In this paper we aim to defend a version of the thesis of “extended mind” against the criticism of some authors that consider that the “extracraneal” devices cannott acomplish the requirements that the components of mental processes must meet. We propose a quality of integration as a criterion to be a mental process, and we consider that, in some situations, external devices can be considered as meeting this criterion.

In this paper, we try to show why a formal definition of truth is not satisfactory (first point). Later, we expound (second point) the polemic between Austin and Strawson about truth with the intention to show that both refer to different problems concerning truth and to prove that Austin did not lose this confrontation and that we can recover some elements of his investigation for making an adequate approach to this notion. We will complete our definition of truth using the (...) latest thesis of Charles Travis and that will permit us to conclude with a semantic definition of truth for natural languages. (shrink)

Behaviour is often described as the computation of a response to a stimulus. This description is incomplete in an important way because it only examines what occurs between the reception of stimulus information and the generation of an action. Behaviour is more correctly described as a control process where actions are performed in order to affect perceptions. This closed-loop nature of behaviour is de-emphasized in modern discussions of brain function, leading to a number of artificial mysteries. A notable example is (...) the ‘symbol grounding problem'. When behaviour is viewed as a control process, it is natural to explain how internal representations, even symbols, can have meaning for an organism, and how actions can be motivated by organic needs. (shrink)

This chapter analyzes aspects of the relationship between consciousness and intentionality. It focuses on the phenomenal character and the intentional content of perceptual states, canvassing various possible relations among them. It argues that there is a good case for a sort of representationalism, although this may not take the form that its advocates often suggest. By mapping out some of the landscape, the chapter tries to open up territory for different and promising forms of representationalism to be explored in the (...) future. In particular, it argues for a nonreductive, narrow, and Fregean variety of representationalism, which contrasts strongly with more widely explored varieties. It concludes with some words about the fundamental relationship between consciousness and intentionality. (shrink)

Digital computers play a special role in cognitive science—they may actually be instances of the phenomenon they are being used to model. This paper surveys some of the main issues involved in understanding the relationship between digital computers and cognition. It sketches the role of digital computers within orthodox computational cognitive science, in the light of a recently emerging alternative approach based around dynamical systems.

Computational complexity is a discipline of computer science and mathematics which classifies computational problems depending on their inherent difficulty, i.e. categorizes algorithms according to their performance, and relates these classes to each other. P problems are a class of computational problems that can be solved in polynomial time using a deterministic Turing machine while solutions to NP problems can be verified in polynomial time, but we still do not know whether they can be solved in polynomial time as well. A (...) solution for the so-called NP-complete problems will also be a solution for any other such problems. Its artificial-intelligence analogue is the class of AI-complete problems, for which a complete mathematical formalization still does not exist. In this chapter we will focus on analysing computational classes to better understand possible formalizations of AI-complete problems, and to see whether a universal algorithm, such as a Turing test, could exist for all AI-complete problems. In order to better observe how modern computer science tries to deal with computational complexity issues, we present several different deep-learning strategies involving optimization methods to see that the inability to exactly solve a problem from a higher order computational class does not mean there is not a satisfactory solution using state-of-the-art machine-learning techniques. Such methods are compared to philosophical issues and psychological research regarding human abilities of solving analogous NP-complete problems, to fortify the claim that we do not need to have an exact and correct way of solving AI-complete problems to nevertheless possibly achieve the notion of strong AI. (shrink)

This PhD thesis focuses on the philosophical foundations of Neuroeconomics, an innovative research program which combines findings and modelling tools from economics, psychology and neuroscience to account for human choice behaviour. The proponents of Neuroeconomics often manifest the ambition to foster radical modifications in the accounts of choice behaviour developed by its parent disciplines. This enquiry provides a philosophically informed appraisal of the potential for success and the relevance of neuroeconomic research for economics. My central claim is that neuroeconomists can (...) help other economists to build more predictive and explanatory models, yet are unlikely to foster revolutionary modifications in the economic theory of choice. The contents are organized as follows. In chapters 1-2, I present neuroeconomists’ investigative tools, distinguish the most influential approaches to neuroeconomic research and reconstruct the case in favour of a neural enrichment of economic theory. In chapters 3-7, I combine insights from neuro-psychology, economic methodology and philosophy of science to develop a systematic critique of Neuroeconomics. In particular, I articulate four lines of argument to demonstrate that economists are provisionally justified in retaining a methodologically distinctive approach to the modelling of decision making. My first argument points to several evidential and epistemological concerns which complicate the interpretation of neural data and cast doubt on the inferences neuroeconomists often make in their studies. My second argument aims to show that the trade-offs between the modelling desiderata that neuroeconomists and other economists respectively value severely constrain the incorporation of neural insights into economic models. My third argument questions neuroeconomists’ attempts to develop a unified theory of choice behaviour by identifying some central issues on which they hold contrasting positions. My fourth argument differentiates various senses of the term ‘revolution’ and illustrates that neuroeconomists are unlikely to provide revolutionary contributions to economic theory in any of these senses. (shrink)

