Gualtiero Piccinini University of Missouri St. Louis
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  1. Gualtiero Piccinini (2011). The Physical Church–Turing Thesis: Modest or Bold? British Journal for the Philosophy of Science 62 (4):733 - 769.
    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. (...)
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  2. Gualtiero Piccinini (forthcoming). Scientific Methods Ought to Be Public, and Descriptive Experience Sampling is One of Them. Journal of Consciousness Studies 18 (1).
    Hurlburt and Schwitzgebel’s groundbreaking book, Describing Inner Experience: Proponent Meets Skeptic, examines a research method called Descriptive Experience Sampling (DES). DES, which was developed by Hurlburt and collaborators, works roughly as follows. An investigator gives a subject a random beeper. During the day, as the subject hears a beep, she writes a description of her conscious experience just before the beep. The next day, the investigator interviews the subject, asks for more details, corrects any apparent mistakes made by the subject, (...)
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  3. G. Piccinini & J. Garson (2014). Functions Must Be Performed at Appropriate Rates in Appropriate Situations. British Journal for the Philosophy of Science 65 (1):1-20.
    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 (...)
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  4. Corey Maley & Gualtiero Piccinini (2013). Get the Latest Upgrade: Functionalism 6.3.1. Philosophia Scientiae 17:135-149.
    Functionalism is a popular solution to the mind–body problem. It has a number of versions. We outline some of the major releases of functionalism, listing some of their important features as well as some of the bugs that plagued these releases. We outline how different versions are related. Many have been pessimistic about functionalism’s prospects, but most criticisms have missed the latest upgrades. We end by suggesting a version of functionalism that provides a complete account of the mind.
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  5. Gualtiero Piccinini & Sonya Bahar (2013). Neural Computation and the Computational Theory of Cognition. Cognitive Science 37 (3):453-488.
    We begin by distinguishing computationalism from a number of other theses that are sometimes conflated with it. We also distinguish between several important kinds of computation: computation in a generic sense, digital computation, and analog computation. Then, we defend a weak version of computationalism—neural processes are computations in the generic sense. After that, we reject on empirical grounds the common assimilation of neural computation to either analog or digital computation, concluding that neural computation is sui generis. Analog computation requires continuous (...)
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  6. Gualtiero Piccinini (2011). Scientific Methods Must Be Public, and Descriptive Experience Sampling Qualifies. Journal of Consciousness Studies 18 (1):102-117.
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  7. Gualtiero Piccinini (2011). Two Kinds of Concept: Implicit and Explicit. Dialogue 50 (1):179-193.
  8. Gualtiero Piccinini & Carl Craver (2011). Integrating Psychology and Neuroscience: Functional Analyses as Mechanism Sketches. [REVIEW] Synthese 183 (3):283-311.
    We sketch a framework for building a unified science of cognition. This unification is achieved by showing how functional analyses of cognitive capacities can be integrated with the multilevel mechanistic explanations of neural systems. The core idea is that functional analyses are sketches of mechanisms , in which some structural aspects of a mechanistic explanation are omitted. Once the missing aspects are filled in, a functional analysis turns into a full-blown mechanistic explanation. By this process, functional analyses are seamlessly integrated (...)
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  9. Gualtiero Piccinini & Andrea Scarantino (2011). Information Processing, Computation, and Cognition. Journal of Biological Physics 37 (1):1-38.
    Computation and information processing are among the most fundamental notions in cognitive science. They are also among the most imprecisely discussed. Many cognitive scientists take it for granted that cognition involves computation, information processing, or both – although others disagree vehemently. Yet different cognitive scientists use ‘computation’ and ‘information processing’ to mean different things, sometimes without realizing that they do. In addition, computation and information processing are surrounded by several myths; first and foremost, that they are the same thing. In (...)
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  10. Gualtiero Piccinini, Computation in Physical Systems. Stanford Encyclopedia of Philosophy.
