The Abstraction/Representation Account of Computation and Subjective Experience (original) (raw)
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Towards a computational theory of experience
A standing challenge for the science of mind is to account for the datum that every mind faces in the most immediate -that is, unmediated -fashion: its phenomenal experience. The complementary tasks of explaining what it means for a system to give rise to experience and what constitutes the content of experience (qualia) in computational terms are particularly challenging, given the multiple realizability of computation. In this paper, we identify a set of conditions that a computational theory must satisfy for it to constitute not just a sufficient but a necessary, and therefore naturalistic and intrinsic, explanation of qualia. We show that a common assumption behind many neurocomputational theories of the mind, according to which mind states can be formalized solely in terms of instantaneous vectors of activities of representational units such as neurons, does not meet the requisite conditions, in part because it relies on inactive units to shape presently experienced qualia and implies a homogeneous representation space, which is devoid of intrinsic structure. We then sketch a naturalistic computational theory of qualia, which posits that experience is realized by dynamical activity-space trajectories (rather than points) and that its richness is measured by the representational capacity of the trajectory space in which it unfolds.
How minds can be computational systems
Journal of Experimental & Theoretical Artificial Intelligence, 1998
This essay explores the implications of the thesis that implementation is semantic interpretation. Implementation is (at least) a ternary relation: I is an implementation of an "Abstraction" A in some medium M. Examples are presented from the arts, from language, from computer science, and from cognitive science, where both brains and computers can be understood as implementing a "mind Abstraction". Implementations have side effects due to the implementing medium; these can account for several puzzles surrounding qualia. Finally, a benign argument for panpsychism is developed.
Representation and Reality in Humans, Other Living Organisms and Intelligent Machines
Studies in Applied Philosophy, Epistemology and Rational Ethics, 2017
This book project is based on several years of collaboration between two editors, starting with the organization of the symposium Computing Nature at the AISB/IACAP World Congress in 2012 in Birmingham. It continued with the AISB50 Convention at Goldsmiths, London in 2014 and the symposium Representation: Humans, Animals and Machines organized in cooperation with Veronica Arriola-Rios, University of Birmingham. During preparation, the book project was presented at the symposium Representation and Reality at UNILOG 2015, World Congress on Universal Logic in Istanbul. All those events, as well as our networks with research communities of cognitive scientists, computer scientists, philosophers, logicians, AI researchers, roboticists and natural scientists, connect us with the authors of the present volume, offering views on the topic of representation and its connections to reality in humans, other living organisms and machines. The choice of the title was made so as to refer to historical attempts at making connections, with Wiener's "Cybernetics: Or Control and Communication in the Animal and the Machine" (Wiener 1948), and Putnam's human-centric "Representation and Reality" (Putnam 1988). How to address this vast topic and connect representation and reality in humans, other living beings and machines, based on the best contemporary knowledge? We invited prominent researchers with different perspectives and deep insights into the various facets of the relationship between reality and representation in those three classes of agents. How can we find a common link between reality-constructing agents like us humans with language ability and social structures that define our agency, other living organisms, from bacteria to plants and animals communicating and processing information in a variety of ways, with machines, physical and virtual? We have taken a cognitive, computational, natural sciences, philosophical, logical and machine perspective. Of course, no perspective is simple and pure, but rather a fractal structure in which recurrent mirroring of other perspectives at different scales and in different senses occurs. So in a contribution characterized predominantly as "cognitive perspective" there are elements of natural sciences, logic, philosophy and so on. Our aim is to provide a multifaceted view of the topic of representation and reality in the range of approaches from disciplinary v vi Preface x Preface
Representation and mental representation
Philosophical Explorations, 2018
This paper engages critically with anti-representationalist arguments pressed by prominent enactivists and their allies. The arguments in question are meant to show that the “as-such” and “job-description” problems constitute insurmountable challenges to causal-informational theories of mental content. In response to these challenges, a positive account of what makes a physical or computational structure a mental representation is proposed; the positive account is inspired partly by Dretske’s views about content and partly by the role of mental representations in contemporary cognitive scientific modeling.
Explaining Computation Without Semantics: Keeping it Simple
Minds and Machines, 2010
This paper deals with the question: how is computation best individuated? The semantic view of computation: computation is best individuated by its semantic properties. The causal view of computation: computation is best individuated by its causal properties. The functional view of computation: computation is best individuated by its functional properties. Some scientific theories explain the capacities of brains by appealing to computations that they supposedly perform. The reason for that is usually that computation is individuated semantically. I criticize the reasons in support of this view and its presupposition of representation and semantics. Furthermore, I argue that the only justified appeal to a representational individuation of computation might be that it is partly individuated by implicit intrinsic representations.