Having, as it is generally agreed, failed to destroy the computational conception of mind with the G\"{o}delian attack he articulated in his {\em The Emperor's New Mind}, Penrose has returned, armed with a more elaborate and more fastidious G\"{o}delian case, expressed in and 3 of his {\em Shadows of the Mind}. The core argument in these chapters is enthymematic, and when formalized, a remarkable number of technical glitches come to light. Over and above these defects, the argument, at best, is (...) an instance of either the fallacy of denying the antecedent, the fallacy of {\em petitio principii}, or the fallacy of equivocation. More recently, writing in response to his critics in the electronic journal {\em Psyche}, Penrose has offered a G\"{o}delian case designed to improve on the version presented in {\em SOTM}. But this version is yet again another failure. In falling prey to the errors we uncover, Penrose's new G\"{o}delian case is unmasked as the same confused refrain J.R. Lucas initiated 35 years ago. (shrink)

We show how an epistemology informed by cognitive science promises to shed light on an ancient problem in the philosophy of mathematics: the problem of exactness. The problem of exactness arises because geometrical knowledge is thought to concern perfect geometrical forms, whereas the embodiment of such forms in the natural world may be imperfect. There thus arises an apparent mismatch between mathematical concepts and physical reality. We propose that the problem can be solved by emphasizing the ways in which the (...) brain can transform and organize its perceptual intake. It is not necessary for a geometrical form to be perfectly instantiated in order for perception of such a form to be the basis of a geometrical concept. (shrink)

This paper aims to explore mechanistic and teleological explanations of consciousness. In terms of mechanistic explanations, it critiques various existing views, especially those embodied by existing computational cognitive models. In this regard, the paper argues in favor of the explanation based on the distinction between localist (symbolic) representation and distributed representation (as formulated in the connectionist literature), which reduces the phenomenological difference to a mechanistic difference. Furthermore, to establish a teleological explanation of consciousness, the paper discusses the issue of the (...) functional role of consciousness on the basis of the aforementioned mechanistic explanation. A proposal based on synergistic interaction between the conscious and the unconscious is advanced that encompasses various existing views concerning the functional role of consciousness. This two-step deepening explanation has some empirical support, in the form of a cognitive model and various cognitive data that it captures. © 2001 Elsevier Science B.V. All rights reserved. (shrink)

Replication or even modelling of consciousness in machines requires some clarifications and refinements of our concept of consciousness. Design of, construction of, and interaction with artificial systems can itself assist in this conceptual development. We start with the tentative hypothesis that although the word “consciousness” has no well-defined meaning, it is used to refer to aspects of human and animal informationprocessing. We then argue that we can enhance our understanding of what these aspects might be by designing and building virtual-machine (...) architectures capturing various features of consciousness. This activity may in turn nurture the development of our concepts of consciousness, showing how an analysis based on information-processing virtual machines answers old philosophical puzzles as well enriching empirical theories. This process of developing and testing ideas by developing and testing designs leads to gradual refinement of many of our pre-theoretical concepts of mind, showing how they can be construed as implicitly “architecture-based” concepts. Understanding how humanlike robots with appropriate architectures are likely to feel puzzled about qualia may help us resolve those puzzles. The concept of “qualia” turns out to be an “architecture-based” concept, while individual qualia concepts are “architecture-driven”. (shrink)

More than a decade ago, philosopher John Searle started a long-running controversy with his paper “Minds, Brains, and Programs” (Searle, 1980a), an attack on the ambitious claims of artificial intelligence (AI). With his now famous _Chinese Room_ argument, Searle claimed to show that despite the best efforts of AI researchers, a computer could never recreate such vital properties of human mentality as intentionality, subjectivity, and understanding. The AI research program is based on the underlying assumption that all important aspects of (...) human cognition may in principle be captured in a computational model. This assumption stems from the belief that beyond a certain level, implementational details are irrelevant to cognition. According to this belief, neurons, and biological wetware in general, have no preferred status as the substrate for a mind. As it happens, the best examples of minds we have at present have arisen from a carbon-based substrate, but this is due to constraints of evolution and possibly historical accidents, rather than to an absolute metaphysical necessity. As a result of this belief, many cognitive scientists have chosen to focus not on the biological substrate of the mind, but instead on the abstract causal structure_ _that the mind embodies (at an appropriate level of abstraction). The view that it is abstract causal structure that is essential to mentality has been an implicit assumption of the AI research program since Turing (1950), but was first articulated explicitly, in various forms, by Putnam (1960), Armstrong (1970) and Lewis (1970), and has become known as _functionalism_. From here, it is a very short step to _computationalism_, the view that computational structure is what is important in capturing the essence of mentality. This step follows from a belief that any abstract causal structure can be captured computationally: a belief made plausible by the Church–Turing Thesis, which articulates the power. (shrink)