  11. Gualtiero Piccinini (2010). How to Improve on Heterophenomenology: The Self-Measurement Methodology of First-Person Data. Journal of Consciousness Studies 17 (3-4):3 - 4.
    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 (...)
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  12. Gualtiero Piccinini (2010). The Mind as Neural Software? Understanding Functionalism, Computationalism, and Computational Functionalism. Philosophy and Phenomenological Research 81 (2):269-311.
    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 (...)
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  13. Gualtiero Piccinini (2010). The Resilience of Computationalism. Philosophy of Science 77 (5):852-861.
    Roughly speaking, computationalism says that cognition is computation, or that cognitive phenomena are explained by the agent‘s computations. The cognitive processes and behavior of agents are the explanandum. The computations performed by the agents‘ cognitive systems are the proposed explanans. Since the cognitive systems of biological organisms are their nervous 1 systems (plus or minus a bit), we may say that according to computationalism, the cognitive processes and behavior of organisms are explained by neural computations. Some people might prefer to (...)
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  14. Gualtiero Piccinini & Andrea Scarantino (2010). Computation Vs. Information Processing: Why Their Difference Matters to Cognitive Science. Studies in History and Philosophy of Science Part A 41 (3):237-246.
    Since the cognitive revolution, it’s become commonplace that cognition involves both computation and information processing. Is this one claim or two? Is computation the same as information processing? The two terms are often used interchangeably, but this usage masks important differences. In this paper, we distinguish information processing from computation and examine some of their mutual relations, shedding light on the role each can play in a theory of cognition. We recommend that theoristError: Illegal entry in bfrange block in ToUnicode (...)
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  15. Gualtiero Piccinini & Sam Scott (2010). Recovering What Is Said With Empty Names. Canadian Journal of Philosophy 40 (2):239-273.
    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 (...)
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  16. Gualtiero Piccinini & James Virtel (2010). Are Prototypes and Exemplars Used in Distinct Cognitive Processes? Behavioral and Brain Sciences 33 (2-3):226-227.
    Machery’s argument that concepts split into different kinds is bold and inspiring but not fully persuasive. We will focus on the lack of evidence for the fourth tenet of Machery’s..
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  17. Andrea Scarantino & Gualtiero Piccinini (2010). Information Without Truth. Metaphilosophy 41 (3):313-330.
    Abstract: According to the Veridicality Thesis, information requires truth. On this view, smoke carries information about there being a fire only if there is a fire, the proposition that the earth has two moons carries information about the earth having two moons only if the earth has two moons, and so on. We reject this Veridicality Thesis. We argue that the main notions of information used in cognitive science and computer science allow A to have information about the obtaining of (...)
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  18. James Virtel & Gualtiero Piccinini (2010). Are Prototypes and Exemplars Used in Distinct Cognitive Processes? Behavioral and Brain Sciences 33 (2-3):226 - 227.
    We argue that Machery provides no convincing evidence that prototypes and exemplars are typically used in distinct cognitive processes. This partially undermines the fourth tenet of the Heterogeneity Hypothesis and thus casts doubts on Machery’s way of splitting concepts into different kinds. Although Machery may be right that concepts split into different kinds, such kinds may be different from those countenanced by the Heterogeneity Hypothesis.
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  19. Gualtiero Piccinini (2009). Computationalism in the Philosophy of Mind. Philosophy Compass 4 (3):515-532.
    Computationalism has been the mainstream view of cognition for decades. There are periodic reports of its demise, but they are greatly exaggerated. This essay surveys some recent literature on computationalism. It concludes that computationalism is a family of theories about the mechanisms of cognition. The main relevant evidence for testing it comes from neuroscience, though psychology and AI are relevant too. Computationalism comes in many versions, which continue to guide competing research programs in philosophy of mind as well as psychology (...)
