N.B. If you’re after a quick answer then see here, if you want an in-depth outline see here or if you want to know how science works see here– this blog is more concerned with the broader conceptual framework within which science fits.
Knowledge is an interesting concept – how can we really “know” anything? How do we determine truth from untruth? Does knowledge even require what is “known” to be true? I don’t think so – I think it merely needs to appear true.
The human brain looks for explanations – being able to identify cause and effect is a powerful capability, after all, it underpins all human achievement. For example, if our ancestors were unable to identify that seeds grow into plants, we could never have established agriculture (and subsequently civilisation).
There are a variety of ways in which we make links between cause and effect, from straightforward reflexive Pavlovian classical conditioning, through more complex methods of identifying concept-based causation, to the rigourous statistical analysis of double-blind randomised controlled trials of modern biomedical research (which marks our current best attempt at linking cause to effect, whilst minimising the influence of coincidental factors). However, one of the most common ways in which we find explanations is by relating an observed occurance with an observed outcome – we look for a correlation.
Of course, the trouble with correlations is that you will often be spotting a relationship that doesn’t really exist. Factor A might occur at the same time or increase at the same rate as factor B, but it could be due to factors 1,2 and 3. For example, seasonal sales of ice-cream in the UK can be directly correlated with seasonal umbrella sales in Australia – obviously they are not directly related to each other, but they share the factor of seasonality in their respective hemispheres. So a summer in the Northern Hemisphere sees more ice-cream being bought, whilst in the Southern Hemisphere it is winter and people are buying umbrellas to keep off the rain. This is a simple illustration that is intended to be clear, but unfortunately most of the time we find it very difficult to identify what the factors involved in a correlation actually are – but that doesn’t stop us drawing conclusions from what we see, or think we see.
So what else do we use as a way of acquiring knowledge Continue reading