A myth has arisen concerning Turing's paper of 1936, namely that Turing set forth a fundamental principle concerning the limits of what can be computed by machine - a myth that has passed into cognitive science and the philosophy of mind, to wide and pernicious effect. This supposed principle, sometimes incorrectly termed the 'Church-Turing thesis', is the claim that the class of functions that can be computed by machines is identical to the class of functions that can be computed by (...) Turing machines. In point of fact Turing himself nowhere endorses, nor even states, this claim (nor does Church). I describe a number of notional machines, both analogue and digital, that can compute more than a universal Turing machine. These machines are exemplars of the class of _nonclassical_ computing machines. Nothing known at present rules out the possibility that machines in this class will one day be built, nor that the brain itself is such a machine. These theoretical considerations undercut a number of foundational arguments that are commonly rehearsed in cognitive science, and gesture towards a new class of cognitive models. (shrink)

Cognitive science has been beset for thirty years by foundational disputes about the nature and extension of cognition—e.g. whether cognition is necessarily representational, whether cognitive processes extend outside the brain or body, and whether plants or microbes have them. Whereas previous philosophical work aimed to settle these disputes, I aim to understand what conception of cognition scientists could share given that they disagree so fundamentally. To this end, I develop a number of variations on traditional conceptual explication, and defend a (...) novel explication of cognition called the sensitive management hypothesis. -/- Since expert judgments about the extension of “cognition” vary so much, I argue that there is value in explication that accurately models the variance in judgments rather than taking sides or treating that variance as noise. I say of explications that accomplish this that they are ecumenically extensionally adequate. Thus, rather than adjudicating whether, say, plants can have cognitive processes like humans, an ecumenically adequate explication should classify these cases differently: human cognitive processes as paradigmatically cognitive, and plant processes as controversially cognitive. -/- I achieve ecumenical adequacy by articulating conceptual explications with parameters, or terms that can be assigned a number of distinct interpretations based on the background commitments of participants in a discourse. For example, an explication might require that cognition cause “behavior,” and imply that plant processes are cognitive or not depending on whether anything plants do can be considered “behavior.” Parameterization provides a unified treatment of embattled concepts by isolating topics of disagreement in a small number of parameters. -/- I incorporate these innovations into an account on which cognition is the “sensitive management of organismal behavior.” The sensitive management hypothesis is ecumenically extensionally adequate, accurately classifying a broad variety of cases as paradigmatically or controversially cognitive phenomena. I also describe an extremely permissive version of the sensitive management hypothesis, arguing that it has the potential to explain several features of cognitive scientific discourse, including various facts about the way cognitive scientists ascribe representations to cognitive systems. (shrink)

The argument presented in this paper is not a direct attack or defence of the Chinese Room Argument (CRA), but relates to the premise at its heart, that syntax is not sufficient for semantics, via the closely associated propositions that semantics is not intrinsic to syntax and that syntax is not intrinsic to physics. However, in contrast to the CRA’s critique of the link between syntax and semantics, this paper will explore the associated link between syntax and physics. The main (...) argument presented here is not significantly original – it is a simple reflection upon that originally given by Hilary Putnam (Putnam 1988) and criticised by David Chalmers and others: instead of seeking to justify Putnam’s claim that, “every open system implements every Finite State Automaton (FSA)”, and hence that psychological states of the brain cannot be functional states of a computer, I will seek to establish the weaker result that, over a finite time window every open system implements the trace of a particular FSA Q, as it executes program (p) on input (x). That this result leads to panpsychism is clear as, equating Q (p, x) to a specific Strong AI program that is claimed to instantiate phenomenal states as it executes, and following Putnam’s procedure, identical computational (and ex hypothesi phenomenal) states (ubiquitous little ‘pixies’) can be found in every open physical system. (shrink)