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  20. Gualtiero Piccinini (2009). First-Person Data, Publicity and Self-Measurement. Philosophers' Imprint 9 (9):1-16.
    First-person data have been both condemned and hailed because of their alleged privacy. Critics argue that science must be based on public evidence: since first-person data are private, they should be banned from science. Apologists reply that first-person data are necessary for understanding the mind: since first-person data are private, scientists must be allowed to use private evidence. I argue that both views rest on a false premise. In psychology and neuroscience, the subjects issuing first-person reports and other sources of (...)
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  21. Gualtiero Piccinini (2008). Access Denied to Zombies. Unpublished.
    According to the zombie conceivability argument, phenomenal zombies are conceivable, and hence possible, and hence physicalism is false. Critics of the conceivability argument have responded by denying either that zombies are conceivable or that they are possible. Much of the controversy hinges on how to establish and understand what is conceivable, what is possible, and the link between the two—matters that are at least as obscure and controversial as whether consciousness is physical. Because of this, the debate over physicalism is (...)
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  22. Gualtiero Piccinini (2008). Computers. Pacific Philosophical Quarterly 89 (1):32–73.
    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 (...)
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  23. Gualtiero Piccinini (2008). Computation Without Representation. Philosophical Studies 137 (2):205-241.
    The received view is that computational states are individuated at least in part by their semantic properties. I offer an alternative, according to which computational states are individuated by their functional properties. Functional properties are specified by a mechanistic explanation without appealing to any semantic properties. The primary purpose of this paper is to formulate the alternative view of computational individuation, point out that it supports a robust notion of computational explanation, and defend it on the grounds of how computational (...)
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  24. Gualtiero Piccinini (2008). Review of Russell T. Hurlburt, Eric Schwitzgebel, Describing Inner Experience? Proponent Meets Skeptic. [REVIEW] Notre Dame Philosophical Reviews 2008 (4).
  25. Gualtiero Piccinini (2008). Some Neural Networks Compute, Others Don't. Neural Networks 21 (2-3):311-321.
    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.
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  26. Gualtiero Piccinini (2007). Allen Newell. In Noretta Koertge (ed.), New Dictionary of Scientific Biography. Thomson Gale.
    Newell was a founder of artificial intelligence (AI) and a pioneer in the use of computer simulations in psychology. In collaboration with J. Cliff Shaw and Herbert A. <span class='Hi'>Simon</span>, Newell developed the first list-processing programming language as well as the earliest computer programs for simulating human problem solving. Over a long and prolific career, he contributed to many techniques, such as protocol analysis and heuristic search, that are now part of psychology and computer science. Colleagues remembered Newell for his (...)
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  27. Gualtiero Piccinini (2007). Connectionist Computation. In , Proceedings of the 2007 International Joint Conference on Neural Networks.
    The following three theses are inconsistent: (1) (Paradigmatic) connectionist systems perform computations. (2) Performing computations requires executing programs. (3) Connectionist systems do not execute programs. Many authors embrace (2). This leads them to a dilemma: either connectionist systems execute programs or they don't compute. Accordingly, some authors attempt to deny (1), while others attempt to deny (3). But as I will argue, there are compelling reasons to accept both (1) and (3). So, we should replace (2) with a more satisfactory (...)
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  28. Gualtiero Piccinini (2007). Computing Mechanisms. Philosophy of Science 74 (4):501-526.
    This paper offers an account of what it is for a physical system to be a computing mechanism—a system that performs computations. A computing mechanism 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 (...)
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  29. Gualtiero Piccinini (2007). Computational Modeling Vs. Computational Explanation: Is Everything a Turing Machine, and Does It Matter to the Philosophy of Mind? Australasian Journal of Philosophy 85 (1):93 – 115.
    According to pancomputationalism, everything is a computing system. In this paper, I distinguish between different varieties of pancomputationalism. I find that although some varieties are more plausible than others, only the strongest variety is relevant to the philosophy of mind, but only the most trivial varieties are true. As a side effect of this exercise, I offer a clarified distinction between computational modelling and computational explanation.<br><br>.
