The Science Myth: God, society, the self and what we will never know
Dominique Chu, 2013, iff Books, 428 pgs.
Reviewed by Michael L Anderson
I enjoyed the Science Myth. While I often found myself jotting down notes over various statements that bothered me, this is the sign of a good book. It provoked me. Chu’s thesis may be roughly paraphrased as:
Whatever science may be, it does not consist solely of physics. The techniques of physics are wonderfully effective, but they simply do not carry over to biochemistry, computer modeling, economics, etc. (This would be painfully obvious were it not for those immodest physics writers and funding requesters who use silly terms like the ‘Theory of Everything’.)
Science is what science does. Chu takes a naturalistic turn here, somewhat at odds with his greater argument. If science is just what scientists do, and no one authority and no underlying truth-guidance mechanism is governing the practitioners, then we should worry for the future of science. Indeed, it would be foolish not to worry at this point, regardless of what science ‘really’ is. Where is science going? Who’s minding the store?
Scientists tend to form a closed “Scientific Rationalism (SR)” elite. This shadowy group is Chu’s bête noire. He mentions only a few proper names on rare occasions, but a large proportion of the book is a polemic against “SR.” Elites grow sclerotic, we must agree.
One thing Chu finds objectionable in SR is its intolerance of conventional religion. They generally assert that there is nothing meaningful to discuss that cannot be treated in scientific terms. Our cherished folk beliefs can be shown to be illusions, misconceptions, chimeras, etc. And they arrogantly claim that science leaves nothing else for explanation. Since Chu is reticent to name names here, I cannot be sure whom exactly he means, but it is a familiar theme. Chu questions the completeness of science.
At its best, Science Myth explains, often in great detail, various research programs of the past. Science is amazingly clever at probing complex processes, isolating and analyzing, creating models and testable hypotheses. Yet there is always a huge noumenal unknown. We rarely acknowledge the gaps in our understanding because it sounds unprofessional, nay philosophical, to ask, ‘but what is an electron?’ A species? Consciousness? A simulation? We see the shadows play against the cave wall, and we can write numerous technical papers on various aspects, but we never wholly capture the thing itself. And when it comes to biological processes, we cannot even capture essences. Galileo did at least capture the essence of gravitation. That is, he demonstrated that every thing with mass, regardless of its color, personality, country of origin, etc. will fall in the gravitational field according to an inverse- square law formula.
Chu uses a somewhat narrow, curious metonymy in which Galileo stands in for all of physics, Jacques Monod for theoretical biology, Thomas Metzinger for over-zealous reductionists, and perhaps a few others. As a balanced exposition, the book is lopsided. Monod gets fifty-odd pages of rather technical treatment, which I found interesting and mostly understandable, but which a biochemist might find inadequate. The detailed treatment definitely supports the overall thesis: how biology (at least, as practiced and understood by Monod) lends itself to severe and illuminating reduction as long as we meet it halfway. We must always let biology be biology, wet and sticky. Nonetheless, while Monod’s hypotheses reveal much about cell metabolism and genes, they never yield a General Theory of biology. We never see the biological equivalent of gravitation, some universal force of organic complexification and cooperation. We see many interesting mechanisms that act on highly unique structures under unique circumstances. We believe that life is the sum total of such mechanisms, but this is far beyond the ability of human brains or computer models to capture completely.
With a good metaphor, Chu describes our knowledge in fields such as biology as “flat-pack furniture.” Think of what you get at Ikea. You do not buy a futon, strictly speaking. You buy a dense box full of laminated boards, screws, pins. That is metaphorically what biology delivers as well. However, Ikea gives its customers a well written, illustrated, multilingual instruction sheet. Nature does not.
Chu describes termite mounds: complex, efficient structures that would seem to require a team of degreed civil engineers to design and construct, not a bunch of dumb, random-walking insects.
“Physicists tend to dislike this lack of generality. The shape of the termites’ mounds depends on the environment and some very particular parameter settings. Change them and you may change everything. There is an inherent messiness in such simulation models. They are a far cry from the platonic beauty of equations in physics. Yet, the need of simulation models is just a reflection of the fact that there is no essence to termites in the same way as there is an essence to the free fall. When it comes to understanding the behaviour of termites, the details matter. This is apparently at odds with the established Galileian idea of physics. Consequently, physics has traditionally ignored complex systems. Not that termites are not interesting to study, but they do not allow general theories and hence are not loved by physicists.” [165]
The theme of essence arises again in the work of Per Bak and sand pile collapsing, a phenomenon familiar to any child who has built castles at the beach. There are numerous examples of similar behavior (Darwinian evolution, forest fires...) There are several mathematical models of the phenomenon, some very interesting and insightful, but none comprehensive, none ‘Galilean,’ as Chu would say.
