turned into a wraith?! If not intentional, that’s poor workmanship for a magazine usually apt at making the most from the graphical side. (And then I could go on and on about the clearly independent choice of illustrations by the managing editor rather than the author(s) of the article…) End of the digression! Or maybe not because there also was an ugly graph from Knowledge is Beautiful about the causes of plane crashes that made pie-charts look great… Not that all the graphs in the book are bad, far from it!

“The development of full artificial intelligence could spell the end of the human race.’ S. Hawkins

The central theme of the magazine is artificial intelligence (and machine learning). A point I wanted to mention in a post following the recent doom-like messages of Gates and Hawking about AIs taking over humanity à la Blade Runner… or in Turing’s test. As if they had not already impacted our life so much and in so many ways. And no all positive or for the common good. Witness the ultra-fast codes on the stock market. Witness the self-replicating and modifying computer viruses. Witness the increasingly autonomous military drones. Or witness my silly Internet issue, where I cannot get hold of a person who can tell me what the problem is and what the company is doing to solve it (if anything!), but instead have to listen to endless phone automata that tell me to press “1 if…” and “3 else”, and that my incident ticket has last been updated three days ago… But at the same time the tone of The Independent tribune by Hawking, Russell, Tegmark, and Wilczek is somewhat misguided, if I may object to such luminaries!, and playing on science fiction themes that have been repeated so many times that they are now ingrained, rather than strong scientific arguments. Military robots that could improve themselves to the point of evading their conceptors are surely frightening but much less realistic than a nuclear reaction that could not be stopped in a Fukushima plant. Or than the long-term impacts of genetically modified crops and animals. Or than the current proposals of climate engineering. Or than the emerging nano-particles.

“If we build systems that are game-theoretic or utility maximisers, we won’t get what we’re hoping for.” P. Norvig

The discussion of this scare in Significance does not contribute much in my opinion. It starts with the concept of a perfect Bayesian agent, supposedly the state of an AI creating paperclips, which (who?) ends up using the entire Earth’s resources to make more paperclips. The other articles in this cover story are more relevant, as for instance how AI moved from pure logic to statistical or probabilist intelligence. With Yee Whye Teh discussing Bayesian networks and the example of Google translation (including a perfect translation into French of an English sentence).

May I believe I am a Bayesian?!

Posted in Books, Statistics, University life with tags , , , , , , , , , on January 21, 2012 by xi'an

…the argument is false that because some ideal form of this approach to reasoning seems excellent n theory it therefore follows that in practice using this and only this approach to reasoning is the right thing to do.” Stephen Senn, 2011

Deborah Mayo, Aris Spanos, and Kent Staley have edited a special issue of Rationality, Markets and Morals (RMM) (a rather weird combination, esp. for a journal name!) on “Statistical Science and Philosophy of Science: Where Do (Should) They Meet in 2011 and Beyond?” for which comments are open. Stephen Senn has a paper therein entitled You May Believe You Are a Bayesian But You Are Probably Wrong in his usual witty, entertaining, and… Bayesian-bashing style! I find it very kind of him to allow us to remain in the wrong, very kind indeed…


Now, the paper somehow intersects with the comments Stephen made on our review of Harold Jeffreys’ Theory of Probability a while ago. It contains a nice introduction to the four great systems of statistical inference, embodied by de Finetti, Fisher, Jeffreys, and Neyman plus Pearson. The main criticism of Bayesianism à la de Finetti is that it is so perfect as to be outworldish. And, since this perfection is lost in the practical implementation, there is no compelling reason to be a Bayesian. Worse, that all practical Bayesian implementations conflict with Bayesian principles. Hence a Bayesian author “in practice is wrong”. Stephen concludes with a call for eclecticism, quite in line with his usual style since this is likely to antagonise everyone. (I wonder whether or not having no final dot to the paper has a philosophical meaning. Since I have been caught in over-interpreting book covers, I will not say more!) As I will try to explain below, I believe Stephen has paradoxically himself fallen victim of over-theorising/philosophising! (Referring the interested reader to the above post as well as to my comments on Don Fraser’s “Is Bayes posterior quick and dirty confidence?” for more related points. Esp. about Senn’s criticisms of objective Bayes on page 52 that are not so central to this discussion… Same thing for the different notions of probability [p.49] and the relative difficulties of the terms in (2) [p.50]. Deborah Mayo has a ‘deconstructed” version of Stephen’s paper on her blog, with a much deeper if deBayesian philosophical discussion. And then Andrew Jaffe wrote a post in reply to Stephen’s paper. Whose points I cannot discuss for lack of time, but with an interesting mention of Jaynes as missing in Senn’s pantheon.)