Context: The advent of a general artificial intelligence mechanism that learns like humans do would represent the realization of an old and major dream of science. It could be achieved by an artifact able to develop its own cognitive structures following constructivist principles. However, there is a large distance between the descriptions of the intelligence made by constructivist theories and the mechanisms that currently exist. Problem: The constructivist conception of intelligence is very powerful for explaining how cognitive development takes place. (...) However, until now, no computational model has successfully demonstrated the underlying mechanisms necessary to realize it. In other words, the artificial intelligence (AI) community has not been able to give rise to a system that convincingly implements the principles of intelligence as postulated by constructivism, and that is also capable of dealing with complex environments. Results: This paper presents the constructivist anticipatory learning mechanism (CALM), an agent learning mechanism based on the constructivist approach of AI. It is designed to deal dynamically and interactively with environments that are at the same time partially deterministic and partially observable. CALM can model the regularities experienced in the interaction with the environment, on the sensorimotor level as well, as by constructing abstract or high-level representational concepts. The created model provides the knowledge necessary to generate the agent behavior. The paper also presents the coupled agent environment system (CAES) meta-architecture, which defines a conception of an autonomous agent, situated in the environment, embodied and intrinsically motivated. Implications: The paper can be seen as a step towards a computational implementation of constructivist principles, on the one hand suggesting a further perspective of this refreshing movement on the AI field (which is still too steeped in a behaviorist influence and dominated by probabilistic models and narrow applied approaches), and on the other hand bringing some abstract descriptions of the cognitive process into a more concrete dimension, in the form of algorithms. Constructivist content: The connection of this paper with constructivism is the proposal of a computational and formally described mechanism that implements important aspects of the subjective process of knowledge construction based on key ideas proposed by constructivist theories. (shrink)

This is a draft of the written version of comments on a paper by David Cole, presented orally at the American Philosophical Association Central Division meeting in New Orleans, 27 April 1990. Following the written comments are 2 appendices: One contains a letter to Cole updating these comments. The other is the handout from the oral presentation.

I argue against the commonly held intuition that robots and virtual agents will never have emotions by contending robots can have emotions in a sense that is functionally similar to humans, even if the robots' emotions are not exactly equivalent to those of humans. To establish a foundation for assessing the robots' emotional capacities, I first define what emotions are by characterizing the components of emotion consistent across emotion theories. Second, I dissect the affective-cognitive architecture of MIT's Kismet and Leonardo, (...) two robots explicitly designed to express emotions and to interact with humans, in order to explore whether they have emotions. I argue that, although Kismet and Leonardo lack the subjective feelings component of emotion, they are capable of having emotions. (shrink)

The overall aim of this thesis is to look at some philosophical issues surrounding autonomous systems in society and war. These issues can be divided into three main categories. The first, discussed in papers I and II, concerns ethical issues surrounding the use of autonomous systems – where the focus in this thesis is on military robots. The second issue, discussed in paper III, concerns how to make sure that advanced robots behave ethically adequate. The third issue, discussed in papers (...) IV and V, has to do with agency and responsibility. Another issue, somewhat aside from the philosophical, has to do with coping with future technologies, and developing methods for dealing with potentially disruptive technologies. This is discussed in papers VI and VII. Paper I systemizes some ethical issues surrounding the use of UAVs in war, with the laws of war as a backdrop. It is suggested that the laws of war are too wide and might be interpreted differently depending on which normative moral theory is used. Paper II is about future, more advanced autonomous robots, and whether the use of such robots can undermine the justification for killing in war. The suggestion is that this justification is substantially undermined if robots are used to replace humans to a high extent. Papers I and II both suggest revisions or additions to the laws or war. Paper III provides a discussion on one normative moral theory – ethics of care – connected to care robots. The aim is twofold: first, to provide a plausible and ethically relevant interpretation of the key term care in ethics of care, and second, to discuss whether ethics of care may be a suitable theory to implement in care robots. Paper IV discusses robots connected to agency and responsibility, with a focus on consciousness. The paper has a functionalistic approach, and it is suggested that robots should be considered agents if they can behave as if they are, in a moral Turing test. Paper V is also about robots and agency, but with a focus on free will. The main question is whether robots can have free will in the same sense as we consider humans to have free will when holding them responsible for their actions in a court of law. It is argued that autonomy with respect to norms is crucial for the agency of robots. Paper VI investigates the assessment of socially disruptive technological change. The coevolution of society and potentially disruptive technolgies makes decision-guidance on such technologies difficult. Four basic principles are proposed for such decision guidance, involving interdisciplinary and participatory elements. Paper VII applies the results from paper VI – and a workshop – to autonomous systems, a potentially disruptive technology. A method for dealing with potentially disruptive technolgies is developed in the paper. (shrink)

