Despite what most of the medical profession would have us believe, they have very little understanding of the actual causes of or best treatments for the obesity epidemic currently sweeping the West. What little scientific evidence there is on the relationship between exercise and body weight indicates that increasing exercise leads to increased weight (presumably because more activity makes the exerciser hungrier). And the extensive scientific evidence on the relationship between dieting and weight indicates very strongly that this relationship is complicated, subject to contextual factors, and highly non-linear, with so-called “set points” that result in increased fat storage when calorie intake goes down significantly, for instance.
Archive for the 'Science' Category
For Popper scientific communities are politically virtuous because they permit unfettered criticism. A scientific community is, by (Popper’s) definition, an open society. Kuhn had to be shouted down because he seemed to deny this claim.”
Page 920 of B. Larvor : Review of I. Lakatos and P. Feyerabend: “For and Against Method“. British Journal for the Philosophy of Science, 51: 919-922.
Evolutionary psychology and sociology have long struck me as arrant nonsense, because they ignore human free will and self-reflection, and thus our ability to rise above our own nature. There are no pianos on the savanna, as I have remarked before, so an evolutionary psychologist will have a major challenge to explain a desire to play the piano in evolutionary terms.
Christopher Booker, in a review of E. O. Wilson’s new book, The Social Conquest of Earth, views similarly the flaws of evolutionary theory when applied to human behaviours:
It is our ability to escape from the rigid frame of instinct which explains almost everything that distinguishes human beings from any other form of life. But one looks in vain to Wilson to recognise this, let alone to explain how it could have come about in terms of Darwinian evolutionary theory. No attribute of Darwinians is more marked than their inability to grasp just how much their theory cannot account for, from all those evolutionary leaps which require a host of interdependent things to develop more or less simultaneously to be workable, that peculiarity of human consciousness which has allowed us to step outside the instinctive frame and to ‘conquer the Earth’ far more comprehensively than ants.
But it is this which also gives us our disintegrative propensity, individually and collectively, to behave egocentrically, presenting us with all those problems which distinguish us from all the other species which still live in unthinking obedience to the dictates of nature. All these follow from that split from our selfless ‘higher nature’, with which over the millennia our customs, laws, religion and artistic creativity have tried their best to re-integrate us.
Nothing is more comical about Darwinians than the contortions they get into in trying to explain those ‘altruistic’ aspects of human nature which might seem to contradict their belief that the evolutionary drive is always essentially self-centred (seen at its most extreme in Dawkins’s ‘selfish gene’ theory). Wilson’s thesis finally crumbles when he comes up with absurdly reductionist explanations for the emergence of the creative arts and religion. Forget Bach’s B Minor Mass or the deeper insights of the Hindu scriptures — as a lapsed Southern Baptist, he caricatures the religious instinct of mankind as little more than the stunted form of faith he escaped from.
His attempt to unravel what makes human nature unique is entirely a product of that limited ‘left-brain thinking’ which leads to cognitive dissonance.
Unable to think outside the Darwinian box, his account lacks any real warmth or wider understanding. Coming from ‘the most celebrated heir to Darwin’, his book may have won wide attention and praise. But all it really demonstrates is that the real problem with Darwinians is their inability to see just how much their beguilingly simple theory simply cannot explain.”
This is a list of non-fiction books which have greatly influenced me – making me see the world differently or act in it differently. They are listed chronologically according to when I first encountered them.
- 2009 – J. Scott Turner : The Tinkerer’s Accomplice: How Design Emerges from Life Itself. (Harvard UP) (Mentioned here.)
- 2008 – Pierre Delattre : Episodes. (St. Paul, MN, USA: Graywolf Press)
- 2006 – Mark Evan Bonds : Music as Thought: Listening to the Symphony in the Age of Beethoven. (Princeton UP)
- 2006 – Kyle Gann : Music Downtown: Writings from the Village Voice. (UCal Press)
- 2001 – George Leonard : The Way of Aikido: Life Lessons from an American Sensei.
- 2000 – Stephen E. Toulmin : Cosmopolis: The Hidden Agenda of Modernity. (University of Chicago Press)
- 1999 – Michel de Montaigne [1580-1595]: Essays.
