If we consider any discipline that calls itself a “science” – such as climatology or academic psychology, for instance – let us ask: Does it use a formalism that enables us to reliably predict future events with precision? No. Does it dissolve a mystery by suggesting an explanation for something we did not understand before? No. Commit it then to the trash: for it can contain nothing but sophistry and illusion.
My words above deliberately echo those of “Hume’s fork”, which Hume and his later followers such as AJ Ayer used to distinguish honest empirical or reflective enquiry (about “matters of fact” or “relations of ideas”) from meaningless metaphysics.
My “fork” is aimed at distinguishing between honest scientific speculation and pseudo-science. The evidence for a scientific theory – or any theory which purports to describe things we can’t see directly – consists of its passing tests, and its explaining things that we otherwise wouldn’t understand. If a theory or discipline does neither of those things, it is garbage. If it is not widely recognised as garbage, that is usually because people are taken in by its impressive-looking rigour. Science does entail rigour of course – but the converse is not true. Mere rigour is not enough for science. Even the most rigorous astrology or homoeopathy is worthless hokum.
So I see any genuine science as having either or both of two virtues: it must have predictive power, or else it must have explanatory power. If it doesn’t explain anything and can’t predict anything, it’s garbage.
Two genuine sciences stand out as being rather short on one virtue, but they more than make up for that vice by being long on the other virtue. Quantum theory has little explanatory value – it is so poorly understood that it creates more mystery and bafflement than it dissolves. But it has extraordinary predictive power. With evolutionary theory, on the other hand, it’s the other way around. Evolutionary theory has little predictive power – we really have very little idea of how future living things will differ from life at present. But it has extraordinary explanatory power.
Predictive power isn’t just futurology or “saying what the future will be like” – astrology does that – it’s predicting specific observable events in the future successfully, in a reliable and repeatable way, so that the hypotheses that imply these future observations are corroborated by actual observations. In other words, the theory to which they belong passes tests.
A theory can have various sorts of explanatory power, because there are several different sorts of explanation. The best-known sort exemplifies the “covering law” model of explanation: a law (such as Newton’s law of gravitation) plus some other assumptions, hypotheses and initial conditions imply that an event (such as the appearance of Halley’s comet around 1066) should occur. The event’s actual occurrence would have been a mystery, until we realised it was implied by other things we accept already. Our acceptance of those other things removes any bafflement we may have had about why that particular event happened.
Another important sort of explanation occurs when one theory is reduced by another theory. This is a relation that exists between two branches of language, so it’s a bit like a weak form of translatability. For example, phenomenological thermodynamics takes heat “at face value” and treats temperature operationally as “whatever is measured by thermometers”. The more recent statistical mechanics revolves around the idea that heat is motion within matter. Thus the molecules of a gas bounce off each other and the walls of their container in a random way, so that temperature in a gas is mean molecular kinetic energy. The latter theory reduces the former theory, so that central claims such as Boyle’s law have a counterpart in both theories. In effect, the two theories “mesh” like cog wheels. This meshing is the best reason we scientific realists have for thinking that science is slowly pulling back the curtain on the parts of reality we can’t see directly. This is good news for both theories.
Evolutionary theory meshes with plate tectonics, explaining why many marsupial species are found in Australia, why some still remain in South America, and how the one species that made it to North America got there via the isthmus of Panama. Evolutionary theory also meshes with genetics. This is good news for plate tectonics and genetics, but it’s extremely good news for evolutionary theory, because its powers of prediction are so limited. We can add its meshing with these other areas of human thought to a vast body of explanation: of why there are as many males as females in most species, of why we like junk food despite calling it “junk”, of why the peacock’s unwieldy tail puts it into serious peril. Evolutionary theory even explains why people come to believe bad science: selfish genes entail cooperation, which entails in-groups and out-groups, which often entails the adoption of theory purely for group-identification purposes. It is a tragedy that many people believe this or that theory for no better reason than “I am a Democrat, so in science I am on this side rather than that side”.
Good science yields good reasons for belief: in prediction, it yields reasons to believe things that may not have even occurred to anyone before, such as the fact that stars appear further apart if their light has to pass near the Sun. In explanation, good science yields reasons to believe things that we already believed, such as the perilous length of the peacock’s tail, but which seemed mysterious or baffling to us because we were unable to fit them into our larger belief system.
Bad science does neither of the above.