Applying Bernard Lonergan's (1957/1992, 1972) analysis of intentional consciousness and its concomitant epistemology, this paper highlights epistemological confusion in contemporary consciousness studies as exemplified mostly in David Chalmers's (1996) position. In ideal types, a first section outlines two epistemologies-sensate-modeled and intelligence-based-whose difference significantly explains the different positions. In subsequent sections, this paper documents the sensate-modeled epistemology in Chalmers's position and consciousness studies in general. Tellingly, this model of knowing is at odds with the formal-operational theorizing in twentieth-century science. This paper (...) then links this epistemology with functionalism and its focus on descriptive efficient causality in external behaviors and its oversight of explanatory formal causality; highlights the theoretical incoherence of the understanding of science in the functionalist approach; connects it with the construal of consciousness as primarily intentional (i.e., directed toward an object) to the neglect of consciousness as conscious (i.e., constituted by a non-objectified self-presence); and relates this outcome to the reduction of human consciousness to animal-like perception and mechanistic interactions. A brief conclusion summarizes these multiple, subtle, and interconnected considerations and suggests how only an intellectual epistemology would be adequate to the intellectual nature of human consciousness and the world of meaning, not of mere bodies, in which humans exist. (shrink)

Donald Davidson and John Searle famously differ, among other things, on the issue of animal thoughts. Davidson seems to be a latter-day Cartesian, denying any propositional thought to subhuman animals, while Searle seems to follow Hume in claiming that if we have thoughts, then animals do, too. Davidson’s argument centers on the idea that language is necessary for thought, which Searle rejects. The paper argues two things. Firstly, Searle eventually argues that much of a more complex thought does depend on (...) language, which reduces a distance between himself and Davidson. Secondly, some of Davidson’s suggestions are promising – in particular the idea that we may lack a vocabulary to capture the contents of animal thoughts. Based on this insight, one might, pace Davidson, grant thoughts to animals. However, this does not mean, pace Searle, that it should be possible to construe even the simplest of such thoughts as propositional. Perhaps we need to move beyond Davidson and Searle by developing a theory of nonpropositional thought for animals. (shrink)

One might think that, once we know something is computable, how efficiently it can be computed is a practical question with little further philosophical importance. In this essay, I offer a detailed case that one would be wrong. In particular, I argue that computational complexity theory---the field that studies the resources needed to solve computational problems---leads to new perspectives on the nature of mathematical knowledge, the strong AI debate, computationalism, the problem of logical omniscience, Hume's problem of induction and Goodman's (...) grue riddle, the foundations of quantum mechanics, economic rationality, closed timelike curves, and several other topics of philosophical interest. I end by discussing aspects of complexity theory itself that could benefit from philosophical analysis. (shrink)

This work analyzes the central role of interpretation in non-routine design. Based on this analysis, a theory of computer support for interpretation in cooperative design is constructed. The theory is grounded in studies of design and interpretation. It is illustrated by mechanisms provided by a software substrate for computer-based design environments, applied to a sample task of lunar habitat design. ;Computer support of innovative design must overcome the problem that designers necessarily make extensive use of situated tacit understanding while computers (...) can only store and display explicit representations of information. The automation techniques used for routine design are not applicable: techniques are needed to support creative, tacit human understanding with explicit computer representations. ;The process by which designers transform their tacit preunderstanding into explicit knowledge is termed "interpretation". Interpretation is necessary for solving design problems and collaborating with other designers. Considerable explicit knowledge is thereby generated in the natural course of designing. Often this knowledge includes the most valuable information that can be presented to designers who revisit these design projects or undertake similar projects in the future. If representations of this knowledge have been defined using computer-based design support systems, then the representations can be captured by these systems for the support of subsequent design work. ;A theory of computer support for interpretation in design is presented in three stages. First, the role of interpretation in design is explored by reviewing descriptions of design by Alexander, Rittel, and Schon; by conducting a protocol analysis of lunar habitat design; and by applying Heidegger's philosophy of situated interpretation. Second, this analysis of interpretation is extended to define a theory of computer support. The features of this theory--support for the situated, perspectival, and linguistic characteristics of interpretation--are used to evaluate previous work on software design rationale systems. Third, design principles are discussed for H scERMES, a prototype hypermedia substrate for building computer-based design environments to support interpretation in tasks like lunar habitat design. The hypermedia integrates a perspectives mechanism and an end-user language to capture and modify representations of the design situation, alternative perspectives on design tasks, and terminology for conceptualizing design issues. (shrink)

