Sympathetic Magic and the Modern Economy
Are big data, macroeconomics and AI more or less sympathetic magic, the sort of things that ancient priests and sages used to summon the gods, ensure fertility and protect the kingdom
I’m posting two old articles about big data and macroeconomics. They set out my view that much of what we say and do in these fields is, essentially, sympathetic magic, the sort of things that ancient priests and sages used to summon the gods, ensure fertility and protect the kingdom. Much the same can be said about the current brouhaha around AI.
Hubris and sympathetic magic - the essence of macroeconomics
The model is broken. So therefore we have to understand how the (broken) model really works and then everything will be fine. In essence this is the nature of the current debate about the economy – no-one really understands how the thing works and so, as we usually do when faced with something large and inexplicable, we behave like the blind men and the elephant.
And so these men of Indostan
Disputed loud and long,
Each in his own opinion
Exceeding stiff and strong,
Though each was partly in the right,
And all were in the wrong!
So it is with macroeconomics. Different sets of economists stand over their models of the economy – each one more Heath Robinson than the next – and argue that the results tickering out from the machine tell us the right things to do. Raise interest rates here, increase money supply there says one set of machine-minders.
Nooo! We hear another crew scream – more taxes, public investment and perhaps a little dose of inflation. That will do the job. All the while, over the wall the third crew say their combination of levers and pulleys provides the only proven and correct system of economic management. And so on along the line from Central Bank to International Body, from think tank to accountancy firm and from college to university – each set of overlookers, underlookers and sagger-maker’s bottom knockers proclaims that their results are proof of how we can make the economy work better.
Every now and then – more by luck than through skill and knowledge – one or other set of economists gets something right. For a moment it appears that a particular combination of lever-pulling and knot-tying is the way to run the economy. The leaders of the team receive great prizes, backs are slapped and the Kings and Princes grant the machine-minders money. And all the other teams, for a short while, shuffle into line by using the specified combination of levers and knots.
All this is just a combination of hubris and sympathetic magic. We witness the combining of the false belief that the economy can be “managed” with the misplaced view that because when we pulled lever seven last Wednesday and the ‘right’ result ensued, this will happen every time we pull lever seven. The truth, of course, is that the pulling of lever seven and that ‘right’ result coincided because of mere happenstance.
There is an old shopkeeper saying – ‘look after the pennies and the pounds will look after themselves’. It is the very antithesis of all this self-confident macroeconomic legerdemain. Rather than trying to design a great unifying theory of the economy (one of those Heath Robinson machines), we might be better looking at the simple process by which value is created. This has nothing to do with money, with central banks or with government but everything to do with providing other people with benefits.
No, not the benefits that are cash entitlements paid by government but the benefits that us advertising folk talk about. You know, the ‘sizzle not the sausage’. We don’t buy things just because they are things, we want them because of what they do for us – feed us, clothe us, shelter us, entertain us, please us. There are no macroeconomic policy levers here just people adding value by offering others benefits and in doing so giving themselves the means to secure the value – the benefits – they want.
All those economic model minders, all those predictors of the economy, all those lever pullers seem oblivious to this simple idea of value. They have become obsessed with money and the meaning of money, convinced that if only the correct dragon’s teeth are sown the economy will thrive and value will spring fully armed from out the ground. It seems to me that these people are the inheritors of those priests and wizards who call on the gods and magic to ensure that the sun rose in the morning and the crops grew in the spring.
The economists and policymongers inhabit grand temples, are granted the ear of kings and princes and are looked on in awe by lesser folk. But their ideas contain only a little more truth or hope of future goodness than did those of the old priest who said the corn must be planted on a full moon or that the rains will come if the right dance was danced.
