Joel Walmsley

Explanation in Dynamical Cognitive Science

In this paper, I outline two strands of evidence for the conclusion that the dynamical approach to cognitive science both seeks and provides covering law explanations. Two of the most successful dynamical models—Kelso’s model of rhythmic finger movement and Thelen et al.’s model of infant perseverative reaching—can be seen to provide explanations which conform to the famous explanatory scheme first put forward by Hempel and Oppenheim. In addition, many prominent advocates of the dynamical approach also express the provision of this kind of explanation as a goal of dynamical cognitive science. I conclude by briefly outlining two consequences. First, dynamical cognitive science’s explanatory style may strengthen its links to the so-called “situated” approach to cognition, but, secondly, it may also undermine the widespread intuition that dynamics is related to emergentism in the philosophy of mind.

Methodological situatedness; or, DEEDS worth doing and pursuing

This paper draws a distinction between two possible understandings of the DEEDS (Dynamical, Embodied, Extended, Distributed and Situated) approach to cognition. On the one hand, the DEEDS approach may be interpreted as making a metaphysical claim about the nature and location of cognitive processes. On the other hand, the DEEDS approach may be read as providing a methodological prescription about how we ought to conduct cognitive scientific research. I argue that the latter, methodological, reading shows that the DEEDS approach is pursuitworthy independently of an assessment of the truth of the metaphysical claim. Understood in this way, the DEEDS approach may avoid some of the objections that have been levelled against it.

The Emergence of Borders: Moral Questions Mapped Out

In this paper, we examine the extent to which the concept of emergence can be applied to questions about the nature and moral justification of territorial borders. Although the term is used with many different senses in philosophy, the concept of “weak emergence”-advocated by, for example, Sawyer (2002, 2005) and Bedau (1997)-is especially applicable, since it forces a distinction between prediction and explanation that connects with several issues in the dis-cussion of territory. In particular, we argue, weak emergentism about borders allows us to distinguish between (a) using a theory of territory to say where a border should be drawn, and (b) looking at an existing border and saying whether or not it is justified (Miller, 2012; Nine, 2012; Stilz, 2011). Many authors conflate these two factors, or identify them by claiming that having one without the other is in some sense incoherent. But on our account-given the concept of emergence-one might unproblematically be able to have (b) without (a); at the very least, the distinction between these two issues is much more significant than has often been recognised, and more importantly gives us some reason to prefer “statist” as opposed to “cultural” theories of territorial borders. We conclude with some further reflections on related matters concerning, firstly, the apparent causal powers of borders, and secondly, the different ways in which borders are physically implemented (e.g., land vs. water).

Historical and Theoretical Background

Intellectual history is bursting at the seams with the precursors of what we now know as AI; the myths, legends and speculative stories about automata, androids, robots are too numerous to list, but prevalent enough to have become well entrenched in the popular imagination. In some ways, this is hardly surprising; an essentially human desire to understand ourselves, coupled with a Promethean predilection for playing with fire, sure enough leads to the two intertwined questions with which this book is concerned, and to which I will repeatedly return: Could a machine think? Are we such thinking machines?

Classical Cognitive Science and “Good Old Fashioned AI”

The last chapter discussed some of the historical and theoretical background that led to AI’s appearance on the intellectual landscape in the 1950s and 1960s. Its emergence was more-or-less concurrent with the birth of the interdisciplinary enterprise we now know as cognitive science, and this chapter examines what may usefully be regarded as the first major paradigm for cognitive science in general and AI in particular: the idea that cognition is what computers do — rule-governed symbol manipulation.

Criticisms and Consequences of the Connectionist Approach

In this chapter, I want to examine two famous discussions of philosophical consequences of the connectionist approach. Naturally, these two discussions are but a small selection of the responses and criticisms that in fact have been made to the development of connectionism. But I have selected these two discussions in particular because they touch on themes that have already been — and will continue to be — important to the particular account being presented in this book. They concern connectionism’s implications for the mind-body problem, and the relationship between connectionism and GOFAI (with the latter also setting the stage for a subsequent discussion of connectionism’s relationship to the dynamical systems approach to cognitive science and AI).

Gödel, the Turing Test and the Chinese Room

In the previous chapter, we examined some of the origins, motivations, exemplars, and implications of GOFAI. These shone a mostly positive (although qualified) light on the approach; naturally, we now want to turn to a handful of the prominent criticisms. In any age, as the above passage from Hamlet reminds us, we humans think that certain of our features make us somehow ‘special’. Descartes, as we saw, focussed on language use. Hamlet mentions reason. Whatever it is that one thinks distinguishes us (or makes us the “paragon of the animals”), one could construct an argument against AI if one could show that machines must lack that feature. This chapter focuses on three related discussions — sometimes misunderstood — that adopt just this rhetorical strategy. In fact only two of them (the Godel argument and Searle’s “Chinese Room”) are explicit criticisms with the conclusion that GOFAI is impossible, but the third (the “Turing Test”) does provide an arena in which a variety of anti-AI arguments (like that of Descartes) often get articulated.

The Dynamical Approach

Imagine it’s the late eighteenth century — during the industrial revolution — and you’re a cotton-mill owner in the north of England who has just acquired a new-fangled rotative steam engine to replace the horses and water-wheels driving your loom. In order to continue producing smooth woven cotton, you need a power source that is highly uniform; the engine’s flywheel must rotate at a constant, unvarying speed. But steam engine output can fluctuate quite widely depending on the pressure of the steam and the load under which it is placed. So you need some device — a widget or machine known as a governor — that can regulate the flywheel speed, despite variations in steam pressure and workload.

The Future: Mind and Machine Merged

I start with this quotation, because in this Chapter I intend to turn back and examine one of our initial questions from a slightly different angle. In addition to the question of the possibility of thinking machines, we have also had at the back of our minds the question of whether we are such machines. In this chapter, I want to consider some ideas in cognitive science and AI that either dispute the legitimacy of the mind-machine distinction, or else blur the boundary between mind and world (or between ‘psychical’ and ‘fleshly’ impulses). The topics I shall discuss are all regarded as ‘speculative’ (as is appropriate for a Chapter concerned with the future of a discipline). The extent to which this tag is intended as derogatory is not clear — I leave it to the reader to adopt their own view on this matter — but I shall treat the topics in ascending order of ‘speculativity’.