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  30. Gualtiero Piccinini (2007). Computationalism, the Church–Turing Thesis, and the Church–Turing Fallacy. Synthese 154 (1):97-120.
    The Church–Turing Thesis (CTT) is often employed in arguments for computationalism. I scrutinize the most prominent of such arguments in light of recent work on CTT and argue that they are unsound. Although CTT does nothing to support computationalism, it is not irrelevant to it. By eliminating misunderstandings about the relationship between CTT and computationalism, we deepen our appreciation of computationalism as an empirical hypothesis.
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  31. Gualtiero Piccinini (2007). The Ontology of Creature Consciousness: A Challenge for Philosophy. Behavioral and Brain Sciences 30 (1):103-104.
    I appeal to Merker's theory to motivate a hypothesis about the ontology of consciousness: Creature consciousness is (at least partially) constitutive of phenomenal consciousness. Rather than elaborating theories of phenomenal consciousness couched solely in terms of state consciousness, as philosophers are fond of doing, a correct approach to phenomenal consciousness should begin with an account of creature consciousness.
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  32. Gualtiero Piccinini (2007). The Ontology of Creature Consciousness: A Challenge for Philosophy. Behavioral and Brain Sciences 30 (1).
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  33. Gualtiero Piccinini (2006). Computational Explanation in Neuroscience. Synthese 153 (3):343-353.
    According to some philosophers, computational explanation is proprietary
    to psychology—it does not belong in neuroscience. But neuroscientists routinely offer computational explanations of cognitive phenomena. In fact, computational explanation was initially imported from computability theory into the science of mind by neuroscientists, who justified this move on neurophysiological grounds. Establishing the legitimacy and importance of computational explanation in neuroscience is one thing; shedding light on it is another. I raise some philosophical questions pertaining to computational explanation and outline some promising answers that (...)
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  34. Gualtiero Piccinini & Sam Scott (2006). Splitting Concepts. Philosophy of Science 73 (4):390-409.
    A common presupposition in the concepts literature is that concepts constitute a singular natural kind. If, on the contrary, concepts split into more than one kind, this literature needs to be recast in terms of other kinds of mental representation. We offer two new arguments that concepts, in fact, divide into different kinds: ( a ) concepts split because different kinds of mental representation, processed independently, must be posited to explain different sets of relevant phenomena; ( b ) concepts split (...)
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  35. Gualtiero Piccinini & Sam Scott (2006). Splitting Concepts. Philosophy of Science 73 (4):390-409.
    A common presupposition in the concepts literature is that concepts constitute a sin- gular natural kind. If, on the contrary, concepts split into more than one kind, this literature needs to be recast in terms of other kinds of mental representation. We offer two new arguments that concepts, in fact, divide into different kinds: (a) concepts split because different kinds of mental representation, processed independently, must be posited to explain different sets of relevant phenomena; (b) concepts split because different kinds (...)
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  36. Gualtiero Piccinini (2005). Symbols, Strings, and Spikes. Unpublished.
    I argue that neural activity, strictly speaking, is not computation. This is because computation, strictly speaking, is the processing of strings of symbols, and neuroscience shows that there are no neural strings of symbols. This has two consequences. On the one hand, the following widely held consequences of computationalism must either be abandoned or supported on grounds independent of computationalism: (i) that in principle we can capture what is functionally relevant to neural processes in terms of some formalism taken from (...)
     
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  37. Gualtiero Piccinini (2004). Functionalism, Computationalism, & Mental States. Studies in the History and Philosophy of Science 35 (4):811-833.
    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.
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  38. Gualtiero Piccinini (2004). Functionalism, Computationalism, and Mental Contents. Canadian Journal of Philosophy 34 (3):375-410.
    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. # 2004 Elsevier Ltd. All rights reserved.
