We are responsible for some things but not for others. In this thesis, I investigate what it takes for an entity to be responsible for something. This question has two components: agents and actions. I argue for a permissive view about agents. Entities such as groups or artificially intelligent systems may be agents in the sense required for responsibility. With respect to actions, I argue for a causal view. The relation in virtue of which agents are responsible for actions is (...) a causal one. I claim that responsibility requires causation and I develop a causal account of agency. This account is particularly apt for addressing the relationship between agency and moral responsibility and sheds light on the causal foundations of moral responsibility. (shrink)

Psychology, according to a standard dictionary definition, is the science of mind and behavior. For a major part of the twentieth century, (nonhuman) animal psychology was on a behavioristic track that explicitly denied the possibility of a science of animal mind. While many comparative psychologists remain wedded to behavioristic methods, they have more recently adopted a cognitive, information-processing approach that does not adhere to the strictures of stimulus-response explanations of animal behavior. Cognitive ethologists are typically willing to go much further (...) than comparative psychologists by adopting folk-psychological terms to explain the behavior of nonhuman animals. This different attitudes of many scientists presupposes a distinction between cognitive and mental state attributions that is not commonly articulated. This paper seeks to understand that distinction. (shrink)

Most people find it obvious that concepts like APPLE, DOG, WATER, CACTUS, SWIM, CHIRP, FURRY, and SMOOTH are acquired from perceptual experiences along with some kind of inferential procedure. Models of how these concepts are inferentially acquired, however, force the acquired concepts to be representationally complex, built from, and composed by, the more primitive representations. Since at least the time of Plato, philosophers and psychologists have struggled to find complex sets of representations that have the same meanings, definitionally or probabilistically, (...) as these concepts. For example, to think about the property-kind being gold is not the same as to think about the complex property-kind being yellowish & shiny & malleable.... I call this Fodor's Challenge: Find an acquisition process that is genuinely inferential and yields a concept that genuinely is one of these lexical concepts. Rather than continue the pursuit of a complex representation that has the same meaning as our concept GOLD. I offer a model on which many lexical concepts are acquired from perception and inference, without being built up from, and composed by, the representations involved. The model, Baptizing Meanings for Concepts, is inspired in part by Saul Kripke's baptism process for assigning meanings to linguistic terms. Many lexical concepts, according to the BMC, are acquired by inferring the presence a new property-kind, picking out the property-kind in terms of those perceptible features, and then assigning a simple mental term, a concept, for that property-kind. (shrink)

The Frame Problem is the problem of how one can design a machine to use information so as to behave competently, with respect to the kinds of tasks a genuinely intelligent agent can reliably, effectively perform. I will argue that the way the Frame Problem is standardly interpreted, and so the strategies considered for attempting to solve it, must be updated. We must replace overly simplistic and reductionist assumptions with more sophisticated and plausible ones. In particular, the standard interpretation assumes (...) that mental processes are identical to certain kinds of computational processes, and so solving the Frame Problem is a matter of finding a computational architecture that can effectively represent relations of semantic relevance. Instead, we must take seriously the possibility that the way in which intelligent agents use information is inherently different. Whereas intelligent agents are plausibly genuinely causally sensitive to semantic properties as such (to what they perceive, desire, believe intend, etc.), computational systems can only be causally sensitive to the formal features that represent these properties. Indeed, it is this very substitution of formal generalizations for genuinely semantic ones that is responsible for the way current AI systems are brittle, inflexible, and highly specialized. What we need is a more sophisticated way of investigating the relationship between computational information processing and genuinely semantic information use, so that these two senses of using information are not conflated, but instead the question of how they are related to one another can be studied directly. I apply the generative methodology I have developed elsewhere for cognitive science and AI research (Miracchi, 2017, 2019a) to show how the Frame Problem can be appropriately updated. (shrink)

In this dissertation, I examine three philosophically important concepts that play a foundational role in developmental psychology: theory, representation, and belief. I describe different ways in which the concepts have been understood and present reasons why a developmental psychologist, or a philosopher attuned to cognitive development, should prefer one understanding of these concepts over another.

