contact@onbelief.orgRequirement for a Philosophy and Science of Life in Matters of Belief
The Need to Explain Complexity
The arguments of previous of previous pages make it clear that our philosophy of belief should not be shaped exclusively by the simplicity of systems arrived at by the extreme reductionism of physics and chemistry and their associated mathematical models. On the other hand we must not underestimate the sophistication of systems that can develop from the emergent properties of simple rule-bound 'agents' acting together to form complex systems (on this site see Economy and Emergence). The ant colony and termite mound are well known biological examples of emergence. The non-dynamic cellular automaton, or space filling rule, is now well known in computing related to pattern formation. Even in that very limited situation an unpredictable complexity arises by a set of relatively simple rules for filling a grid (see example). These simple observations suggest that rather than see a requirement for intelligence in the formation of life we should study how complexity can emerge given the appropriate driving forces of nature. The effects of solar radiation and geochemistry are 2 of the obvious foundations for enquires into the formation of life.
Only in the theoretical world of the theoretical physicist is the entire biosphere reducible to a series of retrospectively descriptive calculations. Prediction of what the state of the biosphere will be in future is neither conceptually nor practically possible. If we could go back in history and re-run the the formation of the world we would not end up with my capital city of Edinburgh for example. Sensitivity of complex systems to extremely small variations in initial conditions means a lack of predictive certainty at the level of detailed description. We can think of many reasons why the city of Edinburgh would not exist, starting from the most general such as the randomness of continental plate movement down to highly specific causes like the premature death of certain individuals.
Limits of Reductionism and Domains of Predictive Competence
The role of reductionism is to observe complex systems and produce a series of discontinuous descriptions that describe the operation of the systems at different levels. The predictive domain for each level of level of analysis will then remain at the level at which the analysis has been made. For example the prediction that the sun will collapse in the future says nothing about the very unlikely possibility of biological species of the future escaping to another solar system. That prediction is not within the domain of predictive confidence of astronomical description and theory. In short there will never be a concise 'theory of everything' we can only refine our understanding of the way the world works by the elaboration of more and more descriptive beliefs derived from observation and logic.
Reductionism as applied to life is not as the Oxford chemist Peter Atkins would more generally argue 'reduction of the world to its constituent parts and putting it back together again'. That ideas seems attractive in the domain of synthetic chemistry for it expresses what the chemist tries to achieve. It is not however possible to fully describe complex systems and the very attempt to do so seems to be contrary to the principal of computational equivalence. To put the world back together again we would need a system as computationally complex in equivalent input-output terms as the world itself. Predictions of all sorts require Bayesian degrees of belief which thus involve a level of indeterminacy. In other words no conceivable amount of simple reductionist descriptions can in practice 'reverse engineer' the world or predict the precise details of its future course.
Predictability and Social Decisions
While a complex non-linear or chaotic system, such as life, is in operation, we cannot for example predict bifurcations of fate which they exhibit. By time-lapse photography you may watch one single cell migrate around on an apparently simple artificial surface but you cannot predict its next turn. The investigator can only know something about the range and frequency of turns that it can make. If the cell had a brain it would not know itself the exact course of its behaviour, as it is not predetermined. (In technical terms cells crawling around, in almost homogeneous 2-D environments, undergo a type of random walk that can be described by Einstein's 1905 paper on Brownian motion. Also see a simulation). Even as something as apparently regular as the healthy human heart has small but unpredictable beat-to-beat variations of timing. When disease strikes predictability of function can then entirely disappear and so result in the unpredictability of premature death. [For a non-mathematical description see Chaos theory in organizational development. Alternatively see a dynamic mathematical visual illustration or at wikipedia logistic map, bifurcation diagram] When complex systems can only be described by the interaction of large numbers of variables at different parametric values the outcome is expected to be unknowable (see wikipedia article on catastrophe theory). Reductionism is therefore almost unidirectional in terms of understanding the functioning of complex systems. We can dissect the component parts of a complex system such as a human being and by making local predictions understand how each part behaves. We cannot however re-construct conceptually or practically the whole and functioning system.
This realisation does not of course mean that we reject the validity or the predictive power of science or its technologies such as medicine or engineering, which can completely transform our lives. The sheer utility of each science cannot be doubted, within its own domain of competence, unlike metaphysics. It in fact means that more of us on this planet need to turn our attentions to the practice of science and the philosophy of science. We need however those who think in the social, political, ethical, creative or even religious domains to point out the limitations of science and its potential for destruction as well as betterment of the human condition. Indeed in philosophical terms it is because of the ultimate lack of predictability of complex systems that we need other approaches that exist outwith the domain of science itself. A scientist cannot predict with certainty the outcome of her own action in perturbing the dynamic and complex systems of your planet. Science itself tell us this. It is therefore entirely wrong of Peter Aktins, brilliant though he may be, to suggest that we should only ask "how questions" and never "why questions". Science gives us more reasons to ask "why questions" not less. Atkins and his sort will prove to be extremely dangerous unless others ask of their activities 'Why'? If scientists like him refuse to do so then the philosophers of logical positivism and the ethicists must do so. With the decline of religious influence we rely even more heavily upon them. (for further discussion on this site see Can science by itself provide us with a way to live?)
Re-Integrating the Cciences and Philosophy
It seems desirable that a comprehensive philosophy of belief should be underpinned by a comprehensive philosophy and science of life if it is to have legitimacy or meaning in the wider world. However each discipline and each individual within the discipline must of necessity choose an area at which to enter the chain of analysis and none should be considered more or less indispensable than the other. Biophysics or the analysis of behaviour and social systems are equally valid starting points, despite what some physicists seem to have assumed (See Philosophy of biology at Wikipedia). The 'father' of nuclear physics Ernest Rutherford said "In science there is only physics; all the rest is stamp collecting". Clearly he undervalued the utility of descriptive observations of complex systems achieved through systematic research and also under-estimated the difficulty of describing complex systems.
Instead of disputing the value of a particular level of analysis, the logical positivist might ideally like to integrate a philosophy of life and belief by connecting a very long chain of reductive analysis supported by observation, prediction, verification, and coherence. That chain might begin by establishing 'laws' of terrestrial life and proceed from there by integrating biophysics, biochemistry, molecular biology, microbiology, cell biology, genetics, zoology, anatomy, physiology, endocrinology, pathology, neuroscience, psychology and anthropology. Such a rich substrate of descriptive propositions will ultimately lead to a richer understanding of the nature of belief. In practice, it is likely that no more than a patch work of knowledge with holes, boundaries and discontinuities will be encountered.
Overcoming the barriers created by academic disciplines should be viewed as a productive and rewarding challenge for scientists and philosophers and those of us who follow their activities. Indeed change, modification and development of belief should be viewed as legitimate and a source of hope for the future.
Notable exemplars of the attitude that the biological sciences should inform philosophy are the philosophers Patricia Churchland and Paul Churchland. Mrs Churchland appears to have whole heartedly embraced the neurosciences for example. (To watch a talk by Patricia Churchland at Beyond Belief II that is steeped in the neuroscientific approach click here >). Although her apparent obsession with particular molecules is perhaps undesirable, her general approach should be seen as much more welcome than the 'other worldliness' of metaphysics.
On the Nature of Belief
www.onbelief.org
Scotland, 12th October 2007 and thereafter
Copyright 2007 onwards