- 1997 – James Pritchett : The Music of John Cage. (Cambridge UP, UK)
- 1996 – George Fowler : Dance of a Fallen Monk: A Journey to Spiritual Enlightenment. (New York: Doubleday)
- 1995 – Chungliang Al Huang and Jerry Lynch : Thinking Body, Dancing Mind. (New York: Bantam Books)
- 1995 – Jon Kabat-Zinn : Wherever You Go, There You Are.
- 1995 – Charlotte Joko Beck : Nothing Special: Living Zen.
- 1993 – George Leonard : Mastery: The Keys to Success and Long-Term Fulfillment.
- 1990 – Trevor Leggett : Zen and the Ways. (Tuttle)
- 1989 – Grant McCracken : Culture and Consumption.
- 1989 – Teresa Toranska : Them: Stalin’s Polish Puppets. Translated by Agnieszka Kolakowska.(HarperCollins) (Mentioned here.)
- 1988 – Henry David Thoreau : Cape Cod.
- 1988 – Rupert Sheldrake : The Presence of the Past: Morphic Resonance and the Habits of Nature.
- 1988 – Dan Rose : Black American Street Life: South Philadelphia, 1969-1971. (U Penn Press)
- 1987 – Jay Neugeboren : Reflections at Thirty.
- 1982 – John Miller Chernoff : African Rhythm and African Sensibility: Aesthetics and Social Action in African Musical Idioms. (University of Chicago Press)
- 1981 – Walter Rodney : How Europe Underdeveloped Africa. (London: Bogle-L’Overture Publications)
- 1980 – James A. Michener : Kent State: What happened and Why.
- 1980 – Andre Gunder Frank : The Development of Underdevelopment. (Monthly Review Press)
- 1980 – Paul Feyerabend : Against Method: Outline of an Anarchistic Theory of Knowledge.
- 1979 – Aldous Huxley : The Perennial Philosophy.
- 1978 – Christmas Humphreys [1949 ]: Zen Buddhism.
- 1977 – Raymond Smullyan : The Tao is Silent.
- 1976 – Bertrand Russell [1951-1969]: The Autobiography. (London: George Allen & Unwin)
- 1975 – Jean-Francois Revel : Without Marx or Jesus: The New American Revolution Has Begun.
- 1974 – Charles Reich : The Greening of America.
- 1973 – Selvarajan Yesudian and Elisabeth Haich : Yoga and Health. (NY: Harper)
Last week’s Observer carried a debate over the status of string theory by a theoretical physicist, Michael Duff, and a science journalist, James Baggott. Mostly, they talk past each other. There is much in what they say that could provoke comment, but since time is short, I will only comment on one statement.
Duff’s final contribution includes these words:
Finally, you offer no credible alternative. If you don’t like string theory the answer is simple: come up with a better one. “
This is plain wrong for several reasons. First, we would have no scientific progress at all if critics of scientific theories first had to develop an alternative theory before they could advance their criticisms. Indeed, public voicing of criticisms of a theory is one of the key motivations for other scientists to look for alternatives in the first place. So Duff has the horse and the cart backwards here.
Secondly, “come up with a better one“? “better“? What means “better“? Duff has missed precisely the main point of the critics of string theory! We have no way of knowing – not even in principle, let alone in practice – whether string theory is any good or not, nor whether it accurately describes reality. We have no experimental evidence by which to assess it, and most likely (since it posits and models alleged additional dimensions of spacetime that are inaccessible to us) not ever any way to obtain such empirical evidence. As I have argued before, theology has more empirical support – the personal spiritual experiences of religious believers and practitioners – than does string theory. So, suppose we did come up with an alternative theory to string theory: how then could we tell which theory was the better of the two?
Pure mathematicians, like theologians, don’t use empirical evidence as a criterion for evaluating theories. Instead, they use subjective criteria such as beauty, elegance, and self-coherence. There is nothing at all wrong with this. But such criteria ain’t science, which by its nature is a social activity.