In the aftermath of a normalized Foucaultian world with an all encompassing web of biopower, one remaining hope is to cultivate nimbleness. Nimbleness is an embodied aesthetic sensitivity to the material presence. Cultivating nimbleness is a particular style of cultivation; it is to willfully gather together one’s self in the wake of a formative force far richer than the derivative web of living power relationships of human embeddness within a horizon of social, economical, political and historical subjectivating power relations; which (...) are chronicled and labeled by Michel Foucault as the normalizing practices of biopower. In other words to have freedom, one must start by rejecting the categories and labels normally internalized in order to relearn to learn from the material presence. Such a style of cultivation is a means of resisting normalizing power relations which co-opt cultivating practices to engross their own dominance which has had the by-product of an impotence to negate the gross material injustices present. This normalizing style of cultivation is a prevalent, corrupted, semblance which denies the importance of beauty for that of efficiency, rejects non-human purposiveness, and limits its measure of ethics to short term economical pragmatism. The thesis acknowledges that something is awry with the world and that giving care to beauty might help. The aim is to examine the event of Beauty as depicted by the philosopher Immanuel Kant and to apply this characterization to elective architectural spaces such that it may motivate individuals to cultivate their own nimbleness in relation to a formative force of nature. However given the revealed need for sensitivity to the particular material presence, the thesis can not be a rule book or catalog for beautiful design. Rather it is a rehabilitation for architects who are already heterospatially curious, with the desired outcome of architects cultivating their own nimbleness to reflectively judge as a ground up, multi-node, rhizomatic means of resistance to normalizing power practices as manifest in bad architecture. (shrink)

O debate entre J. Searle e D. Dennett acerca da possibilidade técnica de uma Inteligência artificial gira em torno de uma única questão: estados mentais expressam algo intrínseco, privado e subjetivo, experimentado em primeira-pessoa ou não passam de entidades obscurantistas, frutos da ignorância e, em princípio, reduzíveis à objetividade científica da neurociência? Searle defende a primeira tese, enquanto Dennett argumenta pela segunda. O texto expõe a posição de Dennett, a crítica de Searle e se direciona para uma nova solução, que (...) defende um monismo integral, no qual mente e cérebro podem ser vistos como duas dimensões de uma mesma realidade. Nesse sentido, o projeto de Inteligência artifical precisará revisar o conceito de “físico” se quiser avançar em suas pretenções, incluindo nele conceitos hoje antagônicos como intencionalidade, liberdade e subjetividade.The debate between J. Searle and D. Dennett about the technical possibility of an artificial intelligence revolves around a single issue: mental states express something intrinsic, private and subjective, experienced in first-person or are merely obscurantist entities, results from ignorance and, in principle, reducible to scientific objectivity of neuroscience? Searle argues for the first position, while Dennett argues for the second. The text exposes the position of Dennett, the criticism of Searle and is directed to a new solution, which advocates an integral monism, in which mind and brain can be seen as two dimensions of the same reality. In this sense, the project of artificial intelligence need to review the concept of "physical" if it wants to advance its claims, including today antagonistic concepts such as intentionality, freedom and subjectivity. (shrink)

The journal of Cognitive Computation is defined in part by the notion that biologically inspired computational accounts are at the heart of cognitive processes in both natural and artificial systems. Many studies of various important aspects of cognition (memory, observational learning, decision making, reward prediction learning, attention control, etc.) have been made by modelling the various experimental results using ever-more sophisticated computer programs. In this manner progressive inroads have been made into gaining a better understanding of the many components of (...) cognition. Concomitantly in both science and science fiction the hope is periodically re-ignited that a manmade system can be engineered to be fully cognitive and conscious purely in virtue of its execution of an appropriate computer program. However, whilst the usefulness of the computational metaphor in many areas of psychology and neuroscience is clear, it has not gone unchallenged and in this article I will review a group of philosophical arguments that suggest either such unequivocal optimism in computationalism is misplaced—computation is neither necessary nor sufficient for cognition—or panpsychism (the belief that the physical universe is fundamentally composed of elements each of which is conscious) is true. I conclude by highlighting an alternative metaphor for cognitive processes based on communication and interaction. (shrink)