Chu hits his pace midway, in the discussion of complexity theory, biology, and cellular automata. Here many elements come together. He acknowledges the intriguing lifelikeness of the patterns, but he strongly counsels against overenthusiasm. These automata are not independent, they do not “move” on their own. They lack “agency”. I do not fully accept this criticism. Yes, the patterns are embedded in a larger context. Yet everything we know about spacetime, physical states, nothingness, motion, entanglement suggests that this is exactly how it works. That the same may hold for biology is rather interesting. A link, a commonality. Chu suggests that the new complexity models find only statistical commonality with the real world, such as a manifestation of power law distributions, and that this misses both the generality of Galilean physics and the particularity of Monodian biology.
Chu discusses climate modeling. While most modelers’ conclusions agree in the broadest outline, it is remarkable how different they may be in detail. This is one area of science that will be especially important to get right in years to come. Any attempted corrective measures will be hugely disruptive to society. Political controversy and misinformation, if not outright violence, will likely ensue. The scientists need to hold their position firmly in mind, even if the position is weak and requires occasional modifications. This is not something the general public tends to understand.
Science Myth is marred by constant, snide sexist comments. The second half of the work ventures more into philosophy and becomes somewhat of a rant. Chu talks about Popperian falsification being rare in medical research, but perhaps neglects the fact that the null hypothesis is standard practice. A common research program is to disprove the null hypothesis, that drug X has no effect whatsoever upon malady Y. This seems to me a form of falsification. Chu insists that medical research is hit or miss, not a test of deep cutting general theories. Medical research is not my field, but this is not entirely consistent with I have seen in my professional encounters with biochemical labs. I believe that Chu’s primary vocation is in computational biochemistry.
Science Myth veers far outward in the latter chapters. Primarily, it is a rather stale, light-weight rehash of the topic of irreducible subjectivity, which Chu insists on calling "fundamental essence of a person" (FUDESS). His perennial nemesis, the Scientific Rationalists (SR) cannot account for FUDESS, Chu explains, and this bothers them. If Chu is thinking of Dennett and Dawkins as representatives of SR, these writers do tend to insist that we must naturalize our seeming subjectivity. And many other philosophers find this too radical and heavy-handed an expurgation, not that any clear alternative avails. It is a stalemate.
I suspect what will happen in years to come is that highly autonomous robots will develop to the point where they can learn for themselves and communicate with each other. Quite likely this will be in a military / police context. Then we will have ‘invented’ artificial consciousness, but it will be mostly the result of ordinary engineering and evolution. It will not require radically new science. We will consider these systems conscious insofar as they surprise us, which is the gist of the Turing test. We will know a lot about their mechanics, but there will necessarily be a large mysterious residuum. We will never know ‘what it’s like’. This is a mere futuristic prediction, but the main point is that this is how science and technology generally progress. Researchers take risks, push ideas, gain footholds, make advances. It is often indirect. New ideas come from left field. We never get to ask, ‘but what the heck is an electron?’ Science can never be completely direct or predictable, although some research areas are far more promising than others. Scientists are a lot like those termites.
Chu does not deny the efficacy of science, but he is troubled by its closed elitism. Rightly so, I agree. It is noteworthy and troubling that the general arc of scientific progress seems to have stalled in the last 25 years. There have been no radically new, massively compelling theories in math or science since superstring theory blossomed in the 1990s. This is despite a roughly 25% increase of world population and strong economic growth in Africa, Asia and Latin America. There are many more smart people around, and less deep science happening. ‘Normal science’ goes about its business. Technology continues on its trajectory, but has always relied on fundamental science for new strategic moves. In the US, the cost of university education, especially for risky careers, has far outpaced the financial means of ordinary Americans. Quo vadis, scientia?
Michael L Anderson, manderson @ blackoakeng.com, holds an MSEE and an MS Physics. He served in the USMC. He now works as a consulting design engineer and business executive in New York.
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