Wednesday, April 20, 2016

In (reflective) praise of DJCM

The scientist, David J. C. MacKay, passed away recently.  I have always been impressed by the wide range of people he influenced, but I was particularly surprised, at his passing, to see what a diverse range of people paid tribute to him, from young scientists working in a range of disciplines who were taught by him and use his Information Theory, Inference, and Learning Algorithms book, to public communicators of science, a relatively small and exclusive group which he effectively joined when he wrote his book 'Sustainable Energy - without the hot air.'

My favourite tribute was a tweet from David Spiegelhalter, who said of him,

"probably the most intelligent, principled, and fun person I shall ever know."

I am not sure there is much I can add to that.  He taught me when I was a master's student in Cambridge.  Among all the lectures I have been to, his were probably the most intelligent and fun.  And to see his principles, one only had to look at his jumpers, which were clearly designed to eliminate any need of central heating.

I think it would not be an understatement for me to say that I idolised him.  Some people idolise great rock stars, or great football players.  For me, at the tender age of 21, it was David MacKay.

I really thought, here is a man who has the power to change the world through the force of his intelligence.  I have a more nuanced view now, both of what it is possible to change, and of the types of people who are needed to achieve that change.

There are others who I think still see him as an idol.  In his obituary, Mark Lynas quotes David MacKay saying, “Please don’t get me wrong: I’m not trying to be pro-nuclear. I’m just pro-arithmetic.”  There is obviously something important here, that we should try and quantify the costs and benefits of different options for energy production and consumption.  However, there also seems to be an implicit suggestion, which I think is misguided, that if everyone was good at arithmetic, we would somehow be able to solve all the world's problems.

In the same obituary, David MacKay is described as a true polymath.  Again there is truth here, in that he was able to move nimbly between different scientific fields, from error-correcting codes in computer science, to information theory in genetics, to neural networks for machine learning, to spin models for particle physics.  The list could go on and on.  However there is a recurring theme, which is the description of a physical system by a mathematical model.  David MacKay was great at analysing models and doing inference for them, and he had a very good understanding of probability that allowed him to apply a relatively small set of principles to a wide range of of scientific problems.

Nevertheless, I am uncomfortable with the epitaph 'true polymath'.  As far as I am aware, David MacKay had no great interests outside of science and the application of science in public policy.  This is not a criticism of him as a person, I think it is very important that such people exist in society.  However, there are many other things in life to enjoy and to be curious about - literature, food, music, philosophy etc.  I think that a 'true polymath', of which there are very few, should be able to think in several different ways.  Descartes is a good example.  He invented cartesian coordinates and he probed the nature of the soul / existence.

What does the future hold for the areas where David MacKay did have greatest impact?  And how can we best ensure that his work and life live on in some sense?  There is clearly still a lot of work to be done.

Within statistical science and machine-learning there is still far too much of a tendency for people to rely on statistical tests that they don't understand very well (such as calculating p-values), and to just keep on trying statistical methods until something works, without really thinking problems through from first principles.  Statisticians need to spend more time (as David MacKay did during his lifetime) teaching people about probability, particularly scientists.

Within energy and climate policy, the all-out war between climate scientists and climate sceptics seems to have died down, but without either side really having learnt very much from the other.  Government work is modularised between different departments, which can create deep divisions.  An example is between the Treasury, which sees things through a 5 year economic prism, and the Department for Energy and Climate Change (DECC), which, put somewhat simplistically, thinks that reducing carbon emissions in the UK should be the number 1 priority of government.  There is a lot more that could be said about this, and I am probably not the best-placed person to say it.  However I do think more needs to be done to develop a sustainable economy and preserve our environment in the long-term (i.e. in the 100 year time-frame), while also attending to the natural desire most people have to live a comfortable life in the short-term (i.e. in the 5-10 year time frame).

I would like to finish on a personal note.  I remember talking to David MacKay about doing a PhD with him.  (This was before I knew he was leaving academia to do public policy work.)  He asked me what I was interested in researching.  His question caught me slightly off-guard, as I hadn't really thought about it that much.  I was also a bit embarrassed about sharing the half-formed ideas I did have with someone who I was in awe of.  In the end that conversation didn't directly lead to anything, but it did help to instill in me a strong sense of curiosity, and a desire to identify research problems that are interesting and important to me.  This is something that I think all academics should be cultivating, both in themselves and in others.