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  39. Gualtiero Piccinini (2004). The Functional Account of Computing Mechanisms. PhilSci Archive.
    This paper offers an account of what it is for a physical system to be a computing mechanism—a mechanism that performs computations. A computing mechanism is any mechanism whose functional analysis ascribes it the function of generating outputs strings from input strings in accordance with a general rule that applies to all strings. This account is motivated by reasons that are endogenous to the philosophy of computing, but it may also be seen as an application of recent literature on mechanisms. (...)
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  40. Gualtiero Piccinini (2004). The First Computational Theory of Mind and Brain: A Close Look at McCulloch and Pitts' Logical Calculus of Ideas Immanent in Nervous Activity. Synthese 141 (2):175-215.
    Despite its significance in neuroscience and computation, McCulloch and Pitts's celebrated 1943 paper has received little historical and philosophical attention. In 1943 there already existed a lively community of biophysicists doing mathematical work on neural networks. What was novel in McCulloch and Pitts's paper was their use of logic and computation to understand neural, and thus mental, activity. McCulloch and Pitts's contributions included (i) a formalism whose refinement and generalization led to the notion of finite automata (an important formalism in (...)
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  41. Gualtiero Piccinini (2003). Alan Turing and the Mathematical Objection. Minds and Machines 13 (1):23-48.
    This paper concerns Alan Turing’s ideas about machines, mathematical methods of proof, and intelligence. By the late 1930s, Kurt Gödel and other logicians, including Turing himself, had shown that no finite set of rules could be used to generate all true mathematical statements. Yet according to Turing, there was no upper bound to the number of mathematical truths provable by intelligent human beings, for they could invent new rules and methods of proof. So, the output of a human mathematician, for (...)
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  42. Gualtiero Piccinini (2003). Book Review: John Von Neumann, the Computer and the Brain, 2nd Edition. [REVIEW] Minds and Machines 13 (2):327-332.
  43. Gualtiero Piccinini (2003). Computations and Computers in the Sciences of Mind and Brain. Dissertation. Dissertation, University of Pittsburgh
    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 (...)
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  44. Gualtiero Piccinini (2003). Data From Introspective Reports: Upgrading From Common Sense to Science. Journal of Consciousness Studies 10 (9-10):141-156.
    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 (...)
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  45. Gualtiero Piccinini (2003). Epistemic Divergence and the Publicity of Scientific Methods. Studies in History and Philosophy of Science 34 (3):597-612.
    Epistemic divergence occurs when different investigators give different answers to the same question using evidence-collecting methods that are not public. Without following the principle that scientific methods must be public, scientific communities risk epistemic divergence. I explicate the notion of public method and argue that, to avoid the risk of epistemic divergence, scientific communities should (and do) apply only methods that are public.
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  46. Gualtiero Piccinini (2002). Jean-Pierre Dupuy, the Mechanization of Mind: On the Origins of Cognitive Science. [REVIEW] Minds and Machines 12 (3):448-453.
  47. Peter K. Machamer, Rick Grush, Peter McLaughlin & Gualtiero Piccinini (2001). Book Reviews-Theory and Method in the Neurosciences. Philosophy of Science 68 (4):584-588.
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  48. Gualtiero Piccinini (2001). Mind Gauging: Introspection as a Public Epistemic Resource. PhilSci Archive.
    Introspection used to be excluded from science because it isn?t public--for any question about mental states, only the person whose states are in question can answer by introspecting. However, we often use introspective reports to gauge each other?s minds, and contemporary psychologists generate data from them. I argue that some uses of introspection are as public as any scientific method.
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  49. Gualtiero Piccinini (2000). Turing's Rules for the Imitation Game. Minds and Machines 10 (4):573-582.
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  50. G. Piccinini (1994). Su una critica dell'intelligenza artificiale «forte». Rivista di Filosofia 85 (1):141-146.
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