Are plants intelligent? Here are 10 reasons for thinking so. I suspect the reason we don’t naturally consider the activities of plants to be evidence of intelligent behaviour is primarily because the timescales over which these activities are undertaken is typically longer than for animal behaviours. We humans have trouble seeing outside our own normal frames of reference. (HT: JV)
Bayesians are so prevalent in Artificial Intelligence (and, to be honest, so strident) that it can sometimes be lonely being a Frequentist. So it is nice to see a critical review of Nate Silver’s new book on prediction from a frequentist perspective. The reviewers are Gary Marcus and Ernest Davis from New York University, and here are some paras from their review in The New Yorker:
Silver’s one misstep comes in his advocacy of an approach known as Bayesian inference. According to Silver’s excited introduction,
Bayes’ theorem is nominally a mathematical formula. But it is really much more than that. It implies that we must think differently about our ideas.
Lost until Chapter 8 is the fact that the approach Silver lobbies for is hardly an innovation; instead (as he ultimately acknowledges), it is built around a two-hundred-fifty-year-old theorem that is usually taught in the first weeks of college probability courses. More than that, as valuable as the approach is, most statisticians see it is as only a partial solution to a very large problem.
A Bayesian approach is particularly useful when predicting outcome probabilities in cases where one has strong prior knowledge of a situation. Suppose, for instance (borrowing an old example that Silver revives), that a woman in her forties goes for a mammogram and receives bad news: a “positive” mammogram. However, since not every positive result is real, what is the probability that she actually has breast cancer? To calculate this, we need to know four numbers. The fraction of women in their forties who have breast cancer is 0.014, which is about one in seventy. The fraction who do not have breast cancer is therefore 1 – 0.014 = 0.986. These fractions are known as the prior probabilities. The probability that a woman who has breast cancer will get a positive result on a mammogram is 0.75. The probability that a woman who does not have breast cancer will get a false positive on a mammogram is 0.1. These are known as the conditional probabilities. Applying Bayes’s theorem, we can conclude that, among women who get a positive result, the fraction who actually have breast cancer is (0.014 x 0.75) / ((0.014 x 0.75) + (0.986 x 0.1)) = 0.1, approximately. That is, once we have seen the test result, the chance is about ninety per cent that it is a false positive. In this instance, Bayes’s theorem is the perfect tool for the job.
This technique can be extended to all kinds of other applications. In one of the best chapters in the book, Silver gives a step-by-step description of the use of probabilistic reasoning in placing bets while playing a hand of Texas Hold ’em, taking into account the probabilities on the cards that have been dealt and that will be dealt; the information about opponents’ hands that you can glean from the bets they have placed; and your general judgment of what kind of players they are (aggressive, cautious, stupid, etc.).
But the Bayesian approach is much less helpful when there is no consensus about what the prior probabilities should be. For example, in a notorious series of experiments, Stanley Milgram showed that many people would torture a victim if they were told that it was for the good of science. Before these experiments were carried out, should these results have been assigned a low prior (because no one would suppose that they themselves would do this) or a high prior (because we know that people accept authority)? In actual practice, the method of evaluation most scientists use most of the time is a variant of a technique proposed by the statistician Ronald Fisher in the early 1900s. Roughly speaking, in this approach, a hypothesis is considered validated by data only if the data pass a test that would be failed ninety-five or ninety-nine per cent of the time if the data were generated randomly. The advantage of Fisher’s approach (which is by no means perfect) is that to some degree it sidesteps the problem of estimating priors where no sufficient advance information exists. In the vast majority of scientific papers, Fisher’s statistics (and more sophisticated statistics in that tradition) are used.
Unfortunately, Silver’s discussion of alternatives to the Bayesian approach is dismissive, incomplete, and misleading. In some cases, Silver tends to attribute successful reasoning to the use of Bayesian methods without any evidence that those particular analyses were actually performed in Bayesian fashion. For instance, he writes about Bob Voulgaris, a basketball gambler,
Bob’s money is on Bayes too. He does not literally apply Bayes’ theorem every time he makes a prediction. But his practice of testing statistical data in the context of hypotheses and beliefs derived from his basketball knowledge is very Bayesian, as is his comfort with accepting probabilistic answers to his questions.
