Computer Modeling and the Fate of Folk Psychology

Although Paul Churchland and Jerry Fodor both subscribe to the so-called theory-theory – the theory that folk psychology (FP) is an empirical theory of behavior – they disagree strongly about FP's fate. Churchland contends that FP is a fundamentally flawed view analogous to folk biology, and he argues that recent advances in computational neuroscience and connectionist AI point toward development of a scientifically respectable replacement theory that will give rise to a new common-sense psychology. Fodor, however, wagers that FP will be largely preserved and vindicated by scientific investigations of behavior. Recent findings by developmental psychologists, I argue, will push both Churchlandians and Fodorians toward the pessimistic view that FP is a misguided theory that will never be displaced, because it is, so to speak, built into our cognitive systems. I explore the possibility of preserving optimism by rejecting the theory-theory and adopting the simulation theory , a competing view developed by Robert Gordon, Alvin Goldman, and Jane Heal. According to simulationists, common-sense interpretation of behavior is accomplished by means of pretense-like operations that deploy the cognitive system's own reasoning capabilities in a disengaged manner. Since on this view no theory-like set of principles would be needed, the simulation theory seems to enjoy a simplicity advantage over the theory-theory. Steven Stich and Shawn Nichols, however, contend that as the cognitive system would require special mechanisms for disengaged operation, the simplicity question cannot be resolved until suitable computational models are developed. I describe a set of models I have constructed to meet this need, and I discuss the contribution such models can make to determining FP's fate.     

Layers of Models in Computer Simulations

I discuss here the definition of computer simulations, and more specifically the views of Humphreys, who considers that an object is simulated when a computer provides a solution to a computational model, which in turn represents the object of interest. I argue that Humphreys's concepts are not able to analyse fully successfully a case of contemporary simulation in physics, which is more complex than the examples considered so far in the philosophical literature. I therefore modify Humphreys's definition of simulation. I allow for several successive layers of computational models, and I discuss the relations that exist between these models, the computer, and the object under study. An aim of my proposal is to clarify the distinction between computational models and numerical methods, and to better understand the representational and the computational functions of models in simulations.     

Affectively Driven Perception: Toward a Non-representational Phenomenology

While classical phenomenology, as represented by Edmund Husserl’s work, resists certain forms of representationalism about perception, I argue that in its theory of horizons, it posits representations in the sense of content-bearing vehicles. As part of a phenomenological theory, this means that on the Husserlian view such representations are part of the phenomenal character of perceptual experience. I believe that, although the intuitions supporting this idea are correct, it is a mistake to maintain that there are such representations defining the phenomenal character of low-level perception. What these representations are called on to explain, i.e., the phenomenal character of perceiving objects in their full presence, can be more parsimoniously explained by appealing to certain affective states or affect schemas that shape the intentional directedness of low-level perceptual experience and define its phenomenal character in a non-representational way. This revision of the Husserlian view, it is shown, also helps us understand the normative character of perception.     

Toward the Language-Ready Brain: Biological Evolution and Primate Comparisons

The approach to language evolution suggested here focuses on three questions: How did the human brain evolve so that humans can develop, use, and acquire languages? How can the evolutionary quest be informed by studying brain, behavior, and social interaction in monkeys, apes, and humans? How can computational modeling advance these studies? I hypothesize that the brain is language ready in that the earliest humans had protolanguages but not languages (i.e., communication systems endowed with rich and open-ended lexicons and grammars supporting a compositional semantics), and that it took cultural evolution to yield societies (a cultural constructed niche) in which language-ready brains could become language-using brains. The mirror system hypothesis is a well-developed example of this approach, but I offer it here not as a closed theory but as an evolving framework for the development and analysis of conflicting subhypotheses in the hope of their eventual integration. I also stress that computational modeling helps us understand the evolving role of mirror neurons, not in and of themselves, but only in their interaction with systems “beyond the mirror.” Because a theory of evolution needs a clear characterization of what it is that evolved, I also outline ideas for research in neurolinguistics to complement studies of the evolution of the language-ready brain. A clear challenge is to go beyond models of speech comprehension to include sign language and models of production, and to link language to visuomotor interaction with the physical and social world.     

THE INADEQUACY OF ROLE MODELS FOR EDUCATING MEDICAL STUDENTS IN ETHICS WITH SOME REFLECTIONS ON VIRTUE THEORY

Persons concerned with medical education sometimes argued that medical students need no formal education in ethics. They contended that if admissions were restricted to persons of good character and those students were exposed to good role models, the ethics of medicine would take care of itself. However, no one seems to give much philosophic attention to the ideas of model or role model. In this essay, I undertake such an analysis and add an analysis of role. I show the weakness in relying on role models exclusively and draw implications from these for appeals to virtue theory. Furthermore, I indicate some of the problems about how virtue theory is invoked as the ethical theory that would most closely be associated to the role model rhetoric and consider some of the problems with virtue theory. Although Socrates was interested in the character of the (young) persons with whom he spoke, Socratic education is much more than what role modeling and virtue theory endorse. It -- that is, philosophy -- is invaluable for ethics education.     

