“I once raised this issue among a group of cosmologists at a high table dinner at the Churchill College at Cambridge. “Why is that you guys are so conservative in your views, in the face of the almost complete lack of understanding of what is going on in your field?” I asked. The answer was as simple as it was surprising. “If we don’t accept some common picture of the universe, however unsupported by facts, there would be nothing to bind us together as a scientific community. Since it is unlikely that any picture that we use will be falsified in our lifetime, one theory is as good as any other.” The explanation was social, not scientific.” (Bak, page 86)

Reference:

Per Bak [1999]: How Nature Works: The Science of Self-Organized Criticality. (New York, USA: Copernicus)

The day ended with a debate at the Royal Society, organized by The Foundation for Science and Technology, on developing adaptation policy in response to climate change.     The speakers were Dr Rupert Lewis of DEFRA, Sir Graham Wynne of the Sub-Committee on Adaptation, UK Committee on Climate Change, and Tom Bolt, Director of Performance Management at LLoyd’s of London.  (Their presentations will eventually be posted here.) As Bolt remarked, insurance companies have to imagine potential global futures in which climate change has wrecked social and economic havoc, and so are major consumers of scientific prognoses.   One commentator from the audience suggested that insurers, particularly, may have a vested short-term financial interest in us all being pessimistic about the long term future, although this inference was not obvious to me:  one human reaction to a belief in a certainly-ruinous future is not to save or insure for it, but rather to spend today.

A very interesting issue raised by some audience members is just how do we engineer and build infrastructure for adaptability?  What would a well-adapted society look like?     One imagines that the floating houses built in the Netherlands to survive floods would fit any such description.  Computer scientists have some experience in creating and managing robust, designing resilient and adaptive systems, and so it may be useful to examine that experience for lessons for design and engineering efforts for other infrastructure.

It seems to me that the historical absence of village pianos in Africa causes a problem for evolutionary psychology, since clearly a daily compulsion to play the piano is not something that has a long-standing evolutionary basis – at least, not for those of us descended from the peoples of the African savannah.  So if evo-psych cannot explain this very real human characteristic, what business does it have explaining any other human characteristic?  Why are some attitudes or characteristics to be explained by evolutionary means yet not others?  What distinguishes the one class of characteristics from the other? And what credence can we possibly give to any evolutionary explanation of phenomena which is not, prima facie, explainable in this way?   Surely, this limitation of the scope of evolutionary explanations completely undermines such arguments, since either all higher-level human characteristics have evolutionary explanations or none at all do.

The scientific method is the only reliable method of achieving knowledge.”

Well, first, it is worth saying that the scientific method does not produce reliable knowledge.  One of the two defining features of science is that scientific claims are defeasible:  they may be contested, questioned, challenged, and even overthrown, if the evidence warrants.   There is nothing inherently reliable about any scientific claim or theory, since new evidence may be found at any time to overthrow it.  The history of science is littered with examples.   (The second key feature is that anyone may do this contesting; science is not, or rather should  not be, a priesthood.)

One could perhaps defend Atkins’ statement by saying that the abstracted method – first announcement of a claim or hypothesis about the world, then running experiments in the world aiming to falsify the claim, then objective revision or retraction of the claim – may lead to reliable knowledge over the long term.   But, as Paul Feyerabend argued from examination of historical records of scientific disputes, actual living, breathing scientists rarely follow any such method:  they merely use whatever argumentation techniques best suit their material at the time in an attempt to win support for their claims, and they typically maintain their personal support for their own claims despite any contrary evidence.  Given such diversity of actual scientific argumentation practice across disciplines, across time and across issues, I think it only a foolhardy person who would seek to demonstrate that an abstraction from these practices was guaranteed to yield reliable knowledge about the world. (I speak as someone who has tried to do just this, under some severe assumptions as to the types of knowledge and the types of argument used.  See reference below.) 