For a long time, philosophers have considered the conundrums of consciousness, self-awareness and free will. Much more recently, scientists have joined in and begun to unravel the secrets of mind. Biologists, physicians and psychologists, studying the human brain, but also physicists, engineers, and computer scientists, working on organizational principles of intelligent information processing systems, have contributed to the subject. This contribution explains several “roads to self-awareness”, all of them based on the natural sciences. The first one follows our bio-psychological evolution. (...) The second road starts with the engineer’s point of view and mainly builds on information science and technology, in particular robotics. The third road taken is the most abstract; it exploits complex dynamic systems and their emergent properties. Despite their different origins and methods, these lines of investigation converge. That is, the findings of various fields can be combined into a unified theory of mind and self-awareness, which is the main purpose of this paper. This overall synthesis suggests that the mind results from a multi-hierarchical organizational structure, and self-reflexive flows of information in embodied systems. In addition to this, stable self-awareness appears spontaneously in sufficiently complex robots, when the system’s capability of describing itself crosses the level of conceptually clear information processing. As an application, one obtains a number of construction principles for mentally developing systems that are explained towards the end of this contribution. (shrink)

This thesis introduces certain aspects in the thought of Dallas Willard and Edmund Husserl as a new way forward in the internalism externalism debate. Husserl’s detailed analysis of cognition has application to epistemology and addresses in great depth an area which in the current discussion is often tertiary and shallow at best. It is argued that in both internalist and externalist camps there is a common assumption about cognition which Husserl argues forcibly against. This assumption is that thought, or cognition, (...) is essentially linguistic. Whatever else thinking may be, when we do it we do it in or with language. This assumption about thought means that whatever justification may be it is linguistic. This thesis holds that the rejecting of this assumption is critical to advancing the discussion past the current stalemate. (shrink)

Abstract Many anticipatory systems cannot in themselves act meaningfully or represent intentionally. This stems largely from the derivative nature of their functionality. All current artificial control systems, and many living systems such as organs and cellular parts of organisms derive any intentionality they might have from their designers or possessors. Derivative functionality requires reference to some external autonomously functional system, and derivative intentionality similarly requires reference to an external autonomous intentional system. The importance of autonomy can be summed up in (...) the following slogan: No meaning without intention; no intention without function; no function without autonomy. This paper develops the role of autonomy to show how learning new tasks is facilitated by autonomy, and further by representational capacities that are functional for autonomy. (shrink)

Charles Siewert presents a series of thought experiment based arguments against a wide range of current theories of phenomenal consciousness which I believe achieves a considerable measure of success. One topic which I think gets insufficient attention is the discussion of functionalism and I address this here. Before that I consider the intriguing issue, which is seldom considered but figures prominently at the close of Siewert's book, of the value of consciousness. In particular, I broach the question of whether the (...) value of consciousness has any impact on our theoretical understanding of consciousness. (shrink)

Philosophical questions about minds and computation need to focus squarely on the mathematical theory of Turing machines (TM's). Surrogate TM's such as computers or formal systems lack abilities that make Turing machines promising candidates for possessors of minds. Computers are only universal Turing machines (UTM's)—a conspicuous but unrepresentative subclass of TM. Formal systems are only static TM's, which do not receive inputs from external sources. The theory of TM computation clearly exposes the failings of two prominent critiques, Searle's Chinese room (...) (1980) and arguments from Gödel's Incompleteness theorems (e.g., Lucas, 1961; Penrose, 1989), both of which fall short of addressing the complete TM model. Both UTM-computers and formal systems provide an unsound basis for debate. In particular, their special natures easily foster the misconception that computation entails intrinsically meaningless symbol manipulation. This common view is incorrect with respect to full-fledged TM's, which can process inputs non-formally, i.e., in a subjective and dynamically evolving fashion. To avoid a distorted understanding of the theory of computation, philosophical judgments and discussions should be grounded firmly upon the complete Turing machine model, the proper model for real computers. (shrink)

Framed within the dialectic of the causal exclusion argument (Kim 2005), this paper does two things. One, it clarifies some properties of multiple realizability based on its true origin (Turing 1950). And two, it challenges a form of argument Noordhof (1997), Clarke (1999), and Whittle (2007) employ to support the idea that the mental has causal powers not had by its physical realization base (Novel). The paper challenges Novel with ideas derived from multiple realizability, among others.

