If science is the most reliable and robust way we have of understanding the world around us, what makes it so?

Karl Popper c1980s
Karl Popper c1980s (Photo credit: LSE Library)

This was the question at the heart of last night’s Cardiff Philosophy Cafe, featuring a talk by John Jackson. John began by suggesting that science is, essentially, an extension of the way we perceive the world at a basic level, and rooted in the same principles which govern perception, memory and association. He proposed that, just as evolution should be considered as a selection process working on genes, perception (and how we respond to what we perceive) is a selection process working on stimuli that produce pleasure and pain. Behaviour grows out of the capacity to predict whether situations will be painful or pleasurable. Science “grows” out of this link between perception and behaviour. It is a way of systematically testing theories – that is, hypotheses about how the world works, about the regularities which underlie our perceptions.

John introduced the ideas of Karl Popper (1902 – 1994) as a means of understanding how scientific knowledge tests hypotheses. Popper’s view of science was, he suggested, very different to that of his contemporaries, the “Vienna Circle” of positivism philosophers. For Popper, science is not an enterprise of proving hypotheses on the basis of discovering facts. Rather, it does what it does by seeking to disprove hypotheses. The goal of a scientist is, having produced a hypothesis designed to explain some natural phenomenon, to come up with an experiment designed to show that it is false. If, having performed the experiment, the hypothesis is not disproven, then this stands in favour of its robustness. But this is different from proof: it simply means that the hypothesis has not, as yet, been disproven. It may be that, one day, it will be. So science does not prove that something is true: instead, it aims to test ideas about the world to destruction. Ideas that survive give us workable or “good enough” theories which we can use in adapting to and adjusting the world around us.

This way of testing hypotheses, John suggested, introduces the same kind of competitive mechanism into knowledge that exists in evolution and in perception. Overall, the value of scientific knowledge is, essentially, to enhance the capacity of the creatures using it (i.e. us) for survival – hence “good enough” hypotheses are all we need, rather than absolute truth. In discussing the relationship between scientific knowledge and religion, he pointed out that the “survival value” of science may be limited in some circumstances, however, and religious belief may “perform” better. The reason for this, he ventured, may be that the knowledge provided by science is often disillusioning – it robs us of cherished beliefs. Newtonianism, for example, was a huge blow to the worldview, first systematically set out byAristotle, that things exist because they embody purposes. By contrast, religion offers hope – which,even if illusory, has survival value.

In discussion, it was pointed out that the picture of science John had painted was very different from the “common-sense” view of science as a body of facts discovered through experiment and deduction. Both popular science (as communicated by celebrity scientists such as Brian Cox and Steve Jones) and the way science is used by governments to back up policy encourage us to think about scientific knowledge as a body of “positive” knowledge, rather than as a “negative” method that, despite being essentially sceptical and critical in nature, is nevertheless the most reliable means of understanding the natural world that we have.

Rather than providing us with certainty, science in the Popperian sense represents a way of living with uncertainty, and of cosntructing robust ways of interpreting the world in the face of an uncertain future. Some drew parallels with an authentic experience of religious faith, in which there is no certainty of salvation. Given that Poppperian science offers only a method of discovery and testing, rather than a way of discovering the truth, what might this mean for how we use science in justifying responses to pressing problems? Human-caused climate change, for example, is a phenomenon for which various explanatory hypotheses have been modelled. Yet testing these hypotheses is not possible: the only test for whether humans are causing the climate to change with CO2 emissions is to continue pumping carbon dioxide into the atmosphere and to see if the climate continues to change (leading to a 2, 4 or 6 degrees increase in global temperature, or whatever).

Faced with such situations – in which the testing laboratory and the world we live in are the same thing – can science help us decide what to do? Might this be an ultimate limit on the “survival value” of scientific knowledge?

UPDATE (08/06/12): just found this visual summary of the session courtesy of Auralab.

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