The post truth world

My work always tried to unite the truth with the beautiful, but when I had to choose one or the other, I usually chose the beautiful,

— Hermann Weyl

Faith in experts

They haven't done fabulously well, have they.

• Gordon Brown thought he’d abolished boom and bust in 2005.
• Financial crisis
  • credit rating agencies
  • risk models failed
• Democratic exercises - count the number of experts who got this wrong:
  • polling errors
  • economic projections

Modes of prediction

Physical science model

Carefully constrained conditions for observation: “laboratory conditions”

• Extraneous noise removed from the system
• Theoretical assumptions and experimental conditions are absolutely rigid and by definition cannot change
• Outcomes are tightly prescribed and you can’t test assumptions themselves the theory: in an experiment with dice you can’t throw a seven, mich less hypothesise what would happen if you did.
  

Model is to observe discrete events whose occurrence neither depends on nor is affected by

• your observation:
• other events in the sample:
  • If you throw one six, that makes it no more or less likely that you'll throw another. Even though instinctively it seems like it.
  • Isn’t variable in retrospect. A six, once thrown, can’t change its mind.

Ordinary “Gaussian” probabilities are appropriate, but even here the model is better at explaining observations once they’ve happened rather than predicting how they’ll happen before they do.

• • Try to catch a cricket ball using only scientific modelling.

Human sociological events

Human sociological events are profoundly different, even though the way we test them is not.

• We do have memory of previous occurrences,
• (outside “laboratory conditions”) it is almost impossible:
• to avoid knowing about other relevant events in a sample
• to avoid changing your behaviour as a result - i.e. reacting to them.

This changes the statistical analysis. A normal distribution has some value in predicting events which fall broadly within the standard deviation (these are events that conform with general expectations, and against which individuals are less likely to react.)
When events are significantly outside the standard deviation, people will react, pushing their own reaction outside the standard deviation - the result being the “long tail” phenomenon. Because individuals have memory these events themselves can older the shape of the system itself. Once you have seen a plane flying into a building, it now becomes a more conceivable outcome and individuals will behave differently as a result (usually governments will force them to). Same goes for the financial crises through time: policy results have been to react to an unanticipated event and prevent behaviour which individuals will generally avoid (in the short term) in any case. Again, we see we are better explaining in hinsight what happened rather than explaining what will happen next.

Path dependency

Laboratory conditions are far less appropriate to sociological experiments than to physical sciences. "Tail events" have two effects: firstly, they drive individuals down the tail (everyone is selling? SELL!) and secondly they change the very parameters and resting conditions - and likely distributios of events - in the environment itself. Firstly, the individual representatives remember the consequences of the action and actively avoid (or embrace) it, and secondly - and more importantly, the development might indicate a profound shift in the underlying assumptions of the economy. Once you have invented crop rotation, or how to refine crude oil, the existing assumptions of the economy are suddenly and profoundly out of date.

Possibilities present themselves that were literally inconceivable before this event. Canals and then railways permitted to fast, reliable transport of source materials in ways which permitted scaling of means of production that simply weren't imaginable beforehand.

Iterated interactions

Humans are different from events in physical sciences in two key ways: Firstly, they remember events and can watch and assimilate events happening to other people, and more importantly they repeatedly interact. 100 dice rolls are discrete events, and will be no different whether one dice or 100 are used. Human actions in a market are personal: the same person interacting in the same way 100 times will base her strategy for interaction on subsequent occasions with the knowledge of what has gone on before. We learn, we adapt and we adjust.

This simple fact is the key insight in considering how commerce works at all: in game theory terms, commerce is a repeated or iterated game of prisoner's dilemma, not a single round. The rational payoff for a single round is defection. The rational approach to an iterated game is cooperation.

Life isn't a game of poker

Which is where the poker analogy doesn't come in: The strategy in a game of poker is overtly one of defection: There is no benefit to cooperation. Through time a businessperson whoo approaches commerce as if playing poker will progressively lose.