The scientific method requires that a hypothesis be supported by consistent and comprehensive comparisons of observed data. If supported in this manner, the hypothesis could be considered a theory.
At any time, however, new, contradictory evidence can upend any theory. Science is based on a continuing evaluation of all theories … none are sacrosanct; all must be validated by observed data.
It is here where Post-Normal Science (PNS) parts company with reality. While real science requires validation of a hypothesis by observed data, Post-Normal Science interjects opinions.
Post-Normal Science is proposed as a replacement for real science whenever:
“Facts are uncertain, values are in dispute, stakes are high, and decisions are urgent.”
This is a formula for replacing scientific objectivity with opinions.
Whose facts are used? Whose values are acceptable? Why are the stakes high? Why are decisions so urgent we can’t take the time to get the facts?
Each of these questions relies on opinions for answers, creating a pseudo science.
There are several techniques being used to support Post-Normal Science.
These include the use of:
- The correlation between unrelated facts to establish cause
- The precautionary principle.
Consensus is being substituted for scientific facts. Consensus creates the illusion that, if most scientists or experts believe something is true, then it must be true.
In the 1600s, the experts put Galileo on trial for heresy because he believed the earth went around the sun, rather than the prevailing consensus claiming the sun orbited the earth.
Very recently, there was a consensus in the medical profession that stomach ulcers were caused by stress. In the 1980s, only 30 years ago, two Australian physicians claimed that 90% of peptic ulcers were caused by bacteria. It took nearly twenty years for the consensus to accept it had been wrong, and that bacteria were the cause of stomach ulcers.
A consensus is not proof; it’s a substitute for proof.
And what is the significance of correlations? Here are examples taken from a presentation by John Droz, physicist, on the scientific method1.
Ice cream sales and shark attacks have excellent correlation. Rock music and US oil production have a strong correlation.
It’s obvious that ice cream sales and shark attacks are unrelated, as is rock music and oil production, but what about situations where it’s not obvious? Should we accept what someone tells us, or should we look more critically at the correlation?
Correlation doesn’t establish causation.
The precautionary principle sounds reasonable; i.e., better safe than sorry.
People tend to accept the precautionary principle without thinking, because it sounds reasonable, even though it can do great harm by preventing society from reaping the benefits of new technologies, products or processes.
The precautionary principle allows regulatory agencies to make decisions when there is little or no scientific evidence to support the decisions.
The rationale behind the precautionary principle is simple, and simplistic: Whenever a new technology, product or process poses a possible threat to human health or the environment, even when the threat hasn’t been proven to exist, it’s best to prevent the technology, product or process from being adopted.
Needless to say, anything new tends to pose a threat because it is new.
For example: Electricity can be dangerous; it can, in fact, kill. The precautionary principle, if in vogue in the late 1800s, could easily have prevented the development of electricity.
Today, the precautionary principle is preventing such things as genetically modified foods, new vaccines and beef being imported by the EU from North America if it’s been treated with hormones, even though the EU and WTO found no scientific rationale for any ban.
The precautionary principle is arbitrary, and without any basis in science. It is the poster child for Post-Normal science, where opinions are the basis for decisions.
How does Post-Normal Science (PNS) affect energy?
The various aspects of PNS, i.e., accepting consensus as proof, rather than establishing the facts; using correlation to define cause without establishing relationships; relying on the precautionary principle rather than on science; collectively, create an environment hostile to the development and use of energy.
Stopping the Keystone pipeline because the oil from Canada might emit more CO2 than oil from other sources, is an example of how PNS affects the development and use of energy.
Should the risk of an oil rig accident in the Gulf of Mexico preclude developing deep oil?
Should we continue to allow EPA regulations to curtail the use of coal because there is an alleged consensus that CO2 causes global warming?
It’s been argued by some, that smart meters shouldn’t be used because radiation might harm the health of homeowners. The facts belie this assertion, but there’s always the possibility, no matter how remote, that radiation from smart meters could be a health risk. Should smart meters be banned?
Critical thinking can discern the truth when media headlines and magazine covers reverberate with warnings, without facts.
Energy provides the underpinnings for our society, and has the potential to free billions of people elsewhere in the world from poverty and misery. Shouldn’t we challenge the fear mongers with facts?
- John Droz has an excellent video that goes into far greater detail, with the necessary supporting data. The video, Science Under Assault by John Droz is available at http://www.youtube.com/watch?feature=player_detailpage&v=cng56swJ_4I#t=1s
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