Science is full of observable facts. Fact, when I drop a hammer off the top of the Shard, it’s going to fall to the ground. It doesn’t matter if I drop it or Brian Cox drops it (either Brian Cox) or Boris drops it, it’s going to fall. There is a scientific law written about this. The law of gravity, that was one of Newton’s. And a law of science is an the ultimate truth, right?
No, not really scientific theories are not an ‘ultimate truths’. All a scientific law (or really a natural law) states is that there has never been an instance where anyone has observed anything different – not that the law is irrefutable and nothing new will ever happen. Scientific facts are observables. In principle, though admittedly not always in practice, it doesn’t matter who does the experiment or makes the measurements, observable facts are observable facts. The problem usually comes in how this evidence is interpreted.
I am an experimental scientist. I measure things. I come to conclusions about what the observables in my experiments mean. I come up with hypotheses, theories and then devise other experiments to try and test these hypotheses. In the somewhat turgid language of the ‘scientific method’, evidence is used to support or refute my hypothesis. If you peruse the scientific literature, it is full of hypotheses which are consistent with a set of data. Observable facts. Theoretical science predicts new things that might be observed but still remain grounded in observable factual evidence. This is the great thing about Higgs. He came up with the Higgs Boson, or rather the facts led him to predict this boson because it fit with the ‘standard model’ of particle physics (apologies to my theoretical physicist friends for the over simplification). This is the point of science, it isn’t about disconnected facts that we create theories about, it is about incorporating those facts into an informed evidence-based framework. This is how modern science works.
The problems usually lie in the interpretation part. This is true of science, as it is of all evidence-based methods. Our theories may fit all of the available evidence we have at the time – but they may not be a ‘truth’ per se, in the sense that many folks think of ‘truth’. They may in fact turn out to be incorrect, with new observables – many scientific theories are proven to be incorrect.
Richard Dawkins theory of the ‘selfish gene’ is a good example. Dawkins uses bits of evidence to support his idea of how evolution works through genetics – the selfish gene is his hypotheses for the mechanism of evolution. There is no definitive proof of a selfish gene currently and it is hard to think of an experiment by which this theory could be tested. Even so, Dawkins may well be right, but he may not be either. Much of the same evidence used in his book The Selfish Gene can also be and has been used to support different theories about the mechanism evolution.
There is a current trend for evidence-based policy, which overall is a good thing, in the context of separating “my pyschic says this is true” vs. “I have data that show that….”
But you have to be careful with evidence. Evidence can lead to all sorts of different theories and conclusions and when it comes to policy even more so. To put policy in the language of science, it is a very complex dynamic system. These kinds of systems are the most difficult to investigate. This is why psychology is such a difficult science, there are so many possibles and factors that effect obsevables and by extension theories of what is happening. Not to mention the evidence is ever-changing, which means the observables can lead to a myriad of different theories.
The same is true of evidence-based policy. It is not a straight-forward game. It is not as simple, usually, as I observe this, therefore we should do that. Usually the evidence is complex and difficult to interpret so while I fully support using evidence in government decisions I think we always have to think long and hard about what the evidence is really telling us.