But, judging from the description in the previous thirty pages, Voulgaris follows instinct, not fancy Bayesian math. Here, Silver seems to be using “Bayesian” not to mean the use of Bayes’s theorem but, rather, the general strategy of combining many different kinds of information.
To take another example, Silver discusses at length an important and troubling paper by John Ioannidis, “Why Most Published Research Findings Are False,” and leaves the reader with the impression that the problems that Ioannidis raises can be solved if statisticians use Bayesian approach rather than following Fisher. Silver writes:
[Fisher’s classical] methods discourage the researcher from considering the underlying context or plausibility of his hypothesis, something that the Bayesian method demands in the form of a prior probability. Thus, you will see apparently serious papers published on how toads can predict earthquakes… which apply frequentist tests to produce “statistically significant” but manifestly ridiculous findings.
But NASA’s 2011 study of toads was actually important and useful, not some “manifestly ridiculous” finding plucked from thin air. It was a thoughtful analysis of groundwater chemistry that began with a combination of naturalistic observation (a group of toads had abandoned a lake in Italy near the epicenter of an earthquake that happened a few days later) and theory (about ionospheric disturbance and water composition).
The real reason that too many published studies are false is not because lots of people are testing ridiculous things, which rarely happens in the top scientific journals; it’s because in any given year, drug companies and medical schools perform thousands of experiments. In any study, there is some small chance of a false positive; if you do a lot of experiments, you will eventually get a lot of false positive results (even putting aside self-deception, biases toward reporting positive results, and outright fraud)—as Silver himself actually explains two pages earlier. Switching to a Bayesian method of evaluating statistics will not fix the underlying problems; cleaning up science requires changes to the way in which scientific research is done and evaluated, not just a new formula.
It is perfectly reasonable for Silver to prefer the Bayesian approach—the field has remained split for nearly a century, with each side having its own arguments, innovations, and work-arounds—but the case for preferring Bayes to Fisher is far weaker than Silver lets on, and there is no reason whatsoever to think that a Bayesian approach is a “think differently” revolution. “The Signal and the Noise” is a terrific book, with much to admire. But it will take a lot more than Bayes’s very useful theorem to solve the many challenges in the world of applied statistics.” [Links in original]
Also worth adding here that there is a very good reason experimental sciences adopted Frequentist approaches (what the reviewers call Fisher’s methods) in journal publications. That reason is that science is intended to be a search for objective truth using objective methods. Experiments are – or should be – replicable by anyone. How can subjective methods play any role in such an enterprise? Why should the journal Nature or any of its readers care what the prior probabilities of the experimenters were before an experiment? If these prior probabilities make a difference to the posterior (post-experiment) probabilities, then this is the insertion of a purely subjective element into something that should be objective and replicable. And if the actual numeric values of the prior probabilities don’t matter to the posterior probabilities (as some Bayesian theorems would suggest), then why does the methodology include them?
Awhile back, I posted some advice from my own experiences on doing a PhD. Since then, several people have asked me for advice about the viva voce (or oral) examination, which most PhD programs require at the end of the degree. Here are some notes I wrote for a candidate recently.
It is helpful to think about the goals of the examiners. In my opinion, they are trying to achieve the following goals:
1. First, they simply want to understand what your dissertation says. This means they will usually ask you to clarify or explain things which are not clear to them.
2. Then, they want to understand the context of the work. This refers to the previous academic literature on the subject or on related subjects, so they will generally ask about that literature. They may consider some topic to be related to your work which you did not cover; in that case, you would normally be asked to add some text on that topic.
3. They want to assess if the work makes a contribution to the related literature. So they will ask what is new or original in your dissertation, and why it is different from the past work of others. They will also want to be able to separate what is original from what came before (which is sometimes hard to do in some dissertations, due to the writing style of the candidate or the structure of the document). To the extent that Computer Science is an engineering discipline, and thus involves design, originality is usually not a problem: few other people will be working in the same area as you, and none of them would have made precisely the same sequences of design choices in the same order for the same reasons as you did.