Second, it is worth noting that Atkins appears to have overlooked other means of achieving knowledge. Pure mathematics, for example, produces new knowledge by means of deductive reasoning, not using anything resembling the scientific method.  Many argue that such knowledge is reliable, since once demonstrated claims cannot be overthrown (at least, not overthrown using the same assumptions and same rules of inference).  Most of theoretical physics in the modern era – from Isaac Newton’s theory of gravity, through Einstein’s relativity theories, right up to contemporary string theory and brane theory – are mathematical in kind, developed by mathematicians from their intuitions and using deductive reasoning without recourse to experiment or anything approaching the scientific method. Newton, for instance, famously assumed that the physical laws which governed the motion of planets around the sun also governed the swings of pendulums here on earth, an assumption for which he had not a skerrick of evidence (and nor could he have had), and which is completely counter-intuitive.   We western moderns do not think it counter-intuitive because we have each received a decade of indoctrination at school in the objectively-weird notions of physics since Newton; without talk of mystical (and never fully explained) forces called “gravity” we too would find this assumption obviously without basis. 

In fact, most of our knowledge of physical Nature comes from these mathematical theories, even in Atkins’ own field of chemisty (where the very abstract mathematical theory of groups finds application).  Of course, we aim to test such mathematical theories by means of experiment, but a test is for the purposes of acceptance or rejection of the theory.   Once tested, the knowledge we have of Nature is from the theory, not usually from the test.   Arguably, it is mathematics, not the scientific method, which provides the knowledge we have.  In the case of string and brane theories, for example, no experiments to test these theories have yet been undertaken, and perhaps none could be undertaken even in principle (since the theories concern dimensions of space-time inaccessible to us).   In this case, not only the knowledge but even the acceptance or rejection of the theory, is from the mathematics, and not from something called a scientific method.   (And on what mathematical basis would we accept a mathematical theory of nature?  Perhaps on its elegance or mathematical beauty, or its simplicity, or its profoundness, or its tractability, or its computability.)

It is worth noting here, also, that in many cases, mathematical or computational models in science provide our only means to apprehend the Nature they are intended to model or describe.  We cannot know whether string theory, for example, describes the natural world well or not because we have no other way to apprehend or observe that part of the world it purports to describe.   It it is therefore moot to say that such theories are “reliable” or “effective”, since how could we tell? 

Atkins also ignores knowledge about actions, as distinct from knowledge of facts (know-how, rather than know-what).  For example, our knowledge about technologies and how they work – surely an important part of knowledge about the world – is typically not gained not through scientific experiment aiming to test some explicit prior hypothesis, but through building prototypes and exploring the properties of these human artefacts.  This process of creation and exploration is closer to play than to anything a philosopher of science would term the scientific method.   Similarly, an artist’s knowledge of some object (real or imagined) may be gained by drawing or painting it, using drawing as a form of thinking, again an activity very much like play.  To argue that any such knowledge gained by the artist is not knowledge, or perhaps not knowledge about Nature, would be reductionist (and, I think, perverse). 

And Atkins has also ignored, as Norm points out, the insight and knowledge  about the world provided by the humane disciplines – theology, literature, philosophy, etc.   As I have argued before, getting things done in the world requires, inter alia, a knowledge of how people and groups behave and function.   The best source of such knowledge is not science or the scientific method (despite the pretensions of academic social psychology), but literature, TV dramas, and films.

Reference:

P. McBurney and S. Parsons [2001]: Representing epistemic uncertainty by means of dialectical argumentation. Annals of Mathematics and Artificial Intelligence. Special Issue on Representations of Uncertainty. 32 (1-4): 125-169.

The play comprised three actors, two men and a woman, who played Newton at different ages – as a child, as a young-ish Cambridge academic, and as an old man.  As a work of drama, the conceit worked well, although it was best when one of the actors was playing another person interacting with Newton (eg, Halley, and later Leibniz, who spoke in an amusing cod-German accent).  Perhaps the real Newton was not sufficiently schizoid for three actors to play him, at least not when constrained to only use the man’s written words.    As I have remarked before, Newton’s personality was all of a piece:  it is only modern westerners who cannot imagine a religious motivation for activities such as scientific research, for example, or who find alchemy and calculus incoherent.