For many years now, Harnad has argued that transduction is special among cognitive capacities -- special enough to block Searle's Chinese Room Argument. His arguments (as well as Searle's) have been important and useful, but not correct, it seems to me. Their arguments have provided the modern impetus for getting clear about computationalism and the nature of computing. This task has proven to be quite difficult. Which is simply to say that dealing with Harnad's arguments (as well as Searle's) has (...) been difficult. Turing, it turns out, only got us started. But Harnad's (and Searle's) arguments ultimately fail. Turing, it turns out, was on the right track. (shrink)

One of the strands of the Transhumanist movement, Singulitarianism, studies the possibility that high-level artificial intelligence may be created in the future, debating ways to ensure that the interaction between human society and advanced artificial intelligence can occur safely and beneficially. But how can we guarantee this safe interaction? Are there any indications that a Singularity may be on the horizon? In trying to answer these questions, We'll make a small introduction to the area of security research in artificial intelligence. (...) We'll review some of the current paradigms in the development of autonomous intelligent systems and evidence that we can use to prospect the coming of a possible technological Singularity. Finally, we will present a reflection using the COVID-19 pandemic, something that showed that our biggest problem in managing existential risks is our lack of coordination skills as a global society. (shrink)

The Turing Test (TT), the Chinese Room Argument (CRA), and the Symbol Grounding Problem (SGP) are about the question “can machines think?” We propose to look at these approaches to Artificial Intelligence (AI) by showing that they all address the possibility for Artificial Agents (AAs) to generate meaningful information (meanings) as we humans do. The initial question about thinking machines is then reformulated into “can AAs generate meanings like humans do?” We correspondingly present the TT, the CRA and the SGP (...) as being about generation of human-like meanings. We model and address such possibility by using the Meaning Generator System (MGS) where a system submitted to an internal constraint generates a meaning in order to satisfy the constraint. The system approach of the MGS allows comparing meaning generations in animals, humans and AAs. The comparison shows that in order to have AAs capable of generating human-like meanings, we need the AAs to carry human constraints. And transferring human constraints to AAs raises concerns coming from the unknown natures of life and human mind which are at the root of human constraints. Implications for the TT, the CRA and the SGP are highlighted. It is shown that designing AAs capable of thinking like humans needs an understanding about the natures of life and human mind that we do not have today. Following an evolutionary approach, we propose as a first entry point an investigation about the possibility for extending a “stay alive” constraint into AAs. Ethical concerns are raised from the relations between human constraints and human values. Continuations are proposed. (This paper is an extended version of the proceedings of an AISB/IACAP 2012 presentation). (shrink)

The dialogue develops arguments for and against a broad new world system - info-computationalist naturalism - that is supposed to overcome the traditional mechanistic view. It would make the older mechanistic view into a special case of the new general info-computationalist framework (rather like Euclidian geometry remains valid inside a broader notion of geometry). We primarily discuss what the info-computational paradigm would mean, especially its pancomputationalist component. This includes the requirements for a the new generalized notion of computing that would (...) include sub-symbolic information processing. We investigate whether pancomputationalism can provide the basic causal structure to the world and whether the overall research program of info-computationalist naturalism appears productive, especially when it comes to new approaches to the living world, including computationalism in the philosophy of mind. (shrink)

Jotta olisimme moraalisesti vastuussa teoistamme, meidän on kyettävä muodostamaan käsityksiä oikeasta ja väärästä ja toimimaan ainakin jossain määrin niiden mukaisesti. Jos olemme täysivaltaisia moraalitoimijoita, myös ymmärrämme miksi jotkin teot ovat väärin, ja kykenemme siten joustavasti mukauttamaan toimintaamme eri tilanteisiin. Esitän, ettei näköpiirissä ole tekoälyjärjestelmiä, jotka kykenisivät aidosti välittämään oikein tekemisestä tai ymmärtämään moraalin vaatimuksia, koska nämä kyvyt vaativat kokemustietoisuutta ja kokonaisvaltaista arvostelukykyä. Emme siten voi sysätä koneille vastuuta teoistaan. Meidän on sen sijaan pyrittävä rakentamaan keinotekoisia oikeintekijöitä - järjestelmiä, jotka eivät (...) ole moraalitoimijoita, mutta kuitenkin toimivat likipitäen siten kuin me itse parhaimmillamme tekisimme. (shrink)

