A Conversation with Massimo Pigliucci on Scientific Explanation
Massimo Pigliucci is a philosopher and biologist who is Professor of Philosophy at the City College of New York. In this conversation, we talked about the nature of scientific explanation.
Massimo Pigliucci is a philosopher and biologist who is Professor of Philosophy at the City College of New York. He has a doctorate in genetics from the University of Ferrara, a PhD in biology from the University of Connecticut, and a PhD in philosophy of science from the University of Tennessee. He publishes a regular column in Philosophy Now entitled “The Art of Living”. His books include How to Be a Stoic: Using Ancient Philosophy to Live a Modern Life and Nonsense on Stilts: How to Tell Science from Bunk. His forthcoming book is Beyond Stoicism: A Guide to the Good Life with Stoics, Skeptics, Epicureans, and Other Ancient Philosophers. You can learn more about him here. In this conversation, we talked about knowledge, instrumentalism, and scientific explanation.
Vatsal: You have stated your preference for Plato’s definition of knowledge as justified true belief. However, you’ve also observed regarding justification that “if we enforced that clause in the Platonic definition of knowledge, it would turn out that we all know very few things comparatively speaking”. Additionally, you’ve argued that the intuition that “true and justified beliefs don’t require a causal explanation”, while handy “as a heuristic and first approximation”, fails to “survive careful scrutiny, and needs to be abandoned”. This brings me to a question about current artificial intelligence (AI) systems. A few years ago you commented on something related to this and concluded, “science advances only if it can provide explanations, failing which, it becomes an activity more akin to stamp collecting”. When you encounter AI systems that can process vast amounts of data, identify regularities, and make increasingly successful predictions, do you, as a scientist and philosopher, feel that there is still something more—like justification or causal explanation—that must be demonstrated before you can say these systems possess knowledge in the same way humans do?
Massimo Pigliucci: That’s right. Current Large Language Models do not possess knowledge, they produce output on the basis of correlation analyses of large amounts of text and symbols. This is, of course, impressive, and it may be useful under certain conditions, but it’s not knowledge, and certainly it’s not understanding.
I’m not suggesting that AI will never be capable of knowledge and understanding. I don’t know, and I doubt anyone else does. But current predictions of AI “surpassing” humans in those realms are baloney. The software architecture of LLMs simply does not allow that, though it does allow these programs to “learn” and to produce impressive, if often limited or even faulty, outputs.
Going back to Plato: I think it would be a good thing if we embraced his definition of knowledge as justified true belief precisely because we would finally realize that we know far less than we think we do. That may make us a little more cautious and humble, which is something that doesn’t come natural to the human race.
As for causal explanations, I meant that scientific knowledge cannot do without causal explanations, but everyday common knowledge may. For instance, I “know” how to drive a car, even though I don’t necessarily understand all the causal connections that make possible for a car to be driven. My lack of knowledge of such causal connections is the difference between me as a regular user of the technology and an engineer who actually knows how cars work and could build, not just drive, one.
Vatsal: You have written about the mechanistic philosophy “that developed a conception of the universe in purely mechanical terms”. You note how this “mechanization of nature proved an important driving force behind the Scientific Revolution, and at the end of the 17th century culminated in Newton’s theory of motion”. There was a controversy that Newton’s theory of universal gravitation allowed for interactions between bodies without contact, resembling, his contemporary critics pointed out, the unintelligible occult forces that the mechanical philosophy was intended to eliminate. Newton appears to have favored some kind of instrumentalism at times, as when he famously wrote, “I frame no hypotheses”. More recently, Stephen Hawking described himself as taking “the positivist viewpoint that a physical theory is just a mathematical model and that it is meaningless to ask whether it corresponds to reality. All that one can ask is that its predictions should be in agreement with observation”. You have described yourself as a realist with respect to the external world, but noted that you “do have strong sympathies for instrumentalism in philosophy of science”. What do you think about this kind of instrumentalism? Like with the AI systems, do you feel that there is something that a scientific theory ought to provide beyond successful predictions?
Massimo Pigliucci: I sympathize with instrumentalism because it is a minimalist, and very convincing, way of looking at scientific theories: we produce models of the phenomena we observe, and if these models are successful at predicting new phenomena we are satisfied. Otherwise, we set aside the model and build a new one.