The performance was followed by a panel discussion by the Great and the Good – two historians and two scientists.  One of the scientists was the Astronomer Royal, Sir Martin Rees, who has subsequently won this year’s Templeton Prize for Science and Religion.  The discussion was interesting, so it is a pity it was not recorded for posterity.

A review of another play about a member of the matherati, Kurt Godel, is here.

The contemporary developed world obesity epidemic has always struck me as being too widespread and occurring too fast to be due simply to a lack of self-discipline by lots of individuals.   Current medical advice is for individuals to eat less and exercise more, advice given despite the experimental evidence showing that increasing exercise actually may increase weight (on average), rather than reducing it.    And advice given despite the fact – known for at least 150 years, since the work of Claude Bertrand – that our bodies are complex adaptive systems, whose properties do not conform to simple linear models; for example, eating less may lead the body to retain more of the nutrients of the food ingested, because of a body-weight set-point effect, and thus not lead to much weight loss at all.   We already have evidence that appetite may have  genetic determinants.  Now, it seems that the obesity epidemic may have environmental or social causes, since as well as humans in the developed world putting on weight, so too have animals.  The animal species studied include not only pets and zoo animals (whose diets may have been influenced directly by human feeding), but also wild animals living near humans.

And schizophrenia, which once was blamed on poor parenting by the mothers of patients, and later on the patient’s genes (and who, Mothers, gave them those?), may in fact be caused by a virus – a retrovirus, present in our and our ancestors’ DNA for some 60 million years.  It turns out this is the same retrovirus that is believed by some scientists to cause Multiple Sclerosis.  A virus as cause could explain why there is a persistent, and statistically significant, effect on the incidence of schizophrenia arising from the season of birth of the patient.  Neither genes nor a mother’s parenting style would be expected to be influenced by the season of birth, but virus lifecycles, activations, durations and diffusions, certainly are.

The standard line initially of the medical panjandrums on RSI was that this medical condition only seemed to affect office workers, and not others who worked a lot with their hands, such as musicians.    The implication of such a statement was that the causes of RSI could not be some objective condition, outside of the patient, and so must be internal, either psychosomatic or actually knowingly invented.  Yet, musicians for at least a couple of centuries have been suffering from RSI (or closely-related conditions), as anyone who asked them would know.

When the medical profession is ready to apologize to us all for wrongly accusing us of moral failings, weakness of will, or malfeasance, I’ll be here ready and waiting.  I’m not, however, holding my breath.

But when I am at home at the Institute for Advanced Study in Princeton, I am surrounded by string theorists, and I sometimes listen to their conversations. Occasionally I understand a little of what they are saying. Three things are clear.  First, what they are doing is first-rate mathematics. The leading pure mathematicians, people like Michael Atiyah and Isadore Singer, love it. It has opened up a whole new branch of mathematics, with new ideas and new problems. Most remarkably,  it gave the mathematicians new methods to solve old problems that were previously unsolvable.  Second, the string theorists think of themselves as physicists rather than mathematicians. They believe that their theory describes something real in the physical world. And third, there is not yet any proof that the theory is relevant to physics.  The  theory is not yet testable by experiment. The theory remains in a world of its own, detached from the rest of physics. String theorists make strenuous efforts to deduce consequences of the theory that might be testable in the real world, so far without success.

. . .

