The comment addresses central issues of a "theory theory" approach as exemplified in Gopnik' and Goldman's BBS-articles. Gopnik, on the one hand, tries to demonstrate that empirical evidence from developmental psychology supports the view of a "theory theory" in which common sense beliefs are constructed to explain ourselves and others. Focusing the informational processing routes possibly involved we would like to argue that his main thesis (e.g. idea of intentionality as a cognitive construct) lacks support at least for two reasons: (...) one methodological and one structural. On the other hand, Goldman raises an important question when he is asking how people ascribe mental states to themselves. Reasons why Goldman's attempt to understand common sense mental representations by using an analogy from visual perception is problematic are discussed. The role which is attributed to a phenomenology is evaluated. (shrink)

Motivated by the question of responsible AI and value alignment, I seek to offer a uniquely Foucauldian reconstruction of the problem as the emergence of an ethical subject in a disciplinary setting. This reconstruction contrasts with the strictly human-oriented programme typical to current scholarship that often views technology in instrumental terms. With this in mind, I problematise the concept of a technological subjectivity through an exploration of various aspects of ChatGPT in light of Foucault’s work, arguing that current systems lack (...) the reflexivity and self-formative characteristics inherent in the notion of the subject. By drawing upon a recent dialogue between Foucault and phenomenology, I suggest four techno-philosophical desiderata that would address the gaps in this search for a technological subjectivity: embodied self-care, embodied intentionality, imagination and reflexivity. Thus I propose that advanced AI be reconceptualised as a subject capable of “technical” self-crafting and reflexive self-conduct, opening new pathways to grasp the intertwinement of the human and the artificial. This reconceptualization holds the potential to render future AI technology more transparent and responsible in the circulation of knowledge, care and power. (shrink)

International Journal of Machine Consciousness, Volume 06, Issue 02, Page 141-161, December 2014. This paper follows directly from an earlier paper where we discussed the requirements for an artifact to be a moral agent and concluded that the artifactual question is ultimately a red herring. As before, we take moral agency to be that condition in which an agent can appropriately be held responsible for her actions and their consequences. We set a number of stringent conditions on moral agency. A (...) moral agent must be embedded in a cultural and specifically moral context and embodied in a suitable physical form. It must be, in some substantive sense, alive. It must exhibit self-conscious awareness. It must exhibit sophisticated conceptual abilities, going well beyond what the likely majority of conceptual agents possess: not least that it must possess a well-developed moral space of reasons. Finally, it must be able to communicate its moral agency through some system of signs: A "private" moral world is not enough. After reviewing these conditions and pouring cold water on recent claims for having achieved "minimal" machine consciousness, we turn our attention to a number of existing and, in some cases, commonplace artifacts that lack moral agency yet nevertheless require one to take a moral stance toward them, as if they were moral agents. Finally, we address another class of agents raising a related set of issues: autonomous military robots. (shrink)

What happens when machines become more intelligent than humans? One view is that this event will be followed by an explosion to ever-greater levels of intelligence, as each generation of machines creates more intelligent machines in turn. This intelligence explosion is now often known as the “singularity”. The basic argument here was set out by the statistician I.J. Good in his 1965 article “Speculations Concerning the First Ultraintelligent Machine”: Let an ultraintelligent machine be defined as a machine that can far (...) surpass all the intellectual activities of any man however clever. Since the design of machines is one of these intellectual activities, an ultraintelligent machine could design even better machines; there would then unquestionably be an “intelligence explosion”, and the intelligence of man would be left far behind. Thus the first ultraintelligent machine is the last invention that man need ever make. The key idea is that a machine that is more intelligent than humans will be better than humans at designing machines. So it will be capable of designing a machine more intelligent than the most intelligent machine that humans can design. So if it is itself designed by humans, it will be capable of designing a machine more intelligent than itself. By similar reasoning, this next machine will also be capable of designing a machine more intelligent than itself. If every machine in turn does what it is capable of, we should expect a sequence of ever more intelligent machines. This intelligence explosion is sometimes combined with another idea, which we might call the “speed explosion”. The argument for a speed explosion starts from the familiar observation that computer processing speed doubles at regular intervals. Suppose that speed doubles every two years and will do so indefinitely. Now suppose that we have human-level artificial intelligence 1 designing new processors. Then faster processing will lead to faster designers and an ever-faster design cycle, leading to a limit point soon afterwards. The argument for a speed explosion was set out by the artificial intelligence researcher Ray Solomonoff in his 1985 article “The Time Scale of Artificial Intelligence”.1 Eliezer Yudkowsky gives a succinct version of the argument in his 1996 article “Staring at the Singularity”: “Computing speed doubles every two subjective years of work.. (shrink)

