In 1798, there were about a billion people in the world and economist Thomas Malthus predicted that overpopulation would lead to war and famine. In 1968, at 4 billion people, scientists published The Population Bomb and The Limits to Growth, which predicted the same.
Today, in 2014, there are over 7 billion people on the planet. Nevertheless, global poverty and violence are at all-time lows. Even carbon emissions are dropping (at least in the US). It seems that the experts have were mistaken.
In a sense, that shouldn’t be surprising. There will always be a wealth of experts arguing a number of sides to any given issue and most will be proved wrong. Yet we still seek them out because whenever there is uncertainty, we listen to anyone who professes to know more than we do. By looking for easy answers, we’re just asking for trouble.
A Battle Of Experts
After World War II, Richard Feynman was one of the world’s most promising young scientists. He was also one of the most eccentric. Few were surprised when he decided to take a year off to lecture in Brazil and play in a samba band. When you’re a genius, you can get away with that sort of thing.
Yet when he returned to the US, he felt lost. The physics world was engaged in a great debate about the decay of some obscure subatomic particles and he found himself completely unable to follow it. His sister suggested that instead of listening to experts, he try to figure it out for himself.
So that’s what he did, but was soon even more confused. The whole argument seemed to make no sense. He dug a little further and discovered why. The original paper that had given rise to the debate was deeply flawed. Feynman had even read it before leaving for Brazil and discarded it because it contained a fundamental—and very obvious—error.
Apparently, none of the great physicists arguing the issue had actually read the original paper. It had somehow just slipped through and nobody really checked it. They just assumed that someone, somewhere had vetted it, so they went on with their debate, oblivious to the fact that they were wasting their time on gibberish.
Feynman never considered himself an expert, but likened himself to a confused ape, which was one reason he saw further and more clearly than everyone else.
The Confidence Trap
One of the things that makes experts so convincing is that they exude confidence. They can talk calmly and knowledgeably about a subject, make reference to relevant facts and build a compelling logic for their case. A good expert is always impressive, but still usually wrong.
In fact, in a twenty year study of political experts, Philip Tetlock found that that their predictions were no better than flipping a coin. Further, he found that pundits who specialized in a particular field tended to perform worse than those whose knowledge was more general. In the contest between the hedgehog and the fox, the fox nearly always wins.
This is so counterintuitive that it hardly seems possible, but it’s true. The reason lies in the confidence of the predictions. Specialists, with their deep knowledge of a particular subject, tend to not to incorporate information outside their domain, which makes for a cleaner, more definitive story line.
Foxes, with their broad-based knowledge are less sure of themselves. They also tend to be right more often. Confusion, more often than not, trumps certainty.
The Rise Of The Machines
As Erik Brynjolfsson and Andrew McAfee describe in their new book, The Second Machine Age, computers are starting to outperform humans in cognitive tasks. Google flu trends identifies outbreaks more effectively than doctors can. Image analysis software beats trained pathologists and a simple algorithm outdoes procurement experts.
In fact, McAfee argues in a the Harvard Business Review that instead of using data to inform our judgments, we should turn our decisions over to algorithms. In effect, the new role of expertise is using superior understanding to make better models, rather than trying to outsmart the data.
This will, of course, be very hard to accept. High level professionals pride themselves on their judgment. We’ve worked hard to know our subject and feel that we’ve earned to right to call things as we see them. Turning decision making over to machines seems to devalue human experience.
And there’s something to that. Decisions often have a human component. Doctors need to take into account more than just diagnoses and disease, but also the patient’s lifestyle and personal preferences. Procurement experts need to make allowances for company partnerships and other soft factors.
Still, more than we’d like to admit, humans tend to be poor information processors and those who profess to have superior powers of insight are usually just fooling themselves.
Beware Of Umbrella Salesman In A Rainstorm
One of the things that always amazes me about New York City is how quickly guys appear to sell me an umbrella in a rainstorm. It seems that as soon as the first drops fall, dozens of them materialize out of nowhere, even if no rain was forecasted. I’m generally forgetful about things like that, so I often buy one.
I’ve noticed the same thing in business. Every time a new, exciting area emerges, a veritable horde of experts emerges, promising to explain the rules of the game, even before anyone has played. They always seem so smart, so convincing and so sure of themselves.
As brands started to become publishers, I was especially surprised to find that there were so many content experts. In all my years of publishing, I had worked with editors, designers and journalists, but had never met a content expert. Now, they were everywhere! None of them seemed to have ever published anything either.
Now, the hot area is data and surely there will be experts eager to educate us. Just as surely, they will be cogent, logical, persuasive and mostly wrong.
How do I know this? Trust me. I’m an expert.
Original Post: http://www.digitaltonto.com/2014/why-experts-always-seem-to-get-it-wrong/