Finally, I give you my own guess for the future of string theory. My guess is probably wrong. I have no illusion that I can predict the future. I tell [page-break] you my guess, just to give you something to think about. I consider it unlikely that string theory will turn out to be either totally successful or totally useless. By totally successful I mean that it is a complete theory of physics, explaining all the details of particles and their interactions. By totally useless I mean that it remains a beautiful piece of pure mathematics. My guess is that string theory will end somewhere between complete success and failure. I guess that it will be like the theory of Lie groups, which Sophus Lie created in the nineteenth century as a mathematical framework for classical physics. So long as physics remained classical, Lie groups remained a failure. They were a solution looking for a problem. But then, fifty years later, the quantum revolution transformed physics, and Lie algebras found their proper place. They became the key to understanding the central role of symmetries in the quantum world. I expect that fifty or a hundred years from now another revolution in physics will happen, introducing new concepts of which we now have no inkling, and the new concepts will give string theory a new meaning. After that, string theory will suddenly find its proper place in the universe, making testable statements about the real world. I warn you that this guess about the future is probably wrong. It has the virtue of being falsifiable, which according to Karl Popper is the hallmark of a scientific statement. It may be demolished tomorrow by some discovery coming out of the Large Hadron Collider in Geneva.” (page 221-222)

Reference:

Freeman Dyson [2009]:  Birds and frogs.  Notices of the American Mathematical Society, 56 (2): 212-223, February 2009.   Available here.

Both Howard [Jakobson] and Tim [Crane], then, neither of them speaking as a believer, sees religion as making the world, so to say, fuller for its adherents – with more of interest, of meaning, of things, even, beyond our grasp. This reminds me of the occasion I asked a religious friend about the basis of his belief and he cut the conversation short by saying simply that his life would be poorer without it.

All I can say is that this account of religion doesn’t work for me – I mean, to shift me – and for two reasons. The first is that the world seems like an intensely interesting place already, without any extra population of meanings and mysteries. Just look, read. There’s no end of it, never mind a fullness. The second is that I don’t feel free to add a further layer of things to those for which some evidence can be supplied, and if I did, I wouldn’t know where to stop. Why just those mysteries?

I think Norm, and the accounts he cites, miss something that is often important both to religious believers and to practitioners of religious activities (two overlapping but not identical groups, as I have explained before).    What is missing is that for many people in these two groups, their interest in religious ideas and practices arises from a contact they have had, or which they perceive they have had, with entities from a non-material realm. This contact usually involves none of their so-called five senses, but is experienced deeply nonetheless.  One can know something from merely being in the presence of somebody, as may happen, for example, when we experience the strong love of another person.

Of course, it may be that people who have had such spiritual experiences are deluded in thinking they had them, or even, that they delude themselves.  Experiments exciting certain parts of the brain with small electric currents can apparently induce very similar perceptions of religious experiences in people.   Even so, such experiments do not demonstrate, or even make likely, the absence of non-material entities; in precisely the same way, patients with tinnitus do not demonstrate that we all live in a silent universe.

So it is perfectly possible that people who perceive they have had direct contact with non-material realms may indeed have had such contact.  This possibility exists even though Richard Dawkins and many another famous person seem not to have had such experiences.  Moreover, the lack of spiritual experiences for some people also tells us nothing about the existence or non-existence of spiritual realms and beings.   Not all of us are born able to hear, for example, but the fact that some people are born deaf is also not usually taken as a sign that the universe itself is silent.  It may thus, indeed, be those who believe that they have not had contacts with a non-material realm who are deluded, or who are deluding themselves.  In a situation of such widespread ignorance, with neither replicable evidence for the existence of spiritual entities nor any evidence against their existence, it behooves no one to be arrogant about his or her position.  (For the record, I do not count Norm in this combined category of arrogant atheists and arrogant religious believers.)

And to Norm’s larger point:   If a person has had such an experience, what does she find?  First, she finds that the experience is entirely discounted by science, since it cannot be replicated via experiment.  This arrogant disdain for phenomena that it cannot yet explain has sadly been a feature of western science since its inception.   Second, she finds that she cannot talk openly about this experience, at least not in a modern western office or university.    In the supremely rationalist environment of our business and education worlds, talking about spiritual experiences among colleagues is one sure way nowadays to receive laughter, scorn and derision.   That is very different from, say, the situation in the West in the middle of the 19th century, or the situation still today in Africa or in Australian Aboriginal society, societies where spiritual experiences are widely respected.   Having lived in both the West and in Africa, I know this difference very well.   Third, she would find no explanation or meaning for her experience in any academic discipline, apart from theology and poetry, and perhaps the arts and music.    She would, however, likely find great sympathy from pure mathematicians, who grapple daily with entities which seem to have existence and properties independent of the material realm, entities which are entirely imaginary, outside the world of our five senses, and yet which seem to exist in some fashion, often sublimely connected with one another.  (The square root of minus 1, for example, is entirely imaginary, yet its properties are not random, to be invented as we might wish from whole cloth, but are decidedly what they are.)