A satisfactory solution to the problem of consciousness would take the form of a simple yet fully general model that specifies the precise conditions under which any given state of consciousness occurs. Science has uncovered numerous correlations between consciousness and neural activity, but it has not yet come anywhere close to this. We are still looking for the Newtonian laws of consciousness. -/- One of the main difficulties with consciousness is that we lack a language in which to formulate illuminating (...) generalizations about it. Philosophers and scientists talk about "what it’s like", sensations, feelings, and perceptual states such as seeing and hearing. This language does not allow a precise articulation of the internal structures of conscious states and their inter-relations. It is inadequate to capture relations of the kind we are looking for between conscious states and physical states. -/- In this thesis I refine and defend a theory of consciousness which promises to solve this regimentation problem: the representational theory of consciousness. I argue that the representational theory can solve the regimentation problem and smooth out other important obstacles to a fruitful study of consciousness. I also make a case for the theory independently of its payoffs, and I discuss the leading opposing theories at some length. (shrink)

Functional intentionality is the dominant theory about how mental states come to have the content that they do. Phenomenal intentionality is an increasingly popular alternative to that orthodoxy, claiming that intentionality cannot be functionalized and that nothing is a mental state with intentional content unless it is phenomenally conscious. There is a consensus among defenders of phenomenal intentionality that the kind of phenomenology that is both necessary and sufficient for having a belief that "there is a tree in the quad" (...) is that the agent be consciously aware of the meaning of "tree" and "quad". On this theory, experiences with a valence -- experiences like happiness and sadness, satisfaction and frustration -- are irrelevant to intentionality. This paper challenges that assumption and considers several versions of "valent phenomenal intentionality" according to which a capacity for valent conscious experiences is either a necessary or a sufficient condition for intentionality (or both). (shrink)

This paper opens the philosophical debate around the notion of Artificial General Intelligence (AGI) and its application in Large Language Models (LLMs). Through the lens of moral philosophy, the paper raises questions about these AI systems' capabilities and goals, the treatment of humans behind them, and the risk of perpetuating a monoculture through language.

David Haig propounds and illustrates the unity of a radically revised set of definitions of the family of terms at the heart of philosophy of cognitive science and mind: information, meaning, interpretation, text, choice, possibility, cause. This biological re-grounding of much-debated concepts yields a bounty of insights into the nature of meaning and life. An interpreter is a mechanism that uses information in choice. The capabilities of the interpreter couple an entropy of inputs to an entropy of outputs is dispelled (...) by observation. The second entropy is dispelled. I propose that an interpreter’s response to inputs meaning of the information for the interpreter. In this conceptual framework, the mechanisms of interpreters provide the much-debated link between Shannon information and semantics. (shrink)

The Turing Machine presents itself as the very landmark and initial design of digital automata present in all modern general-purpose digital computers and whose design on computable numbers implies deeply ontological as well as epistemological foundations for today’s computers. These lines of work attempt to briefly analyze the fundamental epistemological problem that rose in the late 19th and early 20th century whereby “machine cognition” emerges. The epistemological roots addressed in the TM and notably in its “Halting Problem” uncovers the tension (...) between determinism and uncertainty, regarded here as the primal and inherent features of machine cognition. Resumen La Máquina de Turing se presenta como el hito y el diseño inicial de un autómata digital presente en todas las computadoras digitales modernas de propósito general y cuyo diseño en números computables establece bases profundamente ontológicas y epistemológicas para las computadoras de hoy. Estas líneas de trabajo intentan analizar brevemente el problema epistemológico fundamental que surgió a finales del siglo XIX y principios del XX mediante el cual emerge la “cognición de la máquina”. Las raíces epistemológicas que se abordan en la TM y, en particular, en su “Problema de detención” ponen al descubierto la tensión entre el determinismo y la incertidumbre, consideradas aquí, como las características primordiales e inherentes de la cognición de la máquina. (shrink)

In this article I present some characteristics of logics and semantics of an uncertain world. I confront two-valued and fuzzy logic. I use Kafka’s novel Process as an example, which is designed as an uncertain context with words which are rigid designators without rigid meaning. That produces an uncertain world of logical and semantical relations. In presentation of problems I introduce basic concepts of Frege’s, Wittgenstein’s, Tarsky’s, Searle’s, Quine’s and Davidson’s philosophy of language. I differ the logical and semantical identification (...) of identity. I differ reference and inference, or representation and identification as two components which are fundamental for the identification of identity. I found this difference on the role of logical unification and granulation of predicates in the structure of thought and semantical unification and granulation of attributes in the structure of statements and their relation to ontology of context. Through the confrontation of the logical and semantical unification and granulation I find that the limits of logic are not also the limits of language. The semantical unification goes over the highest genre and below the lowest species. That enables the extra-logical, non-scientifical, con-fessional, pro-phetical, artistic, and ordinary use of language. (shrink)