This article reviews eight proposed strategies for solving the Symbol Grounding Problem (SGP), which was given its classic formulation in Harnad (1990). After a concise introduction, we provide an analysis of the requirement that must be satisfied by any hypothesis seeking to solve the SGP, the zero semantical commitment condition. We then use it to assess the eight strategies, which are organised into three main approaches: representationalism, semi-representationalism and non-representationalism. The conclusion is that all the strategies are semantically committed and (...) hence that none of them provides a valid solution to the SGP, which remains an open problem. (shrink)

The question, “What is intelligence?” is deceptively simple. However, scholars have engaged in series of research in order to answer it. Till date there is no simple answer accepted by experts in the relevant disciplines. Attempt to identify a standard definition has been very challenging. This failure is connected with the fact that defining intelligence requires the application of problematic and abstract concepts. Consequently, some researchers decided to put forward theories as an attempt to capture the nature of intelligence. However, (...) this option, as reflected in this paper, further deepens the problem it purports to resolve. The paper is an inquest into the intellectual travails of scholars who fruitlessly attempted to grasp the nature of intelligence. The paper avers that these travails are caused by scholar’s reliance on ontological proof of intelligence which stipulates the possession of brain and mind as evidence of intelligence. The epistemological proof which relies on overt behaviour as index of interpreting intelligence is projected by the paper as a plausible means of overcoming the nebulous nature of the concept. -/- . (shrink)

Information and meaning exist around us and within ourselves, and the same information can correspond to different meanings. This is true for humans and animals, and is becoming true for robots. We propose here an overview of this subject by using a systemic tool related to meaning generation that has already been published (C. Menant, Entropy 2003). The Meaning Generator System (MGS) is a system submitted to a constraint that generates a meaningful information when it receives an incident information that (...) has a relation with the constraint. The content of the meaningful information is explicited, and its function is to trigger an action that will be used to satisfy the constraint of the system. The MGS has been introduced in the case of basic life submitted to a "stay alive" constraint. We propose here to see how the usage of the MGS can be extended to more complex living systems, to humans and to robots by introducing new types of constraints, and integrating the MGS into higher level systems. The application of the MGS to humans is partly based on a scenario relative to the evolution of body self-awareness toward self-consciousness that has already been presented (C. Menant, Biosemiotics 2003, and TSC 2004). The application of the MGS to robots is based on the definition of the MGS applied to robots functionality, taking into account the origins of the constraints. We conclude with a summary of this overview and with themes that can be linked to this systemic approach on meaning generation. (shrink)

Myšlenkové experimenty jsou populárním argumentačním nástrojem ve vědě i filosofii. Jejich kritika ze strany naturalistických a experimentálních filosofů vedla k vytvoření deflačních a minimalistických koncepcí, které oslabují epistemickou sílu myšlenkových experimentů a smiřují je s empirismem. Cílem článku je ukázat, že tyto pokusy nepřekonávají hlavní problémy, se kterými se myšlenkové experimenty ve filosofii střetávají. Omezená lidská racionalita a představivost znemožňují experimentátorům řešit nereálné scénáře spolehlivým způsobem. Myšlenkové experimenty se ve filosofii používají jinak než ve vědě, protože ty pravé jsou obvykle (...) neuskutečnitelné a uzavřené vůči možnosti empirické falsifikace. Navíc jsou založeny na vadných analogiích a neoprávněně přenášejí důkazní břemeno. Persvazivní úspěšnost myšlenkových experimentů je velmi nízká, a proto nedokáží přispět k řešení filosofických problémů. Závěrem článku je, že nejběžnější druhy myšlenkových experimentů by měly být odstraněny ze souboru filosofických metod. (shrink)

Of primary importance in formulating a response to the increasing prevalence and power of artificial intelligence (AI) applications in society are questions of ontology. Questions such as: What “are” these systems? How are they to be regarded? How does an algorithm come to be regarded as an agent? We discuss three factors which hinder discussion and obscure attempts to form a clear ontology of AI: (1) the various and evolving definitions of AI, (2) the tendency for pre-existing technologies to be (...) assimilated and regarded as “normal,” and (3) the tendency of human beings to anthropomorphize. This list is not intended as exhaustive, nor is it seen to preclude entirely a clear ontology, however, these challenges are a necessary set of topics for consideration. Each of these factors is seen to present a 'moving target' for discussion, which poses a challenge for both technical specialists and non-practitioners of AI systems development (e.g., philosophers and theologians) to speak meaningfully given that the corpus of AI structures and capabilities evolves at a rapid pace. Finally, we present avenues for moving forward, including opportunities for collaborative synthesis for scholars in philosophy and science. (shrink)