For Norm, the material world is rich and interesting enough as it is, and needs no further explanation.   If you have ever experienced something beyond the material, then I suggest that finding an explanation or interpretation of that experience which makes some sense of it for you is not nothing, and is a quest not to be ridiculed or derided, however quixotic that quest might prove.

People exert large amounts of problem-solving effort playing computer games. Simple image- and text-recognition tasks have been successfully ‘crowd-sourced’ through games, but it is not clear if more complex scientific problems can be solved with human-directed computing. Protein structure prediction is one such problem: locating the biologically relevant native conformation of a protein is a formidable computational challenge given the very large size of the search space. Here we describe Foldit, a multiplayer online game that engages non-scientists in solving hard prediction problems. Foldit players interact with protein structures using direct manipulation tools and user-friendly versions of algorithms from the Rosetta structure prediction methodology, while they compete and collaborate to optimize the computed energy. We show that top-ranked Foldit players excel at solving challenging structure refinement problems in which substantial backbone rearrangements are necessary to achieve the burial of hydrophobic residues. Players working collaboratively develop a rich assortment of new strategies and algorithms; unlike computational approaches, they explore not only the conformational space but also the space of possible search strategies. The integration of human visual problem-solving and strategy development capabilities with traditional computational algorithms through interactive multiplayer games is a powerful new approach to solving computationally-limited scientific problems.”

References:

Seth Cooper et al. [2010]: Predicting protein structures with a multiplayer online game.  Nature, 466:  756–760.  Published:  2010-08-05.

Eric Hand [2010]:  Citizen science:  people power.  Nature 466, 685-687. Published 2010-08-04.

The Foldit game is here.

Technorati Tags: crowd-sourced, Protein structure prediction

Choosing a PhD program is one of the hardest decisions we can make. For a start, most of us only make this decision once in our lives, and so we have no prior personal experience to go on.

Second, the success or otherwise of a PhD depends a great deal on factors about which we have little advanced knowledge or control, including, for example:

