John Collier

Almost fifty years ago Wilfrid Sellars described two competing ways of imagining the world, the Manifest Image and the Scientific Image. The Manifest Image is an idealization of common sense aided by critical philosophy, whereas the Scientific Image is the product of our best science. The methodologies of the two images are very different: the Manifest Image deals with experience and looks only at relations among bits of experience and analysis of experience into the relations that must lie behind it, whereas the Scientific Image is grounded in explanations of experience, typically causal explanations. This need not be a problem if the two images are compatible. Sellars argued, however, that the Manifest Image implies continuity, but the best science of the time told us that the world is made up of discrete subatomic particles and discrete transitions between quantum states, making the two incompatible. Although Sellars noted that future science might show that the world is continuous, he did not follow this up. Science in the last fifty years has given much more evidence for continuity in the world from complexity studies and Quantum Mechanics, so perhaps the two images can be reconciled after all

The paradigm of Laplacean determinism combines three regulative principles: determinism, predictability, and the explanatory adequacy of universal laws together with purely local conditions. Historically, it applied to celestial mechanics, but it has been expanded into an ideal for scientific theories whose cogency is often not questioned. Laplace’s demon is an idealization of mechanistic scientific method. Its principles together imply reducibility, and rule out holism and emergence. I will argue that Laplacean determinism fails even in the realm of planetary dynamics, and that it does not give suitable criteria for explanatory success except within very well defined and rather exceptional domains. Ironically, the very successes of Laplacean method in the Solar System were made possible only by processes that are not themselves tractable to Laplacean methodology. The results of some of these processes were first observed in 1964, and violate the Lapacean requirements of locality and predictability, opening the door to holism and nonreducibility, i.e., emergence. Despite the falsification of Laplacean methodology, the explanatory resources of holism and emergence remain in scientific limbo, though emergence has been used somewhat indiscriminately in recent scientific literature. I make some remarks at the end about the proper use of emergence in its traditional sense going back to C.D. Broad

Against standard approaches to evolution and ethics, this book develops the idea that moral values may find their origin in regularly recurring features in the cooperative environments of species of organisms that are social and intelligent. Across a wide range of species that are social and intelligent, possibilities arise for helping others, responding empathetically to the needs of others, and playing fairly. The book identifies these underlying environmental regularities as biological natural kinds and as natural moral values. As natural kinds, moral values help to provide more complete explanations for the selection of traits that arise in response to them. For example, helping in an aquatic environment is quite different than helping in an arboreal environment, and so we can expect the selection of traits for helping to reflect these underlying environmental differences. With the human ability to name, talk, and reason about important features of our environment, moral values become part of moral discourse and argument, helping to produce coherent systems of moral thought. Combining a naturalistic approach to morality with an equal emphasis on moral argument and truth, this book will be of interest to philosophers and historians of biology, theoretical biologists, comparative psychologists, and moral philosophers.

A system is autonomous if it uses its own information to modify itself and its environment to enhance its survival, responding to both environmental and internal stimuli to modify its basic functions to increase its viability. Autonomy is the foundation of functionality, intentionality and meaning. Autonomous systems accommodate the unexpected through self-organizing processes, together with some constraints that maintain autonomy. Early versions of autonomy, such as autopoiesis and closure to efficient cause, made autonomous systems dynamically closed to information. This contrasts with recent work on open systems and information dynamics. On our account, autonomy is a matter of degree depending on the relative organization of the system and system environment interactions. A choice between third person openness and first person closure is not required.

Kuhn's incommensurability thesis has generally been interpreted by friends and foes alike so as to preclude direct rational communication across revolutionary divides in science. In this paper, a weaker form of incommensurability is sketched which allows eventual comparison of incommensurable theories, but is consistent with Kuhn's model of science. Incommensurability occurs whenever the knowledge or ability to translate from the language of one theory to that of another is lacking. It can be resolved by acquiring the necessary knowledge or ability.

