Gualtiero Piccinini

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.

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 versus programmable, general-purpose versus special-purpose, analog versus digital, and serial versus 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.

We sketch a novel and improved version of Boorse’s biostatistical theory of functions. Roughly, our theory maintains that (i) functions are non-negligible contributions to survival or inclusive fitness (when a trait contributes to survival or inclusive fitness); (ii) situations appropriate for the performance of a function are typical situations in which a trait contributes to survival or inclusive fitness; (iii) appropriate rates of functioning are rates that make adequate contributions to survival or inclusive fitness (in situations appropriate for the performance of that function); and (iv) dysfunction is the inability to perform a function at an appropriate rate in appropriate situations. Based on our theory, we sketch solutions to three problems that have afflicted Boorse’s theory of function, namely, Kingma’s ([2010]) problem of the situation-specificity of functions, the problem of multi-functional traits, and the problem of how to distinguish between appropriate and inappropriate rates of functioning.

As our data will show, negative existential sentences containing socalled empty names evoke the same strong semantic intuitions in ordinary speakers and philosophers alike.Santa Claus does not exist.Superman does not exist.Clark Kent does not exist.Uttering the sentences in (1) seems to say something truth-evaluable, to say something true, and to say something different for each sentence. A semantic theory ought to explain these semantic intuitions.The intuitions elicited by (1) are in apparent conflict with the Millian view of proper names. According to Millianism, the meaning (or 'semantic value') of a proper name is just its referent. But empty names, such as 'Santa Claus' and 'Superman', appear to lack a ..

Introspective reports are used as sources of information about other minds, in both everyday life and science. Many scientists and philosophers consider this practice unjustified, while others have made the untestable assumption that introspection is a truthful method of private observation. I argue that neither skepticism nor faith concerning introspective reports are warranted. As an alternative, I consider our everyday, commonsensical reliance on each other’s introspective reports. When we hear people talk about their minds, we neither refuse to learn from nor blindly accept what they say. Sometimes we accept what we are told, other times we reject it, and still other times we take the report, revise it in light of what we believe, then accept the modified version. Whatever we do, we have (implicit) reasons for it. In developing a sound methodology for the scientific use of introspective reports, we can take our commonsense treatment of introspective reports and make it more explicit and rigorous. We can discover what to infer from introspective reports in a way similar to how we do it every day, but with extra knowledge, methodological care, and precision. Sorting out the use of introspective reports as sources of data is going to be a painstaking, piecemeal task, but it promises to enhance our science of the mind and brain.

ABSTRACT:Determining the biological function of phenomenal consciousness appears necessary to explain its origin: evolution by natural selection operates on organisms’ traits based on the biological functions they fulfill. But identifying the function of phenomenal consciousness has proven difficult. Some have proposed that the function of phenomenal consciousness is to facilitate mental processes such as reasoning or learning. But mental processes such as reasoning and learning seem to be possible in the absence of phenomenal consciousness. It is difficult to pinpoint in what way phenomenal consciousness enhances these processes or others like them. In this paper, we explore a possibility that has been neglected to date. Perhaps phenomenal consciousness has no function of its own because it is either a by-product of other traits or a (functionless) accident. If so, then phenomenal consciousness has an evolutionary explanation even though it fulfills no biological function.

Some philosophers have conflated functionalism and computationalism. I reconstruct how this came about and uncover two assumptions that made the conflation possible. They are the assumptions that (i) psychological functional analyses are computational descriptions and (ii) everything may be described as performing computations. I argue that, if we want to improve our understanding of both the metaphysics of mental states and the functional relations between them, we should reject these assumptions.

Heterophenomenology is a third-person methodology proposed by Daniel Dennett for using first-person reports as scientific evidence. I argue that heterophenomenology can be improved by making six changes: (i) setting aside consciousness, (ii) including other sources of first-person data besides first-person reports, (iii) abandoning agnosticism as to the truth value of the reports in favor of the most plausible assumptions we can make about what can be learned from the data, (iv) interpreting first-person reports (and other first-person behaviors) directly in terms of target mental states rather than in terms of beliefs about them, (v) dropping any residual commitment to incorrigibility of first-person reports, and (vi) recognizing that thirdperson methodology does have positive effects on scientific practices. When these changes are made, heterophenomenology turns into the self-measurement methodology of firstperson data that I have defended in previous papers.

This article defends a modest version of the Physical Church-Turing thesis (CT). Following an established recent trend, I distinguish between what I call Mathematical CT—the thesis supported by the original arguments for CT—and Physical CT. I then distinguish between bold formulations of Physical CT, according to which any physical process—anything doable by a physical system—is computable by a Turing machine, and modest formulations, according to which any function that is computable by a physical system is computable by a Turing machine. I argue that Bold Physical CT is not relevant to the epistemological concerns that motivate CT and hence not suitable as a physical analog of Mathematical CT. The correct physical analog of Mathematical CT is Modest Physical CT. I propose to explicate the notion of physical computability in terms of a usability constraint, according to which for a process to count as relevant to Physical CT, it must be usable by a finite observer to obtain the desired values of a function. Finally, I suggest that proposed counterexamples to Physical CT are still far from falsifying it because they have not been shown to satisfy the usability constraint.

Computationalism says that brains are computing mechanisms, that is, mechanisms that perform computations. At present, there is no consensus on how to formulate computationalism precisely or adjudicate the dispute between computationalism and its foes, or between different versions of computationalism. An important reason for the current impasse is the lack of a satisfactory philosophical account of computing mechanisms. The main goal of this dissertation is to offer such an account.
I also believe that the history of computationalism sheds light on the current debate. By tracing different versions of computationalism to their common historical origin, we can see how the current divisions originated and understand their motivation. Reconstructing debates over computationalism in the context of their own intellectual history can contribute to philosophical progress on the relation between brains and computing mechanisms and help determine how brains and computing mechanisms are alike, and how they differ. Accordingly, my dissertation is divided into a historical part, which traces the early history of computationalism up to 1946, and a philosophical part, which offers an account of computing mechanisms.
The two main ideas developed in this dissertation are that (1) computational states are to be identified functionally not semantically, and (2) computing mechanisms are to be studied by functional analysis. The resulting account of computing mechanism, which I call the functional account of computing mechanisms, can be used to identify computing mechanisms and the functions they compute. I use the functional account of computing mechanisms to taxonomize computing mechanisms based on their different computing power, and I use this taxonomy of computing mechanisms to taxonomize different versions of computationalism based on the functional properties that they ascribe to brains. By doing so, I begin to tease out empirically testable statements about the functional organization of the brain that different versions of computationalism are committed to. I submit that when computationalism is reformulated in the more explicit and precise way I propose, the disputes about computationalism can be adjudicated on the grounds of empirical evidence from neuroscience.