Paul Cilliers has developed a novel post-structural approach to complexity that has influenced several writers contributing to the current complexity literature. Concomitantly however, Cilliers advocates for modelling complex systems using connectionist neural networks (rather than analytic, rule-based models). In this article, I argue that it is dilemmic to simultaneously hold these two positions. Cilliers' post-structural interpretation of complexity states that models of complex systems are always contextual and provisional; there is no exclusive model of complex systems. This sentiment however appears at odds with Cilliers' promotion of connectionist neural networks as the best way to model complex systems. The lesson is that those who currently follow Cilliers' post-structural approach to complexity cannot also develop a preferred model of complex systems, and those who currently advocate for some preferred model of complex systems cannot adopt the post-structural approach to complexity without giving up the purported objectivity and/or superiority of their preferred model.
Prima facie, we make successful decisions as we act on and intervene in the world day-to-day. Epistemologists are often concerned with whether rationality is involved in such decision-making practices, and, if so, to what degree. Some, particularly in the post-structuralist tradition, argue that successful decision-making occurs via an existential leap into the unknown rather than via any determinant or criterion such as rationality. I call this view radical voluntarism (RV). Proponents of RV include those who subscribe to a view they call Critical Complexity (CC). In this paper, I argue that CC presents a false dichotomy when it conceives of rationality in Cartesian – i.e. ideal and transcendental – terms, and then concludes that RV is the proper alternative. I then outline a pragmatist rationality informed by recent work in psychology on bounded rationality, ecological rationality, and specifically embodied rationality. Such a pragmatist rationality seems to be compatible with the tenets of post-structuralism, and can therefore replace RV in CC.
William Whewell's 19 th century philosophy of science is sometimes glossed over as a footnote to Kant. There is however a key feature of Whewell's account worth noting. This is his appeal to Aristotle's form/matter hylomorphism as a metaphor to explain how mind and world merge in successful scientific inquiry. Whewell's hylomorphism suggests a middle way between rationalism and empiricism reminiscent of experience pragmatists like Steven Levine's view that mind and world are entwined in experience. I argue however that Levine does not adequately explain exactly how mind and world entwine. He could nonetheless do so if he appealed to Whewell's hylomorphic metaphor. We may prefer a reductive metaphysical explanation, but I suggest that pragmatists only have recourse to metaphor in this case. Both reductive and metaphorical explanations can enjoy great explanatory power if they exhibit a suitable measure of what I will call sematic distance. Semantic distance measures how close or how far apart explanandum and explanans are from each other in meaning. Metaphorical explanation as evident in Whewell's hylomorphism and as detailed via the notion of semantic distance presents a valuable new explanatory tool to those who hold that mind and world are entwined sans recourse to metaphysics.
I identify two versions of the scientific anti-realist’s selectionist explanation for the success of science: Bas van Fraassen’s original and K. Brad Wray’s newer interpretation. In Wray’s version, psycho-social factors internal to the scientific community – viz. scientists’ interests, goals, and preferences – explain the theory-selection practices that explain theory-success. I argue that, if Wray’s version were correct, then science should resemble art. In art, the artwork-selection practices that explain artwork-success appear faddish. They are prone to radical change over time. Theory-selection practices that explain theory-success in science are however not faddish. They are mostly stable; that is, long-lived and consistent over time. This is because scientists (explicitly or implicitly) subscribe to what I will call the testability norm: scientific theories must make falsifiable claims about the external physical world. The testability norm and not psycho-sociology explains the theory-selection practices that explain theory-success in science. Contra Wray, scientific anti-realists can then maintain that the external physical world (as expressed in the testability norm) explains theory-success.
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