These are some notes on deciding to do a PhD, notes I wrote some years ago after completing my own PhD.
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) : How to Do Research at the MIT AI Lab. AI Working Paper 316. MIT.
- Alan Bundy, Ben du Boulay, Jim Howe and Gordon Plotkin : 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.
POSTSCRIPT (Added 2012-11-07): And here is Cosma Shalizi’s take on PhD training. Same message, much fewer words.