We provide two programmatic frameworks for integrating philosophical research on understanding with complementary work in computer science, psychology, and neuroscience. First, philosophical theories of understanding have consequences about how agents should reason if they are to understand that can then be evaluated empirically by their concordance with findings in scientific studies of reasoning. Second, these studies use a multitude of explanations, and a philosophical theory of understanding is well suited to integrating these explanations in illuminating ways.

Is it possible to build a conscious machine, an artifact that has qualitative experiences such as feeling pain, seeing the redness of a flower or enjoying the taste of coffee ? What makes such experiences conscious is their phenomenal character: it is like something to have such experiences. In contemporary philosophy of mind, the question of the qualitative aspect of conscious experiences is often addressed in terms of qualia. In a pre-theoretical and intuitive sense, qualia refer to the phenomenal character (...) or “what-it’s-like-ness” of a conscious experience: the painfulness of a pain experience or the redness of a visual experience of a red object. The problem of artificial qualia is the question of the theoretical possibility of the realization of qualia by artifacts. In this work, this problem will serve as a methodological tool to address what is arguably the most fundamental question of philosophy of mind: what exactly is consciousness? (shrink)

In this paper, I will present the responsibility-compatibilist argument against responsibility-incompatibilists (hard-determinists and libertarians), according to whom the existence of ‘free-will’, threatened by determinism, is necessary for moral responsibility. First, I will identify what responsibility-incompatibilism presupposes as necessary conditions of moral responsibility: the Strong Doctrine of Free-Will and the Voluntary Control Principle. Second, inspired by Williams, I will demonstrate that our real practice of responsibility does not necessarily presuppose these conditions. Finally, I will defend responsibility-compatibilism from an objection.

Contemporary psychologism has been amended for most of the objections by its opponents over a century ago. However, some authors still raise doubts about its ability to account for some peculiar properties of logic. In particular, it is argued that the psychological universality of patterns of inferential behavior is not sufficient to account for the normativity of logic. In this paper, I deal with the issue and offer three alternative solutions that do not rely on mere empirical universality. I will (...) use the works of Laurence Jonathan Cohen, Diego Marconi and Marcello D'Agostino, adapting them for the purpose of defending logical psychologism. I will therefore argue that, although more refined work on the subject is needed, contemporary psychologism has the key resources to retain its place in the philosophical debate on the foundations of logic. (shrink)

n this thesis I describe how conventions specify how to put normative principles into practice. I identify a class of recurring situations where there are some given normative principles in effect, but they underdetermine what each individual should do, and what is best for an individual depends on what others do. I demonstrate that in such cases, whenever the community develops a response that repeatedly brings them to as good an outcome as is available according to their principles, that response (...) is a Lewisian convention where the benefit of an outcome to each individual is measured by the extent to which it conforms to the principles they subscribe to. Since these conventions are constrained by the normative principles, I call them limited conventions. They are supplements to the principles, and are ineradicably involved in moral action insofar as the abovementioned cases of moral underdetermination are in play. That has the consequence that in these cases the only reliable way to follow your principles is to follow the relevant conventions. As examples of this mechanism I offer a conventionalist analysis of authority, such that the commands of an authority is normative when they instantiate a limited convention, and of the variation in understandings of virtue and vice across societies, such that the evaluative vocabulary of each society is a set of different limited conventions about how to express in word and deed the evaluative points of the virtues and vices in question. Finally, I discuss how conventions and similar forms of guidance provide a way for individuals to participate in their community’s moral life without having a full understanding of the principles that underlie it, or even if they are profoundly ignorant or outright mistaken about the demands of morality. (shrink)

This article aims to identify the bundle theory and its influence on the philosophy of mind discussions. The theory was put forward by David Hume, one of the pioneer philosophers of the Enlightenment era, in the context of personal identity. Firstly, a general framework will be drawn about the problem of personal identity. Secondly, it will be explained how the problem is understood in Hume’s epistemology through concepts such as person, identity, self, selfhood. To see the philosophical effects caused by (...) Hume's epistemology, discussions of the philosophy of mind will be exemplified in the existence and knowledge of self through the mindbody understandings of philosophers. Daniel Dennet, John Searle, David Chalmers, and Thomas Metzinger, who have theories about the relationship of self, consciousness, and matter, are the names to be considered under the title of philosophy of mind. Finally, Hume and his theories will be presented with several assessments of the philosophical problems caused by the positions of the aforementioned names on the issue of self. This article aims to reveal the similarities between Hume and philosophers of mind in terms of the existence and knowledge of the self. Except for the evaluation and conclusion section, this article aims to present preliminary work on these approaches. (shrink)

