The life, social, and evolutionary sciences have a problem. We posted about the issue of their non-replicability last Friday but that is only part of the problem. They also have non-predictability (see a recent Times commentary), but both replicability and predictability are key elements of science as we know it.
It is difficult to make rigorous assertions that have the kind of predictive power we have come (rightly or wrongly) to expect of science, on the typical if often unstated assumption that our world is law-like, the way it seems that the physical and chemical universe are.
A clear manifestation of the problem is the way that findings in epidemiology and genetic risk say yes factor X is risky, then a few years later no, then yes again, and so on. Can't we ever know if factor X is a cause of some outcome Y? In particular, is X a risk factor? X could be a reason for natural selection, a component of some disease, and so on.
Often, we think of this as a probability. As we've posted before, that means that exposure to that factor yields some probability that the outcome will be observed. If you have two copies of a gene, there is usually a 50% risk or probability that a given one of your children (or parents, or sibs) will also have it.
So, in a strange turn of phrase, coffee or a given HDL cholesterol level is said to be a risk factor for heart disease, or a given genetic variant is a risk factor for cancer. And we try to estimate the level of that risk--the probability that if that factor is present, you will manifest the outcome. Among various possible risk factors, the modern concept of science has it that you are at some net or overall risk of the outcome, like having a heart attack, depending on your exposure to those risk factors.
In evolutionary terms, having a particular genetic variant can have some probability (or some similar measure) of reproducing, or surviving to a particular age. Among various possible genetic risk factors, what you have puts you at some net risk of such outcome, which is your evolutionary fitness in the face of natural selection, for example.
If we assume that enumerated causes of this sort, and that they really are causes, are responsible for a trait then your exposure level can be specified. The causes might truly be deterministic, in the way gravity determines the rate an object will fall--here or anywhere in the universe--but that our incomplete level of knowledge is such that we can only express its effect in terms of probability.
Still, we assume that probabilistic causation is real. When things are the result of probabilities, we can know the causes but can't predict the specific outcome of any given instance. This is the sense in which we know a fair coin will come up Heads 50% of the time, but can't predict the result of a given flip. Actually, and we've posted about this before but the issue of probability is so central to much of science that we keep repeating it, the coin may be perfectly deterministic but we just don't know enough, so that for all practical purposes the result is probabilistic.
In such cases, which are clearly at the foundation of evolutionary inference and of genetic and other biomedical problems, we must estimate the risk associated with a given cause by choosing a sample from all those at risk, and seeing what happened to them. Then, we assume we know the causal structure and can then do what we must be able to do, if this is actual science: predict the outcome. This must be so if the world is causal, even if our predictions are expressed in terms of probabilities: given your genotype you have xx probability of getting yy disease.
So, with our huge and munificently funded science establishment, why is it that day after day the media tout the latest Dramatic Finding....that is just as noisily touted the next day when the previous assertion is overturned?
Why is it that we don't know if coffee is a risk factor for disease? Or isn't? Or isn't for the moment until some new study comes along? Or maybe until some environmental factor changes, like the type of filter paper McDonald's uses in its coffee maker, say--but how would we ever know whether that explains the flip-flopping findings?
Why indeed do we have to continue doing studies of the same purported risk factor to see if they are really, truly risks? These are fundamental questions not about the individual studies, but about the current practice of science itself.
If we look at the reasons, which is tomorrow's post, we'll see how shaky our knowledge really is in these areas, and we can ask whether it is even 'science'.