Naomi Oreskes is an American historian of science.
We as a people have to answer questions that rely on the scientific method – about global warming, evolution, and the effectiveness of vaccines. But increasingly, public opinion polls show that Americans don’t believe the science on these issues. For most people, science is not fully understood, so it is reduced to a matter of ‘belief’, and this is true even for scientists operating outside of their own field (eg a chemist talking about evolutionary biology). So how do we trust scientists?
The inductive model is the textbook scientific method. This forces scientists to
- Develop a hypothesis
- Deduce it’s consequences
- Observe these consequences
In the ideal case, the idea is a law of nature. A law is true in the general case – in all times and places, and cannot be broken.
For example, the theory of general relativity said that space-time wasn’t an empty void and actually had a fabric that was bent in the presence of large objects. An observable conclusion was that light would bend around the sun. This took a few years to test, but was observable and therefore verified the theory of general relativity.
Naomi says this deductive model of science is wrong for 3 reasons
- False theories can make true predictions – just because a test shows something, doesn’t prove this hypothesis.
- Auxiliary Hypothesis – assumptions that scientists are making without realising they are making them. For example to test that the Earth rotated around the sun, scientists suggested that when they focussed on a particular star in June, the backdrop of other stars would be different in December (since it was being observed from a different ‘angle’). They did not see this, so disproved the (correct) model because the effect of ‘stellar parallax’ was small (Earth’s orbit relative to star distances was tiny), and their telescopes were not sensitive enough. The scientists made incorrect implicit assumptions about the size of the orbit and the sensitivity of their equipment, which undermined their conclusions.
- Inductive science – a lot of science is based on finding evidence and data first, then developing a model later. Darwin’s evolutionary work itself evolved after Darwin collected samples and data over a number of years.
Scientists often build models, to explain the root causes of something. A geologist who hypothesised continental drift to form mountains did so first by compressing clay with a clamp – this did show results similar to the folds in mountains and this added to the evidence of continental drift. Climate change is an area where modelling is used to explain the 1 degree celsius temperature increase over the past 50 years. Temperature measurements over 150yr period show that the increase is clear, but the models explain this by taking into account all effects (for example sulfates, volcanic eruptions, greenhouse gases, ozone, solar radiation). By modelling each of these effects, we can see which combination of them affects temperature. The modelling shows that each of these effects yield a temperature change, but the largest rise was driven by the impact of greenhouse gases. This lets us show that not only is climate change happening (from observations of temperature), but also that greenhouse gases are a major driver (from the models).
If scientists do not use a common methodology, how do we know if they are right or wrong? By organised skepticism – they convince each other from a position of mistrust, with the burden of proof on someone who wants to make a novel claim. It is difficult to shift scientific thought to a new radical idea – the model is conservative by design. Scientific knowledge is therefore a model of consensus by the experts.
Is this consensus any different from the ‘appeal to authority’ argument? It is similar to an appeal to authority, but it is not an appeal to an individual, but the authority of the entire collective scientific community. For example – modern automobiles are the product of not 1 person, but on the collective work of every person who has worked on the car for the past 100 years. The same is true for science – but it has been collected over thousands of years. We should trust science, but not blindly – it should be based on evidence. This means scientists need to be better at sharing their reasons for knowing something, but also that we as a community need to be better at listening.