Modal-Epistemic Arithmetic and the problem of quantifying in

The subject of this article is Modal-Epistemic Arithmetic (MEA), a theory introduced by Horsten to interpret Epistemic Arithmetic (EA), which in turn was introduced by Shapiro to interpret Heyting Arithmetic. I will show how to interpret MEA in EA such that one can prove that the interpretation of EA is MEA is faithful. Moreover, I will show that one can get rid of a particular Platonist assumption. Then I will discuss models for MEA in light of the problems of logical omniscience and logical competence. Awareness models, impossible worlds models and syntactical models have been introduced to deal with the first problem. Certain conditions on the accessibility relations are needed to deal with the second problem. I go on to argue that those models are subject to the problem of quantifying in, for which I will provide a solution.     

Conceptual Structure and the Emergence of the Language Faculty: Much Ado about Knotting

Abstract

One perspective in contemporary linguistic theory defends the idea that the language faculty may result from the combinations of diverse systems and principles. As a case study, I critique a recent proposal by Juan Uriagereka and colleagues according to which the evolutionary emergence of the language faculty can be identified through studying the computational structure of knots as present within the fossil record. I here argue that the ability to conceptualize and, thereby, create knots is not parasitic on the ability to conceptualize and create language. On the contrary, these two domains are entirely distinct, unrelatable in terms of their computational complexity, expressive power or, most importantly, in terms of their requisite mental operations and principles. The overall approach defended here can profitably be employed in the study of the relationship between language and thought, as I briefly discuss in the case of the role of language in spatial reorientation.     

Implicit attitudes and the social capacity for free will

In this paper I ask what implicit attitudes tell us about our freedom. I analyze the relation between the literature on implicit attitudes and an important subcategory of theories of free will—self-disclosure accounts. If one is committed to such a theory, I suggest one may have to move to a more social conceptualization of the capacity for freedom. I will work out this argument in five sections. In the first section, I discuss the specific theories of free will that are central to this paper. In the second section, I will show that implicit-bias research raises questions about people’s capacities to exercise (these specific understandings of) free will. In the third section, I will consider how an individual may overcome these failures and argue that the individual ability for self-regulation is significantly limited. One could stop here and conclude that free will is a limited capacity. But I argue that this conclusion would be too hastily drawn. I will instead continue to ask what would be required for free will. By discussing how failures of free will are due to social structures and may be therefore repaired by changing social structures in section 4, I will arrive at an alternative conclusion about the capacity for free will in section 5.     

CONSUETUDO CARNALIS IN AUGUSTINE'S CONFESSIONS: Confessing Identity/Belonging to Difference

The political theorist William E. Connolly reads Augustine's Confessions as an exhortation to deny the paradox of identity/difference. The paradox for Connolly is this: if one confesses a true identity, one must be false to difference, but if one is true to difference, one must sacrifice the promise of true identity. I revisit Augustine's Confessions here in order to offer a reading of their paradoxical character that contrasts with Connolly's. I will argue that Augustine's confession does not deny the paradox of identity/difference but exemplifies what it means to struggle within it. I turn to James Wetzel's work on Augustine's idea of free will and Catherine Keller's work on the doctrine of creatio ex nihilo to suggest that treating Augustine's confession as confession reveals this struggle.     

Universal moral grammar: theory, evidence and the future

Scientists from various disciplines have begun to focus attention on the psychology and biology of human morality. One research program that has recently gained attention is universal moral grammar (UMG). UMG seeks to describe the nature and origin of moral knowledge by using concepts and models similar to those used in Chomsky's program in linguistics. This approach is thought to provide a fruitful perspective from which to investigate moral competence from computational, ontogenetic, behavioral, physiological and phylogenetic perspectives. In this article, I outline a framework for UMG and describe some of the evidence that supports it. I also propose a novel computational analysis of moral intuitions and argue that future research on this topic should draw more directly on legal theory.     

Parallelism and Functionalism

It has recently been argued by Paul Thagard (1986) that parallel computational models of cognition demonstrate the falsity of the popular theory of mind known as functionalism. It is my contention that his argument is seriously mistaken and rests on a misunderstanding of the functionalist position. While my primary aim is to defend functionalism from Thagard's attack, in the process I hope to provide some much needed clarification of matters both philosophical and computational. Since I intend to untangle issues that are often troublesome in cognitive science, the paper should prove useful even for those unfamiliar with Thagard's original piece.     

