John Collier

To account for a perceived distinction it is necessary to postulate a real distinction. Our process of experiencing the world is one of, mostly unconscious, interpretation of observed distinctions to provide us with a partial world-picture that is sufficient to guide action. The distinctions, themselves, are acorrigible (they do not have a truth value), directly perceived, structured, and capable of being interpreted. Interpreted experience is corrigible, representational and capable of guiding action. Since interpretation is carried out mostly unconsciously and in real time, the two aspects are present in experience together so that it is difficult to separate them out

If two successive theories are semantically incommensurable, we have no way to make a complete comparison of their contents. If so, we have no way to verify that the highly confirmed content of the successor is greater than that of its predecessor, and we cannot verify that scientific knowledge has accumulated across the theory change. Thus, incommensurability creates a problem for the justification of the standard cumulative conception of scientific progress. ;To resolve this problem, I distinguish irresolvable strong in commensurability from weak incommensurability, which is resolvable. I argue that Kuhn's arguments, insofar as they are sound, support only the latter. Cumulative progress is therefore not only possible, but in principle justifiable. Nonetheless, I support most of Kuhn's claims about the incommensurability of successive paradigms. ;My argument for weak incommensurability depends on an interpretation of scientific theories which makes the way a theory is understood an integral part of the theory. Both syntactic and semantic approaches to theories fail to deal with the incommensurability problem because they ignore this pragmatic aspect. I offer a context-dependent semantics based on contemporary pragmatics which can both represent the incommensurability problem and show how it can be resolved.

Every manifestation of information, semiosis and meaning we have been able to study experimentally has a physical form. Neglect of their dynamical (energetic) ground tends towards dualism or idealism, leaving the causal basis of semiosis and the causal powers of representations mysterious. Consideration of the necessary physical requirements for the embodiment of semiotic categories imposes a discipline on semiotics required for its integration into the rest of science, especially for the emerging field of biosemiotics, as well as any future extensions to chemistry physics or other realms that might constitute a general, primal semiotics. Without this discipline, or something equally strong, there is a risk of projection of anthropomorphic semiotic terminology onto unsuitable hosts, leading, if unchecked, to the sort of animism that biology in particular has only recently escaped. The problem is suspect whenever teleological notions are used outside of mental or social contexts.1 Although our animistic ancestors may have had a closer rapport with Nature than modern scientists, contemporary scientific explanation requires an understanding of causal structure (Salmon 1984). On the other hand, unless the causal rendition of semiosis can capture full blown cognitive semiosis, it is likely to be too restrictive for the evaluation of primal semiosis in general.

Emergence has traditionally been described as satisfying specific properties, notably nonreducibility of the emergent object or properties to their substrate, novelty, and unpredictability from the properties of the substrate. Sometimes more mysterious properties such as independence from the substrate, separate substances and teleological properties are invoked. I will argue that the latter are both unnecessary and unwarranted. The descriptive properties can be analyzed in more detail in logical terms, but the logical conditions alone do not tell us how to identify the conditions through interactions with the world. In order to do that we need dynamical properties – properties that do something. This paper, then, will be directed at identifying the dynamical conditions necessary and sufficient for emergence. Emergent properties and objects all result or are maintained by dissipative and radically nonholonomic processes. Emergent properties are relatively common in physics, but have been ignored because of the predominant use of Hamiltonian methods assuming energy conservation. Emergent objects are all dissipative systems, which have been recognized as special only in the past fifty years or so. Of interest are autonomous systems, including living and thinking systems. They show functionality and are self governed.

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.

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.

It is generally agreed that organisms are Complex Adaptive Systems. Since the rise of Cybernetics in the middle of the last century ideas from information theory and control theory have been applied to the adaptations of biological organisms in order to explain how they work. This does not, however, explain functionality, which is widely but not universally attributed to biological systems. There are two approaches to functionality, one based on etiology (what a trait was selected for), and the other based in autonomy. I argue that the etiological approach, as understood in terms of control theory, suffers from a problem of symmetry, by which function can equally well be placed in the environment as in the organism. Focusing on the autonomy view, I note that it can be understood to some degree in terms of control theory in its version called second order cybernetics. I present an approach to second order cybernetics that seems plausible for organisms with limited computational power, due to Hooker, Penfold and Evans. They hold that this approach gives something like concepts, certainly abstractions from specific situations, a trait required for functionality in its system adaptive form (i.e., control of the system by itself). Using this cue, I argue that biosemiotics provides the methodology to incorporate these quasi concepts into an account of functionality.

A major goal of science is to discover laws that underlie all regular phenomena. This goal is best satisfied by eternal principles that leave fundamental properties unchanged and unchangeable. Science has been forced to accept that some processes, especially biological processes, are inherently time oriented. It can either forgo the ideal of universal principles, and account for temporality through specific boundary conditions, or else incorporate the sources of change directly into fundamental principles that are the same for all times and places, and for all temporal scales. In the past, unifying principles adequate for biology have caused trouble for physics, and vice versa. Recent work at the intersection of non-equilibrium statistical mechanics and information theory suggests that physics and biology can finally be reconciled.

Anticipation allows a system to adapt to conditions that have not yet come to be, either externally to the system or internally. Autonomous systems actively control the conditions of their own existence so as to increase their overall viability. This paper will first give minimal necessary and sufficient conditions for autonomous anticipation, followed by a taxonomy of autonomous anticipation. In more complex systems, there can be semi-autonomous subsystems that can anticipate and adapt on their own. Such subsystems can be integrated into a system’s overall autonomy, typically with greater efficiency due to modularity and specialization of function. However, it is also possible that semi-autonomous subsystems can act against the viability of the overall system, and have their own functions that conflict with overall system functions.

Integrating concepts of maintenance and of origins is essential to explaining biological diversity. The unified theory of evolution attempts to find a common theme linking production rules inherent in biological systems, explaining the origin of biological order as a manifestation of the flow of energy and the flow of information on various spatial and temporal scales, with the recognition that natural selection is an evolutionarily relevant process. Biological systems persist in space and time by transfor ming energy from one state to another in a manner that generates structures which allows the system to continue to persist. Two classes of energetic transformations allow this; heat-generating transformations, resulting in a net loss of energy from the system, and conservative transformations, changing unusable energy into states that can be stored and used subsequently. All conservative transformations in biological systems are coupled with heat-generating transformations; hence, inherent biological production, or genealogical proesses, is positively entropic. There is a self-organizing phenomenology common to genealogical phenomena, which imparts an arrow of time to biological systems. Natural selection, which by itself is time-reversible, contributes to the organization of the self-organized genealogical trajectories. The interplay of genealogical (diversity-promoting) and selective (diversity-limiting) processes produces biological order to which the primary contribution is genealogical history. Dynamic changes occuring on times scales shorter than speciation rates are microevolutionary; those occuring on time scales longer than speciation rates are macroevolutionary. Macroevolutionary processes are neither redicible to, nor autonomous from, microevolutionary processes.