Ignorance and arrogance of “experts”

“Science is the belief in the ignorance of experts”.

By Richard Feynman, in: “What is Science?”, presented at the fifteenth annual meeting of the National Science Teachers Association, in New York City (1966) published in The Physics Teacher Vol. 7, issue 6 (1969)

Those who have knowledge, don’t predict. Those who predict, don’t have knowledge” – Lao Tzu, 6thCentury BC Chinese Poet

A selection of my blog posts relating to our ignorance and folly, and the folly of “experts”

Stupidity rules the world

The pitfalls of forecasting

Beware the “expert”

Other people’s writings that clarify commonly held fallacies
Most peer reviewed science is wrong [Source: A Dig Through Old Files Reminds Me Why I’m So Critical of Science]

In the year 2000, the US National Heart Lung, and Blood Institute (NHLBI) insisted that all researchers register their “primary aim” and then later their “primary outcome” with clinicaltrials.gov. This one small change in the way medical studies were reported transformed the “success” rates in peer reviewed papers. Before 2000, fully 57% of studies found the success they said they were testing for, but after that, their success rate fell to to a dismal 8%. When people didn’t have to declare what their aim was, they could fish through their results to find some positive, perhaps tangential association, and report that as if they had been investigating that effect all along. The negative results became invisible. If a diet, drug or treatment showed no benefit at all, or turned up bad results, nobody had to know. [Source]

Study demonstrates a pattern in ‘how scientists lie about their data’


This is particularly true in complex disciplines where more than one factor is at work.

Scientists are unlikely to be wrong where ONE thing is at work (e.g. malaria parasite). But wherever there is more than one factor (e.g. chronic diseases, muskulo-skeletal disorders, climate science), then there is a very strong chance they will go wrong MOST OF THE TIME.

It takes enormous effort to untangle effects when multiple factors are at work.


Throughout the inquiry – during public hearings and in submissions – three things about Australian public health lobbyists came to worry me: a conceited arrogance in the face of evidence from overseas; a desire to make laws “for the greater good”, and the belief that “appropriate” intellectuals know better than the rest of us.

Combined, the three tendencies also revealed a growing confluence between nanny-statism.

First, those who would treat us like children and substitute their minds for ours ignore that suffrage has history. One of the arguments against extending the vote to women and working-class men was that they were not fit to make political choices because they spent their money on frivolities such as beer, cigarettes and lacy dresses.

Every time those in love with their own expertise seek to regulate what people buy or wear or put in their mouths, they gloss over the fact that the people who shop and the people who vote are the same people.

Secondly, simply because individuals can make poor decisions does not mean governments make better ones. [Source]