In the 19th and 20th centuries, standard economic models assumed that people would act in a rational and predictable manner. These models are flawed, of course, for if modern psychology has taught us anything it is that we are massively complex beings who are ultimately in important respects not predictable, often not rational, and certainly often rational in ways that are judged irrational by ‘experts’. We are moreover (and this is less widely understood) not predictable not only in practice but also in principle: i.e. this is not a limitation that can be overcome. For if the human future could be predicted, it would then be deliberately altered. Therefore it cannot be predicted. Human creativity and novelty and our ability to respond to predictions means that our actions cannot possibly by reliably modelled, even in principle.
The same can be said to some extent of natural systems too. Many still consider these to be deterministic systems governed by the strict laws of nature. And indeed, in many cases this is correct, but there are a number of outlying cases which do not conform to this. And they are enormously important. Think of chaos theory, for instance. Think of storms and their preceding butterflies…
Typically these cases involve uncertainty, or indeed complete ignorance which results in a necessarily deficient model. When the outliers that such models cannot model are potentially stormy – i.e. catastrophic – then this and similar sorts of situations result in what are informally called ‘black swans’ by my colleague Nassim Taleb (see for example our joint paper here).
But models are also of course based upon evidence — and so here is another problem with them. One should ask where that evidence comes from; the answer is principally observation and experimentation. But the experiments that were conducted to gather this evidence were also based upon a model; which again was based upon evidence gathered from within a particular model. This ‘self-reinforcing’ nature of models within particular disciplines is called by the great philosopher of science Thomas Kuhn a ‘paradigm’ and the presence of a paradigm is one of the benchmarks for what gets classed as a science (or not). The big problem here though is that the experiment typically only tests for what the model says should be there, and often there is no way to measure anything else that might happen as a result of the experiment. There could be a whole new world of science, or at least a completely different way to look at the same science which we have never encountered because of this.
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"We should learn to live in a world that we don’t understand, rather than harbouring dangerous ambitions for total explanation and mastery."
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Normally this isn’t a problem. The paradigm can normally be trusted. But sooner or later, paradigms encounter (or breach) their limits, and break down or require replacement. At the frontier of scientific knowledge, one never knows whether one might be at such a point. Again, this limitation is one that cannot be overcome, by definition.
Issue 49, 10th April 2016
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