A SHORT while ago I was chatting to an ecologist who specialised in woodland habitats. Great job, I thought; strolling along paths, clipboard in hand, observing the relationships between plants and animals, the soil and environment. Going to work every day and dealing with the wonder and complexity of nature. I said I envied her.
‘It’s not really like that,’ she said. ‘I spend most of my time sitting in front my laptop analysing and modelling data to understand relationships and make predictions.’
It occurred to me later that she was mapping. She was taking the incredible diversity and beauty of a woodland and mapping it to abstraction. Collecting real-life data from observations and turning them into numbers in an effort to better understand the woodland environment.
Mapping involves determining the relationship between geographical and Man-made features in terms of distance and elevation, thus creating a replica of an area.
Modelling is similar. It creates replicas of the world from observational data – for example, the weather, health or the stuff that comes from the particle accelerator at CERN. No idea what that is, but it does explain the universe, apparently.
Both mapping and modelling largely involve reducing observations and concepts to numbers and as such help us understand a very complex world. However, in that reduction we of course lose something.
The late theoretical physicist David Bohm was on to this, arguing that science had become increasingly preoccupied with mathematical theories of the world. And with the increasing sophistication of mathematical models, science had become unbalanced. Missing the big picture. Perhaps it’s more comfortable dealing with the apparent certainty of numbers rather than the mystery of reality – my words, not Bohm’s.
The weird world of quantum physics, David Bohm’s field, must be difficult to approach in any way other than mathematics. But as Bohm suggests, mathematics can only provide a partial, albeit very useful, picture of the world. And nowhere is this limitation more problematic than in biology, arguably the most complex of the sciences.
Take one aspect of biology, medicine. If you go to your doctor or into a hospital, you will very probably be mapped. Your GP is likely to request X-rays, scans, or blood tests or possibly the lot. If you go to A &E, you might not see a doctor until blood tests or X-rays have come through.
Such mapping of course may be essential for your wellbeing, but too much reliance on it can prevent us from seeing reality. A very experienced neurologist friend of mine once lamented at what he saw as the loss of clinical skills that accompanied the rise in medical technology.
He believed it was important for doctors to become highly skilled in recognising signs and symptoms in the patient and not just those that manifest physically.
A past UK Health Secretary, Jeremy Hunt, came back from a visit to California as excited as a young man after his first kiss. The clever boys and girls in Silicon Valley showed him what they’d got. Sophisticated and available: Machines that can measure hundreds of biochemicals and many physiological signs. An Ordnance Survey of the human terrain par excellence.
In suggesting that these machines could replace GPs, Hunt clearly didn’t realise that prolonged grief, depression and acute anxiety were aspects of ill-health and could only be managed by an empathic human being and not reduced to numbers.
A while ago I heard about a hospital in Oxfordshire where a tablet (electronic type) was being trialled as a replacement for the standard chart hanging at the end of the bed.
The tablet would have far more information than its paper counterpart. In addition, if any of the patient’s physiological values become abnormal, an alarm would sound.
However, and this is the sensible bit, the developers included a ‘nurse concern’ button, which recognises the importance of human interaction. If the patient’s results are normal but the nurse is concerned from observation of the patient, he/she can sound an alarm on the tablet.
The overemphasis on mapping/modelling is concerning when dealing with individuals, but potentially disastrous when it comes to public health.
This has become all too clear from the novel and catastrophic response to Covid. In the last 18 months, public health policy has largely been informed through modelling: Mathematical abstractions of the relationships between people, micro-organisms and the wider environment, but vastly oversimplified by turning these real things into numbers. I don’t need to dwell on the nonsense spewed out by the modellers’ computers, much of which was generated by the deeply-flawed PCR test.
This gave the politicians and health bureaucrats the simplicity they desire: Charts and graphs, nicely coloured to aid immediate understanding.
But the failures of this approach have become all too clear. The public health responses that were developed over a couple of centuries from observations of people’s diets, living conditions, occupations and relationships were ditched in favour of computer-generated abstractions based on limited data with almost no predictive value, and led to the destruction of many human relationships and a large increase in ill-health.
If David Bohm were alive now, he would see that science has gone much further down the road he warned us about. Modelling is important and useful, and will become more so as computers become more advanced. But therein lies the danger. The more sophisticated the mathematics, the prettier the pictures, the more likely we are to mistake the replica for the real thing.
David Bohm was not against modelling: Most of his work depended on it. He was asking scientists to keep their eyes on the prize – a deeper understanding of the real world that mathematics alone couldn’t give.
A map, like a model, is nice to look at and can be useful. It could even save your life in some circumstances. But the world is not an abstraction, it’s a mystery that needs to be lived in all its messiness. So put your map in your pocket and go for a stroll in the woods.