And yet, there is something profoundly unsatisfying about this pragmatic view of science, and I honestly don’t believe that Hawking—the same guy who said that his theories allow us to look into the mind of God—was truly an instrumentalist.
I think the objective of science is not just to predict the phenomena, but to give us better and better ideas about what Kant called the noumena, that is, the layer of reality that produces the phenomena.
The notion of realism in science becomes controversial and debatable only when we are talking about the very frontiers of physical science, where we are pushing the limits of human understanding. But consider more mundane examples instead. When Galileo observed certain structures around the planet Saturn and concluded that they were not satellites, but rings, did he mean just to produce a model? No, he thought that there really are rings around Saturn. And subsequent telescopic observations, and eventually spacecraft flybys, confirmed his hypothesis. That is good and satisfactory science.
Similarly, when Watson and Crick hypothesized that DNA is structured as a double helix they didn’t mean their hypothesis to be simply a model capable of accounting for the X-ray crystallography data produced by Rosalind Franklin. They meant to say that DNA really is structured as a double helix. And it is, as direct electron microscope observations have amply confirmed.
The issue of instrumentalism only arises in fundamental physics and, to a lesser extent, in cosmology, that is at scales of the ultra-small and the super-large. That’s because at those scales a lot of useful analogies and metaphors break down and we are pushing the limits of our understanding. But even if human understanding should turn out to be forever limited, that doesn’t mean that there is no actual reality out there, and we have been able to correctly (it seems) grasp an increasing portion of it, ever since the beginning of the scientific revolution.
Vatsal: A natural question that arises is regarding the nature of justification or explanation, and here people sometimes invoke the four kinds of causes that Aristotle proposed. You have dealt with the claim that “modern science ever since Francis Bacon has illicitly dropped two of Aristotle’s famous four types of causes from consideration altogether, thereby unnecessarily restricting its own explanatory power”, arguing instead that “Darwin made it possible to put all four Aristotelian causes back into science”. You have described science as a Wittgenstein-type cluster concept, which is “characterized by a number of threads connecting instantiations of the concept, with some threads more relevant than others to specific instantiations”. Do you think a broader view of explanations beyond efficient causes expands the explanatory power of science against the kind of reductionism that you have debated against, according to which “the genetic-molecular level of analysis is the fundamental one in biology, and that everything else, from cell behaviors to ecosystem functioning, ultimately reduces to the properties of the molecules of inheritance”?
Massimo Pigliucci: You raise a couple of distinct, yet related points. Let’s start with Aristotle’s causes. He famously argued that if, say, I want to have a complete understanding of Marcus Aurelius’s statue on the Capitoline Hill in Rome I need to describe it in terms of four “causes,” or explanatory aspects: (i) Material cause — what is the statue made of? (ii) Efficient cause — what made the statue possible? (iii) Formal cause — what is the structure or form of the statue? (iv) Final cause — what is the statue for?
In the case of Marcus’s statue the answers are: (i) Bronze; (ii) A particular (unknown) sculptor; (iii) It represents the emperor on a horse; (iv) It was made to honor the emperor.
Now, supporters of Intelligent design creationism, like William Dembski, claim that Francis Bacon, one of the early philosophers of science, eliminated both formal and final causes from the realm of science, which—in their opinion—resulted in a science that is crippled and incomplete. The two missing causes are the so-called teleonomic ones, because they concern the apparent purposefulness of a thing (from the Greek telos, purpose, and nomos, law). What I argue instead is that teleonomic questions simply don’t apply to sciences like chemistry and physics. It makes no sense to ask why atoms or galaxies are the way they are. They are that way as a result of the laws of physics, period.
But in the case of living organisms, it does make perfect sense to ask “why”? Why are the eyes of a vertebrate made of those particular materials and structured in that particular way? Because their function is to see. Atoms and galaxies don’t have functions, but biological structures do. The difference is the phenomenon of natural selection, the fundamental Darwinian insight that explains why living organisms are the way they are.
To get back to your second point, the one concerning reductionism, yes, including the teleonomic causes in our explanations requires a broader, more organic view than straightforward reductionism allows, because addressing all four of Aristotle’s causes necessitates multiple levels of analysis, not just the most basic one. Biological explanations do certainly benefit from molecular biology, biochemistry, and all the other “reductionist” sciences. But that’s not enough. We also need the organismal disciplines, like evolutionary biology and ecology, to more fully make sense of what Darwin called this grand (evolutionary) view of life.
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