Don Ross

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?

It is generally recognized that descriptive and normative individualism are logically independent theses. This paper defends the stronger view that recognition of the falsehood of descriptive individualism is crucial to understanding the evolutionary and developmental basis of normative individualism. The argument given for this is not analytic; rather, it is based on empirical generalizations about the evolution of markets with specialized labor, about the nature of information processing in large markets, and about the socialization of human children.

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.

Recently, philosophers have developed an extensive literature on social ontology that applies methods and concepts from analytic metaphysics. Much of this is entirely abstracted from, and unconcerned with, social science. However, Epstein (2015) argues explicitly that analytic social metaphysics, provided its account of ontological ‘grounding’ is repaired in specific ways, can rescue social science from explanatory impasses into which he thinks it has fallen. This version of analytic social ontology thus directly competes with radically naturalistic alternatives, in a way that helps to clarify what makes some metaphysics genuinely scientific (that is, part of the scientific enterprise and worldview). I consider this competition, marshal considerations against the value to social science of analytic metaphysics, and sketch a contrasting scientific metaphysics for understanding the implications of revisionist social ontology in unified scientific ontology.

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.

People become addicted in different ways, and they respond differently to different interventions. There may nevertheless be a core neural pathology responsible for all distinctively addictive suboptimal behavioral habits. In particular, timing models of reward learning suggest a hypothesis according to which all addiction involves neuroadaptation that attenuates serotonergic inhibition of a mesolimbic dopamine system that has learned that cues for consumption of the addictive target are signals of a high-reward-rate environment

‘Naturalism’ about the ontology of society can most blandly be characterized as the belief that social phenomena are among the class of natural phenomena. Contemporary scholars are apt to regard this thesis as bland because its denial seems quaint at best, if not outright unhinged, after a century and a half of development in the social sciences. There has, however, been a powerful tradition in (at least) Western culture that has understood the ‘artificial’ as a primary contrast class with the ‘natural’, and which has interpreted the social as a creation of human beings that stands over and against the natural realm. Often..

I discuss the role of economics in the study of social cognition. A currently popular view is that microeconomics should collapse into psychology partly because cognitive science has shown that valuation is constitutively social, whereas non-psychological economics insists that it is not. In the paper I resist this view, partly by reference to the relevant history of economic theory, and partly by reference to an alternative model of the way in which that theory complements, without reducing to, psychological accounts of social cognition.

Critics of mainstream economics typically rest important weight on the differences between people and the 'agents' that populate economic theory and economic models. Hollis and Nell (1975) is both representative of and ancestral to many more recent variations on the theme. Lately, the upgraded status of behavioral economics (BE) within the discipline's mainstream has encouraged a number of writers to use revolutionary rhetoric in promotion of a 'paradigm shift' that includes the rejection of 'rational economic man' (Ormerod 1994, Heilbroner and Milburg 1995, Fullbrook 2003). The current leading developers of BE are generally more circumspect, claiming that their approach complements standard theory rather than promising to supplant it (Camerer and Loewenstein 2004, Angner and Loewenstein this volume). However, they generally join the more florid critics in supposing that microeconomics is bound to improve its empirical relevance to the extent that it substitutes the study of people for that of abstract economic agents. Another body of thought that promotes this view stems from Sen's (1977) attack on standard economic agents as 'rational fools', amplified in Davis's (2003) argument that since economic agents lack some essential properties of human individuals, economic theory requires fundamental reform if it is to make progress in explaining human behavior.