A. Newell and H. A. Simon were two of the most influential scientists in the emerging field of artificial intelligence (AI) in the late 1950s through to the early 1990s. This paper reviews their crucial contribution to this field, namely to symbolic AI. This contribution was constituted mostly by their quest for the implementation of general intelligence and (commonsense) knowledge in artificial thinking or reasoning artifacts, a project they shared with many other scientists but that in their case was theoretically (...) based on the idiosyncratic notions of symbol systems and the representational abilities they give rise to, in particular with respect to knowledge. While focusing on the period 1956-1982, this review cites both earlier and later literature and it attempts to make visible their potential relevance to today's greatest unifying AI challenge, to wit, the design of wholly autonomous artificial agents (a.k.a. robots) that are not only rational and ethical, but also self-conscious. (shrink)

The late 19th-century Ignorabimus controversy over the limits of scientific knowledge has often been characterized as proclaiming the end of intellectual progress, and by implication, as plunging Germany into a crisis of pessimism from which Liberalism never recovered. My research supports the opposite interpretation. The initiator of the Ignorabimus controversy, Emil du Bois-Reymond, was a physiologist who worked his whole life against the forces of obscurantism, whether they came from the Catholic and Conservative Right or the scientistic and millenarian Left. (...) Du Bois-Reymond’s doubt that scientists would ever elucidate consciousness must therefore be seen as an endorsement, and not a rejection, of his faith in reason. (shrink)

Philosophers of information, according to Luciano Floridi (The philosophy of information. Oxford University Press, Oxford, 2010, p 32), study how information should be “adequately created, processed, managed, and used.” A small number of epistemologists have employed the concept of information as a cornerstone of their theoretical framework. How this concept can be used to make sense of seemingly intractable epistemological problems, however, has not been widely explored. This paper examines Fred Dretske’s information-based epistemology, in particular his response to radical epistemological (...) skepticism. We discuss the relationship between information, evidence and knowledge in relation to the problem of skepticism and the options available to an information-based epistemology for dealing with it. (shrink)

Deferential Monadic Panpsychism is a view that accepts that physical science is capable of discovering the basic structure of reality. However, it denies that reality is fully and exhaustively de- scribed purely in terms of physical science. Consciousness is missing from the physical description and cannot be reduced to it. DMP explores the idea that the physically fundamental features of the world possess some intrinsic mental aspect. It thereby faces a se- vere problem of understanding how more complex mental states (...) emerge from the mental features of the fundamental features. Here I explore the idea that a new form of aggregative emergence, which I call 'combinatorial infusion', could shed light on this problem and bolster the prospects for this form of panpsychism. (shrink)

Critical in the computationalist account of the mind is the phenomenon called computational or computer simulation of human thinking, which is used to establish the theses that human thinking is a computational process and that computing machines are thinking systems. Accordingly, if human thinking can be simulated computationally then human thinking is a computational process; and if human thinking is a computational process then its computational simulation is itself a thinking process. This paper shows that the said phenomenon—the computational simulation (...) of human thinking—is ill-conceived, and that, as a consequence, the theses that it intends to establish are problematic. It is argued that what is simulated computationally is not human thinking as such but merely its behavioral manifestations; and that a computational simulation of these behavioral manifestations does not necessarily establish that human thinking is computational, as it is logically possible for a non-computational system to exhibit behaviors that lend themselves to a computational simulation. (shrink)

The Hypothesis of Extended Cognition (HEC) holds that that not all human cognition is realized inside the head. The related but distinct Hypothesis of Extended Mentality (HEM) holds that not all human mental items are realized inside the head. Clark & Chalmers distinguish between these hypotheses in their original treatment of cognitive extension, yet these two claims are often confused. I distinguish between functionalist theories on which functional roles are individuated according to computational criteria, and those on which functional roles (...) are individuated according to rational criteria. I then present an argument for a modest version of HEC from computational functionalism, based on Clark & Chalmers’ original argument. In doing so I articulate a successor to their parity principle, and review studies by Wayne Gray et al. that provide plausible evidence for actual cognitive extension. I then respond to a new criticism of HEC by Mark Sprevak using the modest account I have developed, arguing that Sprevak conflates HEC and HEM. (shrink)