Goodman’s account of the ‘grue’ paradox stands at a crossroads in the history of twentieth century epistemology. Published in 1954, Fact, Fiction, and Forecast is a reaction to the logical empiricist views that held sway in the first half of the last century and anticipates many of the conventionalist and/or relativist moves popular throughout the second half. Through his evaluation of Hume’s problem of induction, as well as his own novel reformulation of it, Goodman comes to reject a number of the fundamental parts of logical empiricism. In particular, Goodman argues that the formal epistemic methods the logical empiricists wanted to rely upon are insufficient. This leads him to turn towards conventionalism, which is the basis of his rejection of the objective view of knowledge. In his conventionalism he is a precursor of writers such as Hanson, Kuhn and Feyerabend, who, seeing the inadequacy of formalism, sought to fill the gaps it left in epistemic methodology with scientific values, tacit knowledge and linguistic practices. Making use of Susan Haack’s distinction between three different kinds of foundationalism, we analyse Goodman’s position and its relation to the views of the logical empiricists. The two are reflections of each other in that, where the logical empiricists are foundationalists in their views on empirical evidence, methods used and objective criteria of justification, Goodman consistently opts for the corresponding coherentist options. As it turns out, this choice of options makes it impossible for Goodman to deal with the very objections he raises against the logical empiricists. In adding the new problem of induction to the old one, Goodman adds a problem which clearly can not be resolved by a purely syntactic solution. The charge Goodman raises is that logical empiricists cannot determine which predictions are sound and which are not. We argue that his method of identifying acceptable predictions based on the use of entrenchment is, in the end, arbitrary and only postpones the underlying problem.

In these notes I want to address some issues concerning self-organization that seem to me to apply generally from the micro-physical through the biological and social to the cosmological. That is, they are a part of the general theory of self-organization. I prefer to distinguish the theory of selforganization from the analysis of the concept of self-organization (which Maturana claims is oxymoronic, since there is no self that organizes1). General usage gives us something to which the term 'self-organization' refers. We can set aside the question of whether or not selves can really do such a thing until we know what it is they are supposed to do.2 This approach also allows the possibility that self-organization does not pick out a single natural kind, but may refer to a range of things that are grouped together by a Wittgenstein style “family resemblance”

Typically, we think of both artificial and natural computing devices as following rules that allow them to alter their behaviour (output) according to their environment (input). This approach works well when the environment and goals are well defined and regular. However, 1) the search time for appropriate solutions quickly becomes intractable when the input is not fairly regular, and 2) responses may be required that are not computable, either in principle, or given the computational resources available to the system. It may seem that there is no way to deal with these conditions, but if we think of systems as dynamical non-equilibrium autonomous entities, there are ways to deal with the unexpected and irregular by taking advantage of self-organising and self-preserving capacities of such systems. A generalised force acting on a system far from equilibrium will cause the system to reorganise itself in the direction of the generalised force in such a way as to minimise its effects (Nicolis and Prigogine, 1977), but there can be unpredictable effects in different generalised directions in the system’s phase space. In order to preserve system integrity, these effects must be damped or used for further self-reorganisation, possibly starting a cascade effect that leaves the system in a substantially different state in which it can handle further instances of this sort of information. This model is similar to and extends the theoretical model of accommodation and assimilation of Piaget, derived from his observations of the development of intelligence in children

Wilfrid Sellars described his Manifest Image and Scientific Image as idealizations of our common sense and scientific views of the world, including our own special role in the world as humans. If, as Sellars suggested, there is an irreconcilable conflict between these images, it may not be possible to reconcile science with common sense. The Scientific Image, as we have inherited it, has a strong reductionist element that seems to imply that things are not really as they appear to common sense. Although some amount of discrepancy between common sense and science is not a problem, since we know from experience that we may be mistaken about nearly any given thing, a systematic clash between science and common sense presents problems for the acceptance of one, the other, or both views