A reminder that "Big Data" analysis isn't research it's sympathetic magic
IF we analyse the principles of thought on which magic is based, they will probably be found to resolve themselves into two: first, that like produces like, or that an effect resembles its cause; and, second, that things which have once been in contact with each other continue to act on each other at a distance after the physical contact has been severed. The former principle may be called the Law of Similarity, the latter the Law of Contact or Contagion. From the first of these principles, namely the Law of Similarity, the magician infers that he can produce any effect he desires merely by imitating it: from the second he infers that whatever he does to a material object will affect equally the person with whom the object was once in contact, whether it formed part of his body or not. (from The Golden Bough, Sir James Frazer)
The current obsession with 'big data' should concern us - not because the data is useless but because it makes people think in peculiar (and worrying) ways:
But with the advent of “big data” this argument has started to shift. Large data sets can throw up intriguing correlations that may be good enough for some purposes. (Who cares why price cuts are most effective on a Tuesday? If it’s Tuesday, cut the price.) Andy Haldane, chief economist of the Bank of England, recently argued that economists might want to take mere correlations more seriously. He is not the first big-data enthusiast to say so.
This quote is from Tim Harford and describes what I refer to as sympathetic magic. We pile up enormous mountains of data and interrogate that data with clever computer technology (that mostly we didn't create and don't understand), find correlations and make sweeping assumptions based on the correlations we do find - as opposed to the myriad other correlations we haven't found.
So what that chap from the Bank of England is saying is that if we pull this lever here and press that button there it does seem that this result occurs. We've no idea why it occurs or even whether, given a different set of instructions to the clever computer technology, we'd get the same correlation again. Yet the economist takes the result spat out by the big data black box and declares it to be scriptural - the latest set of levers and buttons that will set the economy on the right course.
All the acolytes of that economist then produce graphs showing the results of all that wonderful (and essentially magical) data-crunching. Until such a time as a different mountain of data or a different analysis tool produces a different set of buttons and levers to press or pull. This continues in cycles as the followers of one or other school of magic contest to either create new answers or - more commonly - to argue backwards and forwards why the other school is wrong.
Back in 1990, before all this Internet lack, us direct marketers were playing with big databases - the geodemographics and psychographics economists and such folk think are new and exciting were the tools we used. We experimented with expert systems and with emerging data mining tools of one sort or another. And we discovered that the results of such analyses (prices cuts are more effective on Tuesdays or whatever) were very useful. But not as useful as we'd like them to be. Big data analysis was still no substitute for information about real purchase behaviour meaning that the database analyses were more useful as a planning tool than as a pointer to where marketing investment might work best.
Much of macroeconomics - for all the volume of learned interpretation it generates - falls into this trap. There is a great deal (too much probably) of information but what matters isn't how much data we have but the tools we use to assess that data. And these tools provide conflicting information meaning that there simply isn't a right answer - other than that something should be done to direct the economy.
None of this is to say we shouldn't analyse that data, crunch those numbers, try to understand what these Big Data runes tell us about the world. But we should do it with humility and should recognise that this is not real knowledge but rather a chimaera of knowledge - real knowledge is to know, for now at least, the causes of something:
Do Big Data help us establish ‘causation’ more accurately? No. But new and unexpected patterns might emerge that suggest how combinations of risks interact unexpectedly.
Though even then some patterns are just, well, luck. Their probative value can not be assumed. Quick, give me another grant! We need more data to help us understand what Big Data are telling us!
Such is the nature of this big data thing. Yet we assume - because there is so much information - that the answers it spews out will be better, more true. To which I reply with this research:
Demographic segmentation variables are cheap and easy to measure, while psychographic variables are more expensive and harder to measure, but can provide more insight into consumers’ psychology. Suggests that a prima facie case exists for the suitability of astrology as a segmentation variable with the potential to combine the measurement advantages of demographics with the psychological insights of psychographics and to create segments which are measurable, substantial, exhaustive, stable over time, and relatively accessible. Tests the premise empirically using results from a Government data set, the British General Household Survey. The analyses show that astrology does have a significant, and sometimes predictable, effect on behavior in the leisure, tobacco, and drinks markets.
This is Big Data analysis. Do you believe it?