This paper investigates how the simulation of intelligence, an activity that has been considered the notional task of Artificial Intelligence, does not comprise its duplication. Briefly touching on the distinction between conceivability and possibility, and commenting on Ryan’s approach to fiction in terms of the interplay between possible worlds and her principle of minimal departure, we specify verisimilitude in Artificial Intelligence as the accurate resemblance of intelligence by its simulation and, from this characterization, claim the metaphysical impossibility of duplicating intelligence, (...) as neither verisimilarly nor convincingly simulating intelligence involves its duplication. To this end, we argue by a representative case of simulation that, albeit conceivable, Turing’s test for machine intelligence wrongly equates the occurrence of indistinguishable intelligence performance to intelligence duplication, which is grounded in a prima facie conceivable but metaphysically impossible view that separates intelligence from its origin. Finally, we establish the following criterion for evaluating simulation in Artificial Intelligence: simulations succeed in AI if and only if they are able to epistemically persuade human beings that intelligence has been duplicated, that is, if and only if verisimilar simulations can convincingly minimally depart from actual intelligence. (shrink)

Computationalism provides a framework for understanding how a mathematically describable physical world could give rise to conscious observations without the need for dualism. A criterion is proposed for the implementation of computations by physical systems, which has been a problem for computationalism. Together with an independence criterion for implementations this would allow, in principle, prediction of probabilities for various observations based on counting implementations. Applied to quantum mechanics, this results in a Many Computations Interpretation (MCI), which is an explicit form (...) of the Everett style Many Worlds Interpretation (MWI). Derivation of the Born Rule emerges as the central problem for most realist interpretations of quantum mechanics. If the Born Rule is derived based on computationalism and the wavefunction it would provide strong support for the MWI; but if the Born Rule is shown not to follow from these to an experimentally falsified extent, it would indicate the necessity for either new physics or (more radically) new philosophy of mind. (shrink)

The main trends underlying advancements in AI technology are increased autonomy, increased functionality, higher level social interaction and integration, and, many suggest, hard-wired ethical codes of conduct. These trends, along with the promises of engineers and scientists, give us ample reason to evaluate the agency of future AI machines.

We frame the question of what kind of subjective experience a brain simulation would have in contrast to a biological brain. We discuss the brain prosthesis thought experiment. Then, we identify finer questions relating to the original inquiry, and set out to answer them moving forward from both a general physicalist perspective, and pan-experientialism. We propose that the brain simulation is likely to have subjective experience, however, it may differ significantly from human experience. Additionally, we discuss the relevance of quantum (...) properties, digital physics, theory of relativity, and information theory to the question. (shrink)

The concept of morality underpins the moral responsibility that not only depends on the outward practices (or ‘output’, in the case of humanoid robots) of the agents but on the internal attitudes (‘input’) that rational and responsible intentioned beings generate. The primary question that has initiated extensive debate, i.e. ‘Can humanoid robots be moral?’, stems from the normative outlook where morality includes human conscience and socio-linguistic background. This paper advances the thesis that the conceptions of morality and creativity interplay with (...) linguistic human beings instead of non-linguistic humanoid robots, as humanoid robots are indeed docile automata that cannot be responsible for their actions. To eradicate human ethics in order to make way for humanoid robot ethics highlights the moral actions and adequacy that hinges the myth of creative agency and self-dependency, which a humanoid robot can scarcely express. (shrink)

The use of thought experiments seems to provoke much controversy, often in the form of charges of appeals to intuition. The notion of intuition, however, is vaguely defined in both the context of thought experiments and in philosophy in general. This vagueness suggests that the description of thought experiments is incomplete, and thus the prospect for their evaluation remains unfulfilled. Previous analyses of thought experiments have come largely from philosophy where the focus has been on truth value and validity. But (...) these approaches seem to view argument monologically; no accommodation of an audience response like intuition is possible. I try to show that van Eemeren and Grootendorst's pragma-dialectical model provides a framework for analyzing thought experiments and evaluating them because it treats thought experiments as part of a dialogue and as the result of a perspective. (shrink)