Progress has become a suspect concept in evolutionary biology, not the least because the core concepts of neo-Darwinism do not support the idea that evolution is progressive. There have been a number of attempts to account for directionality in evolution through additions to the core hypotheses of neo-Darwinism, but they do not establish progressiveness, and they are somewhat of an ad hoc collection. The standard account of fitness and adaptation can be rephrased in terms of information theory. From this, an information of adaptation can be defined in terms of a fitness function. The information of adaptation is a measure of the mutual information between biota and their environment. If the actual state of adaptation lags behind the state of optimal adaptation, then it is possible for the information of adaptation to increase indefinitely. Since adaptations are functional, this suggests the possibility of progressive evolution in the sense of increasing adaptation. Keywords: evolution, information, adaptation, fitness, entropy, progress..

In Robert West’s talk last week, dynamical systems theory (DST) was applied to a specific problem involving interacting symbolic systems, without much reference to how those systems are embodied or related to other types of systems. Despite this level of abstraction, DST can yield interesting results, though one might be left wondering if it really leads to understanding, or what it all means. In particular, Robert noted problems he has in convincing referees that the sort of explanation he gave can give a useful understanding, and that it doesn’t invoke dubious notions with its references to emergence, holism, and mathematical openness

Supervenience is a relationship which has been used recently to explain the physical determination of biological phenomena despite resistance to reduction. Supervenience, however, is plagued by ambiguities which weaken its explanatory value and obscure some interesting aspects of reduction in biology. Although I suspect that similar considerations affect the use of supervenience in ethics and the philosophy of mind, I don’t intend anything I have to say here to apply outside of the physical and biological cases I consider.The main point of this paper is that there is a property of biological systems which makes it both misleading and inappropriate to reduce central biological phenomena to the properties of underlying components. Despite this, reductive explanation has been a major source of innovation in biological theory. The apparent tension can be resolved if underlying properties are explanatorily relevant to the higher level phenomena even though the latter are not strictly reducible to the former. Supervenience, I will argue, is not robust enough to deny reduction while supporting explanatory relevance.

In this critical notice, I argue that the semantic view championed by Thompson no logical advantage over the syntactic view of theories, especially in the area of interpretation. Each weakness of the syntactic view has a corresponding weakness in the semantic view. In principle the two are not different in power, but it is sometimes better to adopt one rather than the other, for practical reasons. I agree with Thompson that many issues in the philosophy of biology can be illuminated by the semantic view, but that other things, especially deriving specific prediction, are best understood with the syntactic view

Biological systems are typically hierarchically organized, open, nonlinear systems, and inherit all of the characteristics of such systems that are found in the purely physical and chemical domains, to which all biological systems belong. In addition, biological systems exhibit functional properties, and they contain information in a form that is used internally to make required functional distinctions. The existence of these additional biological properties is widely granted, but their exact nature is controversial. I will address first the issue of biological function, and then turn to the issue of information in biosystems

Systematics, along with the other comparative biological sciences and certain astronomical disciplines, is much more concerned with form and organization than other biological and physical sciences, in which dynamics plays the central role. Within the biological sciences, Nelson (1970) characterizes disciplines that study diversity and patterns “comparative” and those that search for process and dynamics “general.” The goal of “general” science is to uncover the mechanisms that unify observed phenomena. Whether the physicist sees herself, like Newton (1953: 3-5), to be discovering fundamental causal explanations, or like Duhem (1962: 19-30), to be uncovering a natural classification, dynamical concepts referring to essentially hidden processes are indispensable. Much of comparative biology, in contrast, is primarily descriptive, with explanations taking a secondary role, at least until the diversity is described and comparisons made. Unlike the general sciences, in which elegance and quantitative analysis have long been major indicators of truth, the comparative sciences stress complexity, happenstance and qualitative analysis. In systematics in particular, theory and explanation are often thought to play a minimal role, if any at all1