The Bayesian theory is a theory on how to remain perfect but it does not explain how to become good.” Stephen Senn, 2011

While associating theories with characters is a reasonable rethoretical device, especially with large scale characters as the one above!, I think it deters the reader from a philosophical questioning on the theory behind the (big) man. (In fact, it is a form of bullying or, more politely (?), of having big names shoved down your throat as a form of argument.)  In particular, Stephen freezes the (Bayesian reasoning about the) Bayesian paradigm in its de Finetti phase-state, arguing about what de Finetti thought and believed. While this is historically interesting, I do not see why we should care at the praxis level. (I have made similar comments on this blog about the unpleasant aspects of being associated with one character, esp. the mysterious Reverent Bayes!) But this is not my main point.

…in practice things are not so simple.” Stephen Senn, 2011

The core argument in Senn’s diatribe is that reality is always more complex than the theory allows for and thus that a Bayesian has to compromise on her/his perfect theory with reality/practice in order to reach decisions. A kind of philosophical equivalent to Achille and the tortoise. However, it seems to me that the very fact that the Bayesian paradigm is a learning principle implies that imprecisions and imperfections are naturally endowed into the decision process. Thus avoiding the apparent infinite regress (Regress ins Unendliche) of having to run a Bayesian analysis to derive the prior for the Bayesian analysis at the level below (which is how I interpret Stephen’s first paragraph in Section 3). By refusing the transformation of a perfect albeit ideal Bayesian into a practical if imperfect bayesian (or coherent learner or whatever name that does not sound like being a member of a sect!), Stephen falls short of incorporating the contrainte de réalité into his own paradigm. The further criticisms found about prior justification, construction, evaluation (pp.59-60) are also of that kind, namely preventing the statistician to incorporate a degree of (probabilistic) uncertainty into her/his analysis.

In conclusion, reading Stephen’s piece was a pleasant and thought-provoking moment. I am glad to be allowed to believe I am a Bayesian, even though I do not believe it is a belief! The praxis of thousands of scientists using Bayesian tools with their personal degree of subjective involvement is an evolutive organism that reaches much further than the highly stylised construct of de Finetti (or of de Finetti restaged by Stephen!). And appropriately getting away from claims to being perfect or right. Or even being more philosophical.

Truly random [again]

Posted in Books, R, Statistics, University life with tags , , , , , , , , on December 10, 2010 by xi'an

“The measurement outputs contain at the 99% confidence level 42 new random bits. This is a much stronger statement than passing or not passing statistical tests, which merely indicate that no obvious non-random patterns are present.” arXiv:0911.3427

As often, I bought La Recherche in the station newsagent for the wrong reason! The cover of the December issue was about “God and Science” and I thought this issue would bring some interesting and deep arguments in connection with my math and realism post. The debate is very short, does not go in any depth. reproduces the Hawking’s quote that started the earlier post, and recycles the same graph about cosmology I used last summer in Vancouver! However, there are alternative interesting entries about probabilistic proof checking in Mathematics and truly random numbers… The first part is on an ACM paper on the PCP theorem by Irit Dinur, but is too terse as is (while the theory behind presumably escapes my abilities!). The second part is about a paper in Nature published by Pironio et al. and arXived as well. It is entitled “Random numbers certified by Bell’s Theorem” and also is one of the laureates of the La Recherche prize this year. I was first annoyed by the French coverage of the paper, mentioning that “a number was random with a probability of 99%” (?!) and that “a sequence of numbers is  perfectly random” (re-?!). The original paper is however stating the same thing, hence stressing the different meaning associated to randomness by those physicists, “the unpredictable character of the outcomes” and “universally-composable security”. The above “probability of randomness” is actually a p-value (associated with the null hypothesis that Bell’s inequality is not violated) that is equal to 0.00077. (So the above quote is somehow paradoxical!) The huge apparatus used to produce those random events is not very efficient: on average, 7 binary random numbers are detected per hour… A far cry from the “truly random” generator produced by Intel!

Ps-As a concidence, Julien Cornebise pointed out to me that there is a supplement in the journal about “Le Savoir du Corps” which is in fact handled by the pharmaceutical company Servier, currently under investigation for its drug Mediator… A very annoying breach of basic journalistic ethics in my opinion!

Mathematics and realism

Posted in Books with tags , , , , , , , , , , , on November 27, 2010 by xi'an

I read in Liberation a rather surprising tribune (in French) by “Yann Moix, writer”. The starting point is a criticism of Stephen Hawking (and Leonard Mlodinow)’s recent book The Grand Design, With regards to its conclusion that a god is not necessary to explain the creation and the working of the Universe: “It is not necessary to invoke God to light the blue touch paper and set the universe going.” I haven’t read Hawking’s book (although I briefly considered buying it in London last time I was there, here is a Guardian review), I had never heard before of this (controversial) writer, and I do not see the point in debating about supernatural beings (except when reviewing a fantasy book!). However, the arguments of Moix are rather limited from a philosophical viewpoint.

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