• The relationship between the student and the supervisor. A PhD is usually awarded only after a student has undertaken some original research. In some programs, this must also be significant. The key point here is that the student has to do this, not the supervisor, and not the two of them together. If you have never done research before, then you will have a period of learning. A good supervisor should be helpful, particularly at the beginning, but eventually wean you off his or her help.
• The relationship between the student and the subject-matter. In formal subjects, such as pure mathematics, research is primarily undertaken in the head of the researcher. In experimental subjects, much of the effort involved in research may be taken up with creating the apparatus or system on which the experiments are conducted. In engineering, much of the effort may be taken up with designing and building the artefact or system which is the object of the research.One of the great features of Artificial Intelligence (AI) at this particular time in its history is that there are not yet established rules and procedures for how research in AI should be undertaken. Hence, people in AI use a mix of: the deductive analysis of formal systems (as in pure mathematics), computational experiment and simulation (as in the physical sciences and computational economics), the creation of artefacts (as in engineering, music or art), personal introspection (reasoning about our own reasoning and behaviours, as in parts of philosophy), reasoning about the reasoning processes of others (as in so-called rational-actor theories in economics, game theory, or political science), social introspection (reasoning about the behaviour of groups with which we are acquainted, as in sociology, social psychology, or the study of organizational behaviour), and reflective narrative and dialog (as in anthropology or business strategy). Some researchers emphasize one approach over others, some use a mix of approaches. Not everyone has the skills or aptitude for each approach. If you attempt a PhD centered on simulation, for example, without good software programming and debugging skills, you will not be playing to your strengths. It may still be possible to complete the PhD, but only at the cost of great personal pain.In my experience, academics are remarkably unwilling to engage in discussion about HOW they do research. I do not know if this is because they fear that talking about their methods will frighten away their muse, or because, like most people in most professions, they do not reflect much on what they do. Of all disciplines, AI ought to have the most self-reflective practitioners, but I have not found this.
• The relationship between the student and the school. Despite their claims to the contrary, Universities are not at all meritocratic. Having now had personal working experience in Government, in business and in University, I have to say that Universities are the most status-conscious of the three institutions, and the one where good, original ideas from low-status people are given the shortest-shrift, if they are heard at all. So be prepared to be ignored.If you are coming to a PhD straight from undergraduate studies, you will not find many changes in the way you are treated by academic or other staff. However, if you have any prior working experience at all, you will find life as a PhD student a great shock. You may have commanded empires, thousands may have quaked at your words, but this will count for absolutely nothing in a university. You will be treated as if you were a blank piece of paper, to be inscribed on by the faculty, and only rarely will you find anyone interested in what you may have done before enrolling in the PhD.  I think part of the reason for this is that most academics — having no experience of the world beyond their walls – think that only their problems contain intellectual challenges, and look down on those in business and Government.  How little they know!  Related to this is the bias which most academics have for beliefs over actions. Perhaps it is a result of the nature of the modern research university where the culture is primarily a written one, rather than being verbal or tactile; in the main, written outputs (such as books and journal articles) are preferred over non-written outputs (such as developing complex software).  Certainly, there are many important activities in modern society requiring great intelligence and advanced skills which are not, and could not be, taught through lectures and reading (for example: playing the piano;  forecasting demand for high-tech products; managing software development projects).  All of these activities are learnt on the job, not in formal education.  Another part of the reason is that most universities, being state-funded or funded by generous endowments, do not face the ever-present threat of extinction which even large companies in most markets face. How else to explain the fact that Universities so often treat their next generation of leaders with apathy, disrespect and cynicism, in ways which no company would survive very long doing.A PhD is perhaps the last remnant of a feudal relationship in the modern world. The only way to deal with this, in my opinion, is to maintain your self-respect and self-esteem, despite the insults thrown at you (wittingly or not) by the system. Stand your ground, give no quarter, and believe in yourself.

Third, it is very hard to evaluate a decision to undertake a PhD. Because most of us only do one PhD in our lives, we have no control group to compare our PhD with another.  Moreover, even after you have finished, and successfully obtained your PhD, you may not be able to tell whether it was a good program or not.  It may have been a painful and frustrating exercise, but that may be true of both good and bad programs.  The program may produce lots of prize-winning graduates, but that may be feature of the people attracted to enter it, rather than anything they received while doing the PhD.

Deciding to do a PhD and deciding which PhD program to enter are therefore decisions we make and carry-through under great uncertainty. In particular, prior to doing the PhD, you will not be in a position to know what will be your own reactions to the experience, what the possible outcomes will be, or your own valuations of these outcomes.  (It is odd that classical decision theory – developed by academic economists – should be so useless for such a common and important decision. Yet another failing of economics!) The first thing you can do is talk to as many people as possible about their experiences as PhD students (both successful and failed), or as PhD supervisors, before you make your decision.  Here are some guides which I have found useful, and you may gain something from them:

• David Chapman (Editor) [1988]: How to Do Research at the MIT AI Lab. AI Working Paper 316. MIT.
• Alan Bundy, Ben du Boulay, Jim Howe and Gordon Plotkin [1985]: The Researcher’s Bible, a guide produced by AI and CS people at Edinburgh University.
• Some guides produced by the Computer Science Department at Carnegie-Mellon University.

