Don Ross

Though the days of consciousness-raising are mostly passed, the days of consciousness seem to be upon us, or, at least, to be upon philosophers. Dennett's recentConsciousness Explainedis the flagship for a flotilla of new major works on the subject, by Flanagan, Jackendoff, Searle, Seager and others. It seems to be something of a convention in such work that one begins by complaining that consciousness is a sorely neglected topic among philosophers; this cliché has created the faintly comical situation in whicheveryoneis saying that no one is talking about consciousness. For our part, therefore, we shall seek to escape the convention by inverting it: here are yet more papers about consciousness.

That the rationality of individual people is ‘bounded’ – that is, finite in scope and representational reach, and constrained by the opportunity cost of time – cannot reasonably be controversial as an empirical matter. In this context, the paper addresses the question as to why, if economics is an empirical science, economists introduce bounds on the rationality of agents in their models only grudgingly and partially. The answer defended in the paper is that most economists are interested primarily in markets and only secondarily in the dynamics of individual decisions – specifically, they are interested in these dynamics mainly insofar as they might systematically influence the most useful approaches to modeling interesting markets. In market contexts, bounds on rationality are typically generated by institutional and informational properties specific to the market in question, which arise and are sustained by structural dynamics that do not originate in or reduce to individuals' decisions or psychologic..

Ontic structural realism (OSR) is crucially motivated by empirical discoveries of fundamental physics. To this extent its potential to furnish a general metaphysics for science may appear limited. However, OSR also provides a good account of the progress that has been achieved over the decades in a formalized special science, economics. Furthermore, this has a basis in the ontology presupposed by economic theory, and is not just an artifact of formalization. †To contact the author, please write to: 4th Floor, Humanities Building, University of Alabama at Birmingham, 900 13th Street South, Birmingham, AL 35294‐1260; School of Economics, Leslie Social Science Building, University of Cape Town, Private Bag, Rondebosch 7701, Cape Town, South Africa; e‐mail: [email protected].

It is widely appreciated that establishment and maintenance of coordination are among the key evolutionary promoters and stabilizers of human language. In consequence, it is also generally recognized that game theory is an important tool for studying these phenomena. However, the best known game theoretic applications to date tend to assimilate linguistic communication with signaling. The individualistic philosophical bias in Western social ontology makes signaling seem more challenging than it really is, and thus focuses attention on theoretical problems – for example, coordination on lexical meaning – that actual evolution did not need to solve by improving humans’ strategic or social intelligence relative to the endowments of other primates. At the same time, issues of genuine evolutionary significance related to language, especially those around the tensions between individual and collective agency, and around intergenerational accumulation of knowledge, are obscured. This in turn leads to underestimation of the potential contribution that game theory can make to enlightening models of the evolution of human language. JEL classification: A11, A12, B52, C73, D02, D03, D82, Z13

It is widely appreciated that establishment and maintenance of coordination are among the key evolutionary promoters and stabilizers of human language. In consequence, it is also generally recognized that game theory is an important tool for studying these phenomena. However, the best known game theoretic applications to date tend to assimilate linguistic communication with signaling. The individualistic philosophical bias in Western social ontology makes signaling seem more challenging than it really is, and thus focuses attention on theoretical problems - for example, coordination on lexical meaning - that actual evolution did not need to solve by improving humans' strategic or social intelligence relative to the endowments of other primates. At the same time, issues of genuine evolutionary significance related to language, especially those around the tensions between individual and collective agency, and around intergenerational accumulation of knowledge, are obscured. This in turn leads to underestimation of the potential contribution that game theory can make to enlightening models of the evolution of human language. JEL classification: A11, A12, B52, C73, D02, D03, D82, Z13

We discuss Russell's 1913 essay arguing for the irrelevance of the idea of causation to science and its elimination from metaphysics as a precursor to contemporary philosophical naturalism. We show how Russell's application raises issues now receiving much attention in debates about the adequacy of such naturalism, in particular, problems related to the relationship between folk and scientific conceptual influences on metaphysics, and to the unification of a scientifically inspired worldview. In showing how to recover an approximation to Russell's conclusion while explaining scientists' continuing appeal to causal ideas (without violating naturalism by philosophically correcting scientists) we illustrate a general naturalist strategy for handling problems around the unification of sciences that assume different levels of naïveté with respect to folk conceptual frameworks. We do this despite rejecting one of the premises of Russell's argument, a version of reductionism that was scientifically plausible in 1913 but is not so now.

This paper is motivated by the concern that increasingly fewer philosophers of mind seem prepared to call themselves ‘functionalists’ these days. I suggest that this has less to do with explicit arguments presented against functionalism than with a gradual decay in the clarity of the term’s reference. This decay has two sources: functionalism has involved several different, logically independent research commitments, and it has become tightly associated, to an unnecessary degree, with classical computationalism, a program which is now under severe pressure from connectionist and other bottom-up methodologies in Al. After diagnosing the causes of this drift, I seek to arrest it by sketching a version of functionalism---Minimal Strong Functionalism---that is strong enough to have ontological and methodological bite, but that is sufficiently minimal in its empirical commitments so as to not be hostage to the outcome of the current dispute in Al between connectionists and classicists

