Another interesting and enjoyable chapter in this very long book, which I am not even halfway through, despite having bought it very shortly after publication in November 2021. At this rate it will be 2024 before I finish it!
As mentioned before, the book is in three parts. The first part is made up of nine chapters and a coda, in which McGilchrist writes about The Hemispheres and the Means to Truth. I have yet to finish reading the last two chapters of Part 1, but for notes on Chapters 2 to 7, see https://jennymackness.wordpress.com/the-matter-with-things-2/
In Part 2 McGilchrist writes about The Hemispheres and the Paths to Truth. In the first chapter, Chapter 10, he explores the question What is Truth? . Chapter 11, Science’s Claims on Truth is the second chapter. So far, I am enjoying Part 2 more that Part 1.
The main thrust of this chapter is that in the West, recent history has seen a move away from religion to science, and more particularly, to scientism (the belief that science will one day answer all our questions), in our search for truth. But, says McGilchrist, there are intrinsic limits to science, which tends to make exaggerated claims, use models that distort, and succumb to institutional pressures. Science has come to be thought of as the only path to truth and a discussion of its limits is often not welcome. Whilst McGilchrist is emphatic about the value of science, his concern is that it can’t answer the big questions; it can’t, for example, tell us what it means to be in love. Science finds it hard to deal with all that is experiential, but most of what we value in life is experiential, not observable, or measurable. The bigger the human meaning, the less science can offer. What we are asking science to do is to give us information/data but can that be converted into an understanding and what part does science play in the achievement of an understanding? Science can answer questions where explicit, mechanistic explanations are required, but not where understanding is required.
Explanation, metaphor, and models
Science cannot escape using models and metaphors because they are the basis of all understanding, so science depends on metaphors derived from concrete experience. All understanding depends on metaphor. Science uses models. Models are simply extended metaphors. The choice of the model is critical because:
‘We never just see something without seeing it as a something. We may think that our theories are shaped by observations, but it is as true that our observations are shaped by theories. This means that we can be blind to some very obvious things in our immediate environment. We don’t look where we don’t expect to see, so that our expectations come to govern what we can see.’ p.410
In the past the dominant model was a tree, a river, a family – something in the natural world. These days the dominant model is the machine (as favoured by the left hemisphere). The machine model is science’s defining paradigm, but it is a form of metaphor, and not all metaphors are good metaphors. All models are only a partial fit. A model determines not only what we do see but also what we don’t see, and we affect the model. No one model will ever be the perfect fit. We need to try and test different models, even though we may ultimately need to jettison them. Ideas of 100% truth cannot be sustained. In science certain things will be neglected. We may think that only things that are quantifiable are real (a left hemisphere perspective), but we have to rethink objectivity.
We cannot do without objectivity, but it is easily misinterpreted. To quote McGilchrist:
‘Science provides us with that objective knowledge by taking ‘us’ out of the picture, so removing subjective distortion from its objective presentation of how, in itself, the world actually is.’ p.413
We have already seen, however, that this aspiration to take ‘us’ out of the picture is compromised by the fact that science can’t get going without metaphor and metaphor is something from which ‘we’ cannot possibly be divorced.’ p.413
‘Objectivity is always someone’s position, situated somewhere and making some assumptions.’ p.414
Objectivity should be able to inhabit a lot of different perspectives – we ought to try to see from different perspectives.
Between us and the world there is always the barrier of our brains, and since we have two hemispheres in our brains each with their own view of the world, there are at least two views that science must take into account.
All methods rely on our judgements and values, even though these can’t be measured. Science frequently passes over what can’t be measured. It can’t cope with things that are imprecise or can’t be generalised. When considering objectivity, we need a more nuanced interpretation which recognises that existing answers are inadequate and provisional; there are always alternative answers. There are no whole truths, only half-truths, and context is of critical importance. Science tends to take things out of context. In trying to make science robust, we veer unstably between black and white positions, but we shouldn’t make statements that are too great or absolute. Instead of trying to make science robust, we should make it anti-fragile.
There are many assumptions in science. Science assumes that everything is understandable in physical terms, but science’s explanations both reveal and conceal. Sometimes assumptions are justified, but we must acknowledge them. Science can do very, very much, but not everything. As mentioned above, it cannot answer the very big questions, about values, meaning and purpose in life. Science is far from having all the answers – it is alive, provisional, and uncertain.
On p.420 McGilchrist quotes Max Planck as saying – ‘we have no right to assume that any physical laws exist, or if they have existed up to now, that they will continue to exist in a similar manner in the future.’
The scientific method
The scientific method is a myth. A belief in the notion of scientific objectivity, has led to a loss of imagination in science, but science requires imagination to come up with fruitful hypotheses. Chance and serendipity, intuition and inspiration play important roles in science.
Great discoveries are often made through images and metaphors rather than through chains of logic. Big insights are not made by following a logical linear sequence of steps, but by things like pattern recognition. Results can come in a flash of intuition and often precede arguments. Good hypotheses always ‘go beyond’ the immediate facts.
‘….. this does not discredit science in any way: it shows, instead, what an exciting and humbling business science is. We collaborate with nature, and with fortune, pay attention and learn from her. We neither withdraw the human element, as the myth of the scientific method implies, nor force nature to our preconceived ends.’ p.425
‘…. Just because what we rightly take to be scientific truths are not ‘objective’ in the sense that nothing human, contingent, and fallible enters into them, this does not mean they have no legitimate claim to be called true. … truth is never objective ….. All knowledge whatsoever is contextual and contingent. p. 429
Scientists must have faith, and science must be aware of its own limits.
For a discussion about this chapter between Iain McGilchrist and Alex Gomez-Marin, see:
McGilchrist, I. (2021). The Matter With Things. Our Brains, Our Delusions, and the Unmaking of the World. Perspectiva Press.