In the last few months, several papers of mine have been accepted for publication. Since they all complement each other to form a somewhat cohesive whole, it might be useful for me to list them together with a brief explanation of how they are related to one another. Thanks again to the many people who commented on my papers, including many contributors and readers of this blog.
Although each paper is self-contained, I will list them in the order in which I would recommend reading them to someone who wants to read them all. The first paper is my most detailed articulation of what I call ‘mechanistic account of computation’. The second paper is a systematic taxonomy of kinds of computer from a mechanistic perspective. The third paper is a systematic treatment of connectionist systems from a mechanistic perspective (including, but not limited to, connectionist computation). The fourth paper offers a mechanistic reformulation of functionalism in philosophy of mind and discusses how functionalism does and does not relate to computationalism.
“Computing Mechanisms,” Philosophy of Science, 74.4 (2007), pp. 501-526.
Abstract. This paper offers an account of what it is for a physical system to be a computing system—a system that performs computations. A computing system is a mechanism whose function is to generate output strings from input strings and (possibly) internal states in accordance with a general rule that applies to all relevant strings and depends on the input strings and (possibly) internal states for its application. This account is motivated by reasons endogenous to the philosophy of computing, namely, doing justice to the practices of computer scientists and computability theorists. It is also an application of recent literature on mechanisms, because it assimilates computational explanation to mechanistic explanation. The account can be used to individuate computing mechanisms and the functions they compute and to taxonomize computing mechanisms based on their computing power.
“Computers,” Pacific Philosophical Quarterly, 89.1 (2008), pp. 32-73.
Abstract. I offer an explication of the notion of computer, grounded in the practices of computability theorists and computer scientists. I begin by explaining what distinguishes computers from calculators. Then, I offer a systematic taxonomy of kinds of computer, including hard-wired vs. programmable, general-purpose vs. special-purpose, analog vs. digital, and serial vs. parallel, giving explicit criteria for each kind. My account is mechanistic: which class a system belongs in, and which functions are computable by which system, depends on the system’s mechanistic properties. Finally, I briefly illustrate how my account sheds light on some issues in the history and philosophy of computing as well as the philosophy of mind.
“Some Neural Networks Compute, Others Don’t,” forthcoming Neural Networks.
Abstract. I address whether neural networks perform computations in the sense of computability theory and computer science. I explicate and defend the following theses. (1) Many neural networks compute—they perform computations. (2) Some neural networks compute in a classical way. Ordinary digital computers, which are very large networks of logic gates, belong in this class of neural networks. (3) Other neural networks compute in a non-classical way. (4) Yet other neural networks do not perform computations. Brains may well fall into this last class.
“The Mind as Neural Software? Revisiting Functionalism, Computationalism, and Computational Functionalism,” forthcoming in Philosophy and Phenomenological Research.
Abstract. Defending or attacking either functionalism or computationalism requires clarity on what they amount to and what evidence counts for or against them. My goal here is not to evaluate their plausibility. My goal is to formulate them and their relationship clearly enough that we can determine which type of evidence is relevant to them. I aim to dispel some sources of confusion that surround functionalism and computationalism, recruit recent philosophical work on mechanisms and computation to shed light on them, and clarify how functionalism and computationalism may or may not legitimately come together.