The second thing to do, before you start your PhD, is to list all the challenges you expect to encounter in the course of the program, and to identify possible reactions to these.  Most PhD students get depressed at one or more points in their studies, often at the immense amount of reading they feel they have to do. To counter this depression, you need to identify strategies to deal with it, such as tackling some non-reading PhD activity (e.g., building a software simulator) or engaging in something not associated with your PhD (e.g., taking a holiday).  Of course, you won’t know in advance all the challenges you are likely to face, nor the best strategies for surmounting or coping with them.  But thinking about these in advance of starting forces you to reflect on the path you are embarking on.  Thirdly, it is useful in my experience to keep a diary of your experiences, and of your reactions to them, as you proceed through the program.  Writing a regular diary forces you to reflect on your experiences, and thereby distances you somewhat from them.  I think it the best antidote to depression.

Some general advice I give to PhD students:

It is my belief that one crucial skill which a PhD student should acquire in the course of his or her degree is the ability to identify a feasible research problem. Therefore, I believe very strongly that the supervisor should not choose the problem for the student, but instead allow the student to identify a problem for him or herself.  I realize that this is not the usual practice in all academic disciplines, especially mathematics, where the supervisor usually assigns a problem to each student.  I think this practice condescending, and inappropriate in computer science and AI.  Accordingly, as the problem may only be identified gradually, the precise details of the research may only emerge in the course of the PhD itself. Emergence is a phenomenon with which all researchers in AI should be familiar. This means that the actual work undertaken during the PhD may appear to repeat on itself, or to diverge in new directions, or appear in other ways to be undirected. Nothing is undirected, if viewed from the right perspective.  Part of the task of a PhD is to find the right perspective with which to view the work undertaken.

Research can be very frightening.  In formal subjects such as computer science, we are trying to put together a jigsaw puzzle, but a puzzle where we do not know in advance what the picture is on the jigsaw.  Also, the pieces are not given to us in advance – we usually have to find them, or even have to construct them ourselves. Moreover, once we complete the puzzle we may discover that the picture it displays is not the one we thought we were constructing. We may even find that our efforts result in a jigsaw without any picture at all. This is indeed scary, and I liken it to finding one’s way across a deep canyon one has never been in before in thick fog.  Why do we do it?   Well, partly because we imagine the view from the other side of the canyon is so beautiful, partly because we want to be first to reach the other side, and partly because the adrenalin rush as we stumble down and back up the canyon is addictive.   Doing a PhD successfully involves finding that source of adrenalin and using it to motivate us through three hard years of mountaineering.

I view the literature search as a survey of a landscape: you want to find what’s in the landscape, and where it is.  Most of the survey is simply so you know what’s where, and so that you can find it again, if you need to.   Some of the material you will read will turn out to be extremely important to your research topic, but you won’t know this in advance of reading it, and you may not even know it until you are near the end of your PhD.  Only when you come to final write-up will you be forced to identify, formally and precisely, what your research is really about, and so ideally your literature search should only be done at the end.  But, of course, you need to do it at the beginning in order to know what is where. This tension is an example of activities which appear to be undirected (reading everything more than once), but which in reality are essential.

Try not to be depressed by all the reading in front of you at the beginning. If you persist through this, then by about 18 months or so after you start, you will awake one morning to find you now know what is important to your topic and what not. You will then find you need to do very little reading until you come near the end.

Finally, it seems customary in guidebooks for PhDs to have some statement about this being the best experience of one’s life, or about research being a noble and elevated calling. I think such statements are misleading. PhDs are a feudal anachronism, an example of Karl Marx’s definition of tradition being the accumulated errors of past generations. They are required in order to get a job as an academic, or as a researcher in many advanced research labs. They serve no purpose that I can see which would not be served by other, less humbling, and less psychologically-intrusive means of learning how to do research.  The best you can hope for, in my experience, is to find a supervisor and a topic with whom you are sympatico, and try your best to get the damn thing over with as soon as possible.  Real life in a real world awaits you, after all.

If you have any comments on these notes, I would very much welcome hearing from you.