How to be smart in a post-truth world

What the heck just happened? Events over recent months in the UK and USA, two nations divided by a common language, have led to a swathe of commentary expressing disbelief and anger alongside the jubilation and enactment. “They were all stupid,” says one side; “Stop moaning and get over it, losers,” says the other. No doubt the name calling will continue.
But what does any of this mean for an industry whose central purpose is to collate, process and deliver information? In the midst of it all lies a common theme, that of seeing data and facts as only one element of the debate, and an apparently low-priority element to boot. “People have had enough of experts,” said Brexit campaigner Michael Gove MP, even as his side laid out its own, fact-light agenda.
“Let’s give £350 million to the National Health Service,” they said, a promise Brexiters had no intention of keeping. They couldn’t: it wasn’t ever up to them, even if such an idea was even possible. Remainers had their own “Project Fear” meanwhile: a string of catastrophic consequences that would inevitably occur should the vote go against them. Many won’t, to the quiet delight of everybody.
As it turns out, neither ‘facts’ nor ‘promises’ mattered in Brexit; nor did they have much of a place in the Presidential election. Voters really didn’t appear care about the potential negative consequences, about historical misdemeanours, about promises that could never be kept (cf that some parts of the wall with Mexico becoming a fence — “I’m very good at this, it’s called construction,” said Trump).
It turns out that Michael Gove was right. People really had had enough of experts to the extent that they would, in both cases, appear to vote for the unknown rather than the known. “I think people just wanted to see what would happen,” a taxi driver said to me a few days ago. I’m not sure he is right; rather, I believe that we, as a species, have proved ourselves unable to appreciate the much bigger picture of what has been going on.
Over time we will unpick the reasons why people voted one way or another, and perhaps arrive at some conclusions: the data about voting attitudes, as well as reviewing historical factors through past decades, will no doubt reveal some truths. But if there is anything we can take from the current situation, it is that our current analytical abilities cannot necessarily reveal future behaviours.
Addressing this, deeper truth is of fundamental importance. If I had to put my money anywhere, it is that the models we use have completely failed to grasp the geo-political and psychological complexity of the situation. Condemning voters of either side as ‘stupid’ is symptomatic of this failure: they must be stupid, because they have done the inexplicable, right? Wrong, it is our ability to explain what is going on that is lacking, not ‘their’ decision making skills.
If we did understand such things at a deeper level we might be able to see more clearly the causes of current voter behaviours and indeed, do something about them. It may be for example that the seeds of recent events were sown back in the 80’s and 90’s, way before social media (which is taking the brunt of criticism) was a ‘thing’. Even armed with such an understanding however, we might still struggle to predict the unexpected from happening again.
Why? Due to the very characteristics that make us human in the first place. We are quick to jump to conclusions; we have agendas; we prefer to act on less information rather than waiting for a complete picture, particularly if it might go against what we want to do. We hunger for control, we often act in ways against our longer-term interests. And, frequently, we seek to justify our actions and positions using data that fits with our views, ignoring all that does not.
We know all of this. Lies, damn lies and statistics, we say, as if the data is the problem, rather than our propensity to interpret it selectively. The pollsters got it so, so wrong, yet still we use them. And while they are global and virtual, the echo chambers we inhabit today are no different to the past. So we share information that reflects our views, suppressing the “clearly biased” views of others. It is ironic that we even have a very human notion — of irony — to explain this phenomenon.
Meanwhile however, we continue to build information systems as if data holds some hallowed, incorruptible place in our lives. It doesn’t: we only have to look at how the oh-so-open Twitter has been castigated for harbouring trolls, or Facebook’s fake news issues, to see how vulnerable data can be to human behaviour. The models we build into systems design are equally subject to bias; the architectures assume people will be good first, and then are patched in response to the rediscovery that they are not.
Right now, we are seeing a renewed wave of interest in Artificial Intelligence, the latest attempt to create algorithms that might unlock the secrets contained in the mountains of data we create. Such algorithms will not deliver on their promise, not while they are controlled by human beings whose desires to be right are so strong they are prepared to ignore even the most self-evident of facts. And that means all of us. A failure to understand this will continue us on a path to inadequate understanding and denial of the real truth that lies beneath.