The purpose of this article is to offer a new view of the key relation between the content and the conscious character of visual experience. The author aims to support the following claims. First, the author rejects the qualia realist claim that conscious character is an intrinsic, nonrepresentational property of visual experience, for example, a pattern of activation of neurons. However, the author also rejects the rival widespread representationalist claim that the conscious character of visual experience is identical to, or supervenes on, any specific property represented by visual experience. The positive proposal is the following. Conscious character is identical with those patterns of activation of neurons that are referentially or representationally alive. Conscious redness , for example, is a pattern of activations of neurons that is created normally only when brains of physical duplicates come in visual contact with some distal property and this pattern of activation is recruited by natural selection to represent that property. This is called meaning representationalism. Keywords qualia realism – representationalism – meaning representationalism – conscious character – singular content
A vehicular theory of corporeal qualia (a gift to computationalists)
Philosophical Studies, 2011
The idea that certain aspects of human cognition involve the construction and utilization of non-sentential representations akin to pictures and scale models has been with us at least since Aristotle's De Anima (4 th-century B.C./1987). Among the most vocal latter-day critics of this idea are those, like Pylyshyn (1981, 1984, 2002, 2003), who favor an across-the-board computational theory of cognition, where 'computation' should hereafter be understood in what might be termed the strict sense that involves the application of syntax-sensitive rules to sentential data structures (e.g., as opposed to a looser sense of the term that allows for transformations to other kinds of information-bearing vehicles). As these critics know all-too well, computational theories of cognition automatically enjoy the status of being neurally realizable, at least for all practical purposes. One way of showing this is to note that a device that approximates a universal Turing machine can be constructed out of neuron-like processors that interact purely on the basis of biologically plausible operating principles. 1 In fact, McCulloch and Pitt's early work in this regard inspired von Neumann to show that this same sort of device can be created out of electronic components (e.g., vacuum tubes) (Boden 2006, 196). This latter achievement yielded a platform on which many high-level cognitive models and architectures would be constructed, which clearly accelerated the ascent of the computational theory cognition. Clearly it would do much to bolster the credibility of the theory that brains sometimes realize nonsentential images and models if it could be shown that we have equally good reason to believe that brains are capable, at least in principle, of realizing representations of this sort. For this reason, I have taken great pains to demonstrate that certain computer scientists and engineers have, by creating what are known as finite element models, inadvertently shown precisely this (Waskan 2003, 2006, 2008). What their work shows, in particular, is that because non-sentential images and models can be realized by (strict) computations, they too can-if not directly, then at least indirectly via computations-also be realized by neural machinations. I am realistic enough to know that many of those who favor an across-the-board computational theory of cognition, especially the philosophers among them, will reject these proposals, so what I will try to show here is that by accepting them they actually stand to gain a great deal. My efforts will be directed towards showing how the proposal that some computers realize non-sentential images and models can resolve one major facet of the 11 There are, of course, also important differences between InCoMs and scale models (Waskan 2005). 12 http://globetrotter.berkeley.edu/people/Searle/searle-con4.html (last accessed 9/25/08). 13 Searle bristles at this terminology, but I feel that it is perfectly apt in light of the foregoing exposition. 14 To overcome the limitations imposed by human memory and, worse still, by the fairly rigid constraints governing perception and thought, this project will surely require the construction of vast computational models of neural systems (see Waskan 2006, chapter 9). Admittedly, to the extent that these models do explain qualia, it will sometimes (viz., as concerns creatures with radically different perceptual organs) be akin to the way in which computational models of black holes or the big bang explain these occurrences. Apart from inspiring a wealth of useful metaphors, in the end they may not provide us with the exact kinds of insight and understanding that Mary and Nagel seek. Still, unlike their topic-neutral predecessors, these models and metaphors would, in their own way,
Situatedness and Embodiment of Computational Systems
In this paper, the role of the environment and physical embodiment of computational systems for explanatory purposes will be analyzed. In particular, the focus will be on cognitive computational systems, understood in terms of mechanisms that manipulate semantic information. It will be argued that the role of the environment has long been appreciated, in particular in the work of Herbert A. Simon, which has inspired the mechanistic view on explanation. From Simon's perspective, the embodied view on cognition seems natural but it is nowhere near as critical as its proponents suggest. The only point of difference between Simon and embodied cognition is the significance of body-based off-line cognition; however, it will be argued that it is notoriously over-appreciated in the current debate. The new mechanistic view on explanation suggests that even if it is critical to situate a mechanism in its environment and study its physical composition, or realization, it is also stressed that not all detail counts, and that some bodily features of cognitive systems should be left out from explanations.
The Representational View: Experiencing as Representing (chap. from *Perception*)
This is a chapter from my introductory book *Perception* covering the representational view of experience. I use the Ramsey-Lewis method to define the theoretical term "experiential representation". I clarify and discuss various questions for representationalists, for instance, "how rich is the content of experience?" and "is the content of visual experience singular or general?" Finally, I address some objections to representationalism - in particular, that it cannot explain perceptual presence (John Campbell), and that it cannot explain the "laws of appearance" (constraints on how things can appear). WEBSITE: https://sites.google.com/view/adampautz/home