I Don't Know

It seems to me that life was simpler back in the sixties – although, admittedly, that may have been from the perspective of not knowing what I didn’t know. But the internal combustion engine certainly was simpler. If something went wrong – as it frequently did – you could easily diagnose the problem by peeking under the bonnet, noting the symptom and tracing the cause – usually steam coming from radiator caused by broken fan belt or failed water-pump. But when my campervan broke down last week no amount of peeking could throw light on the problem. It required the attendance of an engineer – not a mechanic, I noted – whose first action was to plug a computer into the diagnostic terminal (I didn’t know there was one) and peruse the list of faults that came up on the screen. Unfortunately, however, this was just the start of an extended process which required a good deal of human intervention in the form of experts deploying their experience to identify and fix the actual cause. Their job would have been easier if the vehicle had been fitted with a computer which learnt from each fault and subsequent fix. Man and machine in perfect harmony.

Computers are being developed which attempt to mimic human thinking by learning from their mistakes (or miscalculations) and when this technology is perfected it could be usefully deployed not only for engine problems but also for the wider benefit of mankind: for whereas individual humans may learn from their experience and modify their behaviour accordingly, collective human memory is leakier than an old colander and subject to distortion, manipulation and degradation – especially in the sphere of democratic governance. It is acknowledged that leaders, not being omniscient, must rely on specialist advisors to define policies where required. Typically, this means economic and military advisory panels but, because these often have a woeful ignorance of the precedents of history, leaders would do well to augment them with a panel of history experts. In addition, and in the interests of greater objectivity, they should subject all their resulting proposals to algorithmic analysis by artificial intelligence and act only on those outcomes.

Of course this approach would not be acceptable to dictators or megalomaniacs. For them the primary aim is to acquire and hold on to power; and one way they do this is to keep the majority of their constituents in blissful ignorance. The less people know, the more meagre are their aspirations and, therefore, the more easily are they appeased. Ignorance is the biggest obstacle to progress, which is why the best thinkers prize collaboration and the pooling of knowledge. They recognise only too well the need to know what they don’t know. Some of our politicians, on the other hand, seem to manage very well indeed without such awareness: millions watched in disbelief as one American Republican politician last week proved that he didn’t even know Aleppo is a place, let alone a problem, while yet another had to be reminded that there is a difference between “strong” and “dictatorial” when it comes to assessing Putin’s style of leadership. But then they are appealing to an audience that believes that Donald Trump will revive dead industries in Virginia and elsewhere, despite his giving no clue as to how he will achieve this. It appears that the parties concerned in this process are content not to know what they don’t know.

Politics in the sixties was, rather like engines, simpler in terms of identifying cause and effect. But now the traditional parties are struggling to get to grips with seismic shifts in employment patterns, wealth inequality and shifting international power blocs. Perhaps it’s time they employed the latest complexity-busting tool: bring on the artificial intelligence and let’s see if it can introduce some fair-play to human affairs. Then we will perhaps know what we didn’t know.