Are Lovers Ever One? Reconstructing the Union Theory of Love

Current analytical philosophies of romantic love tend to identify the essence of such love with one specific element, such as concern for the beloved person, valuing the beloved person or the union between the lovers. This paper will deal with different forms of the union theory of love which takes love to be the physical, psychic or ontological union of two persons. Prima facie, this theory might appear to be implausible because it has several contra-intuitive implications, and yet, I submit, it is more coherent and attractive than it seems to be. I shall distinguish three specific models and thereby offer a differentiated account of the union theory which has not previously been provided in the literature (1). I will claim that two of these models (the strong ontological model and the striving model) should be rejected (2). I shall then defend the third model (the moderate ontological model) against certain possible objections (3); but nevertheless, I shall conclude by showing how this model, too, faces further significant objections which ultimately expose the limits of the union theory of love (4). In conclusion, I will sketch the outlines of a non-reductive cluster theory of love.     

Representations and Cognitive Explanations: Assessing the Dynamicist's Challenge in Cognitive Science

Advocates of dynamical systems theory (DST) sometimes employ revolutionary rhetoric. In an attempt to clarify how DST models differ from others in cognitive science, I focus on two issues raised by DST: the role for representations in mental models and the conception of explanation invoked. Two features of representations are their role in standing-in for features external to the system and their format. DST advocates sometimes claim to have repudiated the need for stand-ins in DST models, but I argue that they are mistaken. Nonetheless, DST does offer new ideas as to the format of representations employed in cognitive systems. With respect to explanation, I argue that some DST models are better seen as conforming to the covering-law conception of explanation than to the mechanistic conception of explanation implicit in most cognitive science research. But even here, I argue, DST models are a valuable complement to more mechanistic cognitive explanations.     

Projectible predicates in analogue and simulated systems

We investigate the relationship between two approaches to modeling physical systems. On the first approach, simplifying assumptions are made about the level of detail we choose to represent in a computational simulation with an eye toward tractability. On the second approach simpler, analogue physical systems are considered that have more or less well-defined connections to systems of interest that are themselves too difficult to probe experimentally. Our interest here is in the connections between the artifacts of modeling that appear in these two approaches. We begin by outlining an important respect in which the two are essentially dissimilar and then propose a method whereby overcoming that dissimilarity by hand results in usefully analogous behavior. We claim that progress can be made if we think of artifacts as clues to the projectible predicates proper to the models themselves. Our degree of control over the connection between interesting analogue physical systems and their targets arises from determining the projectible predicates in the analogue system through a combination of theory and experiment. To obtain a similar degree of control over the connection between large-scale, distributed simulations of complex systems and their targets we must similarly determine the projectible predicates of the simulations themselves. In general theory will be too intractable to be of use, and so we advocate an experimental program for determining these predicates.

the object of the natural history which I propose is...to give light to the discovery of causes and supply a suckling philosophy with its first food. Francis Bacon, The Great Instauration

     

Connectionist Models of Word Reading

Abstract— Connectionist models of word reading attempt to explain the computational mechanisms underlying this important skill. The goal of this research is an integrated theory of reading and its brain bases, with the computational model as the interface between the two. The models are governed by computational principles that differ considerably from naive intuitions but nonetheless account for many aspects of normal and impaired (dyslexic) reading.     

Computational enactivism under the free energy principle

In this paper, I argue that enactivism and computationalism—two seemingly incompatible research traditions in modern cognitive science—can be fruitfully reconciled under the framework of the free energy principle (FEP). FEP holds that cognitive systems encode generative models of their niches and cognition can be understood in terms of minimizing the free energy of these models. There are two philosophical interpretations of this picture. A computationalist will argue that as FEP claims that Bayesian inference underpins both perception and action, it entails a concept of cognition as a computational process. An enactivist, on the other hand, will point out that FEP explains cognitive systems as constantly self-organizing to non-equilibrium steady-state. My claim is that these two interpretations are both true at the same time and that they enlighten each other.

     

Theoretical status of computational cognitive modeling

This article explores the view that computational models of cognition may constitute valid theories of cognition, often in the full sense of the term “theory”. In this discussion, this article examines various (existent or possible) positions on this issue and argues in favor of the view above. It also connects this issue with a number of other relevant issues, such as the general relationship between theory and data, the validation of models, and the practical benefits of computational modeling. All the discussions point to the position that computational cognitive models can be true theories of cognition.     

Refining the Inferential Model of Scientific Understanding

In this article, I use a mental models computational account of representation to illustrate some details of my previously presented inferential model of scientific understanding. The hope is to shed some light on possible mechanisms behind the notion of scientific understanding. I argue that if mental models are a plausible approach to modelling cognition, then understanding can best be seen as the coupling of specific rules. I present our beliefs as ‘ordinary’ conditional rules, and the coupling process as one where the consequent of one ordinary rule (OR) matches and activates the antecedent of the rule to which it is coupled in virtue of the activation of an intermediate ‘inference’ rule. I argue that on this approach knowledge of an explanation is the activation of ORs in a cognitive hierarchy, while understanding is achieved when those activated ORs are also coupled via correct inference rules. I do not directly address issues regarding the plausibility of mental models themselves. This article should therefore be seen as an exercise in refining the inferential model within an already presupposed computational setting, not one of arguing for the psychological adequacy of computational approaches.