Invited to give the 2000 Rick Turner Memorial Lecture, I pondered the following question: What explains the fact that the sincere thought of a brilliant and heroic person such as Turner can appear preposterous to me, if bad faith or scholarly ignorance on one side or the other are ruled out, as they should be in this case? I address this question by considering what ‘ideologies' are from the perspective of cognitive learning theory. I describe the dynamics by which pressures for social coordination cause brains to implement alternative natural softwares for performing inferences in complex domains of association and inference. I conclude by noting that this need not imply normative relativism, since the relative justifications for conclusions produced by different softwares can still be debated. My aim is thus not to contest Turner's ideology or political views, but to partially explain how learning produces differences that transcend factual disagreements and even ethical ones. S. Afr. J. Philos. Vol.22(2) 2003: 139–156

It is crucial, first of all, to stress the importance Churchland attaches to the idea that the neural networks whose assemblages he holds to be “engines of reason” must be recurrent. Non-recurrent networks, of the sort best known among philosophers, simply discover patterns in input data presented to them as sets of features. The learning capacities of such networks, extensively discussed since the publication of Rumelhart and McClelland et al., are indeed impressive; and Churchland describes them clearly and gracefully as preparation for introducing recurrent networks. Now, the importance of recurrence as a feature of the networks Churchland hypothesizes as forming the basis of cognitive activity is well motivated. A cognitive system that was an assembly of non-recurrent networks would be, in essence, a stimulus-response machine of the sort that early behaviourists took themselves to be studying when they examined the mind/brain. Such a system could learn to find novel patterns in data. However, it is empirically evident that human— and some non-human—cognitive capacities go well beyond this. People dream, imagine scenarios that never existed, reconceptualize their perceptions, and theorize. All these activities seem to require not merely inferring patterns from data, but reconceiving the nature of the data itself in light of the inferential structures built through learning. For this to be possible, the data cannot be “clamped,” as they are in the case of non-recurrent networks. Hence the importance of recurrence. A recurrent network can be defined as one which takes some or all of its own output and then treats that output as a source of input. This allows for the recognition of meta-patterns. Furthermore, if some such networks are feeding their output as input to other networks with which they are linked, the possibility of reasoning and conceptualizing by analogy arises; and this ability, as Churchland argues, seems to be an essential aspect of genuine creativity in science, art, and the continuously ongoing re-design of the social order. The actual existence of simulated recurrent networks, and the capacities they demonstrate, constitute an impressive possibility argument that a system with enormous cognitive plasticity and behavioural flexibility could be built out of parallel distributed processing networks, so long as at least many of these networks were recurrent. The importance of this possibility argument should not be under-emphasized, but it of course invites an obvious question: how good are our grounds for supposing that the possibility in question is actually realized in the biological domain?

An article by Alexandra Kirsch accepted for publication in Cognitive Processing occasioned debate among reviewers about broad methodological issues in cognitive science. One of these issues is the proper place of Popperian falsificationism in the interdisciplinary cluster. Another is the tension between abstract models and theories that apply to wide classes of cognitive systems, and models of more restricted scope intended to predict specifically human patterns of thought and behavior. The lead editorial in a Commentary debate invited by the journal’s editors considers these issues from the perspective of a pragmatist philosophy of science inspired by Herbert Simon’s classic, MIT Press, Cambridge, 1969) reflections on the blurring of the distinction between science and engineering in cognitive science.

Pathological gambling (PG) is a kind of ‘ideal puzzle’ for the economic model of the consumer. The pathological gambler takes pains to engage in activity that transparently has negative expected returns if utility varies positively with money. She also, typically, spends further resources on commitment devices designed to interfere with her gambling. These properties together describe an agent that is a kind of perfect foil for the rationally maximizing consumer. Recently, aspects of the neuropathology underlying the strange economic agency of the pathological gambler are becoming understood. Thus PG is an ideal test bed phenomenon for working out relationships between economic modeling based on constrained optimization of utility and the new neuroscience of behavior.

The rise of behavioral economics since the 1980s led to richer mutual influence between economic and psychological theory and experimentation. However, as behavioral economics has become increasingly integrated into the main stream in economics, and as psychology has remained damagingly methodologically conservative, this convergence has recently gone into reverse. At the same time, growing appreciation among economists of the limitations of atomistic individualism, along with advantages in econometric modeling flexibility by comparison with psychometrics, is leading economists to become more pluralistic than psychologists about the ontology of behavioral causation and structures. This, combined with economists’ growing interest in network models, is drawing economists closer in theory and practice to sociologists who use quantitative or mixed methods.

In this article, I critically respond to Herbert Gintis's criticisms of the behavioral-economic foundations of Ken Binmore 's game-theoretic theory of justice. Gintis, I argue, fails to take full account of the normative requirements Binmore sets for his account, and also ignores what I call the ‘scale-relativity’ considerations built into Binmore 's approach to modeling human evolution. Paul Seabright's criticism of Binmore, I note, repeats these oversights. In the course of answering Gintis's and Seabright's objections, I clarify and extend Binmore 's theory in a number of respects, integrating it with Kim Sterelny's and Don Ross's recent work on the evolution of people as cultural entities. The account also yields a novel basis for choosing between socialism and what Binmore calls ‘whiggery’ as normative political programs. Key Words: theory of justice • bargaining theory • evolutionary game theory • human evolution • Ken Binmore • Herbert Gintis • Kim Sterelny

I discuss implications of Tomasello et al's hypothesis that humans exhibit distinctive collective intentionality for game-theoretic approaches to modeling human evolution. Representing the hypothesis game-theoretically forces a question about whether it implies only distinctively human motivations or both distinctive motivations and distinctive cognitive capacities for representation of intentions. I also note that the hypothesis explains uniquely human ideological conflict and invites game-theoretic modeling of this.