4. They will usually want to assess if the new parts in the dissertation are significant or important. They will ask you about the strengths and weaknesses of your research, relative to the past work of others. They will usually ask about potential future work, the new questions that arise from your work, or the research that your work or your techniques make possible. Research or research techniques which open up new research vistas or new application domains are usually looked upon favourably.
5. Goals #3 and #4 will help the examiners decide if the written dissertation is worth receiving a PhD award, since most university regulations require PhD dissertations to present an original and significant contribution to knowledge.
6. The examiners will also want to assess if YOU yourself wrote the document. They will therefore ask you about the document, what your definitions are, where things are, why you have done certain things and not others, why you have made certain design choices and not others, etc. Some examiners will even give the impression that they have not read your dissertation, precisely to find out if you have!
7. Every dissertation makes some claims (your “theses”). The examiners will generally approach these claims with great scepticism, questioning and challenging you, contesting your responses and arguments, and generally trying to argue you down. They want to see if you can argue in favour of your claims, to see if you are able to justify and support your claims, and how you handle criticism. After all, if you can’t support your claims, no one else will, since you are the one proposing them.
The viva is not a test of memory, so you can take a copy of your thesis with you and refer to it as you wish. Likewise, you can take any notes you want. The viva is also not a test of speed-thinking, so you can take your time to answer questions or to respond to comments. You can ask the examiners to explain any question or any comment which you don’t understand. It is OK to argue with the examiners (in some sense, it is expected), but not to get personal in argument or to lose your temper.
The viva is one of the few occasions in a research career when you can have an extended discussion about your research with people interested in the topic who have actually read your work. Look forward to it, and enjoy it!
Do we each have a soul that incarnates in different bodies over time? Most scientists in my experience dismiss any such idea, like they do most everything they cannot yet explain. But a true scientist would (a) keep an open mind on the question, while (b) devising a scientific test of the claim. And here’s where things become difficult – and interesting. Exactly how would one test the hypothesis of reincarnation?
If reincarnation occurs, then there is a connection between bodies in different historical time zones. Yet there seems to be no way that such bodies could communicate their special connectedness to one another. In the case that reincarnation occurs, is there some way for instance that I could communicate with my future self (or selves), and only that person or people, in a way that they could recognize came from me (their own past incarnation) and no one else? Thus far, I have not been able to imagine such a communication channel or message. It may be possible to design a message that is public and seen by all, yet is only understood correctly by a particular recipient, as with the signal sent by the USSR’s Strategic Missile Command to the leadership of the USA during the August 1991 coup.
It would seem that no such inter-carnate communication is possible between incarnations of the same soul. Yet all the scientific tests of the hypothesis of reincarnation I can imagine would require some form of direct communications between separate human incarnations of the same soul, in the case there was reincarnation. Suggestions for experiments most welcome.
The Music Shop at no. 436 Strand
Monday 22 October 2012, 6.00pm-7.30pm
Venue: King’s College London
Strand Building 2:39 (English Seminar Room)
Introduced by Clare Pettitt
From the age of fourteen until his late teens, Charles Wheatstone worked in his uncle’s musical instrument shop on the Strand, modifying instruments and conducting experiments in acoustics at the back of the shop until he left to take up a scientific career, later moving down the road to become Professor of Experimental Philosophy at King’s College London and inventing the stereoscope, improving the concertina (Wheatstone’s musical instrument makers is still a going concern and makes concertinas) and inventing, with Cooke, the telegraph. When he was only 19 years old in September 1821, Wheatstone caused quite a sensation by inventing and exhibiting the ‘Enchanted Lyre or Aconcryptophone’ at his father’s music school/shop on Pall Mall and subsequently at the Adelaide Gallery of Practical Science on the Strand.
This session will concentrate on the crossover between musical, commercial and scientific culture and will ask whether it is possible to map the multiple utility of spaces on the Strand (shops which are schools which are galleries which are scientific workshops etc.) onto the radical rearrangement of the senses in this period which made new technologies of seeing, hearing and communication possible.
[Text from here, where references and suggestions for further reading may also be found.]