The posterior parietal cortex (PPC) is the most likely site where egocentric spatial relationships are represented in the brain. PPC cells receive visual, auditory, somaesthetic, and vestibular sensory inputs; oculomotor, head, limb, and body motor signals; and strong motivational projections from the limbic system. Their discharge increases not only when an animal moves towards a sensory target, but also when it directs its attention to it. PPC lesions have the opposite effect: sensory inattention and neglect. The PPC does not seem (...) to contain a “map” of the location of objects in space but a distributed neural network for transforming one set of sensory vectors into other sensory reference frames or into various motor coordinate systems. Which set of transformation rules is used probably depends on attention, which selectively enhances the synapses needed for making a particular sensory comparison or aiming a particular movement. (shrink)

Despite facing significant criticism for assigning human-like characteristics to artificial intelligence, phrases like “trustworthy AI” are still commonly used in official documents and ethical guidelines. It is essential to consider why institutions continue to use these phrases, even though they are controversial. This article critically evaluates various reasons for using these terms, including ontological, legal, communicative, and psychological arguments. All these justifications share the common feature of trying to justify the official use of terms like “trustworthy AI” by appealing to (...) the need to reflect pre-existing facts, be it the ontological status, ways of representing AI or legal categories. The article challenges the justifications for these linguistic practices observed in the field of AI ethics and AI science communication. In particular, it takes aim at two main arguments. The first is the notion that ethical discourse can move forward without the need for philosophical clarification, bypassing existing debates. The second justification argues that it’s acceptable to use anthropomorphic terms because they are consistent with the common concepts of AI held by non-experts—exaggerating this time the existing evidence and ignoring the possibility that folk beliefs about AI are not consistent and come closer to semi-propositional beliefs. The article sounds a strong warning against the use of human-centric language when discussing AI, both in terms of principle and the potential consequences. It argues that the use of such terminology risks shaping public opinion in ways that could have negative outcomes. (shrink)

CRS says that the meanings of expressions of a language or other symbol system or the contents of mental states are determined and explained by the way symbols are used in thinking. According to CRS one.

There are different ways to present a Presidential Address to the APA; the one I have chosen is simply to report on work that I am doing right now, on work in progress. I am going to present some of my further explorations into the computational model of the mind.\**.

Who Needs Stories if You Can Get the Data? ISPs in the Era of Big Number Crunching Content Type Journal Article Category Special Issue Pages 371-390 DOI 10.1007/s13347-011-0041-8 Authors Mireille Hildebrandt, Institute of Computer and Information Sciences (ICIS), Radboud University Nijmegen, Nijmegen, the Netherlands Journal Philosophy & Technology Online ISSN 2210-5441 Print ISSN 2210-5433 Journal Volume Volume 24 Journal Issue Volume 24, Number 4.

The central mission of cognitive science is to reveal the real nature of the mind, however familiar or foreign that nature may be to naive preconceptions. The existence of naive conceptions is also important, however. Prescientific thought and language contain concepts of the mental, and these concepts deserve attention from cognitive science. Just as scientific psychology studies folk physics (McCloskey 1983, Hayes 1985), viz., the common understanding (or misunderstanding) of physical phenomena, so it must study folk psychology, the common understanding (...) of mental states. This subfield of scientific psychology is what I mean by the phrase 'the psychology of folk psychology'. (shrink)

Conceivability arguments constitute a serious threat against reductive physicalism. Recently, a number of authors have proven and characterized a devastating logical truth centered on these arguments: namely, that their soundness entails the inconceivability of reductive physicalism. In this paper, I demonstrate that this is only a logical truth when reductive physicalism is interpreted in its stronger, intrinsic sense, as opposed to its weaker—yet considerably more popular—extrinsic sense. The basic idea generalizes: perhaps surprisingly, stronger forms of reduction are uniquely resistant to (...) the conceivability arguments opposing them. So far as the modal epistemology of reduction is concerned, therefore, it pays to go intrinsic. (shrink)

Artificial intelligence, the "science and engineering of intelligent machines", still has yet to create even a simple "Advice Taker" [McCarthy, 1959]. We have previously argued [Waser, 2011] that this is because researchers are focused on problem-solving or the rigorous analysis of intelligence (or arguments about consciousness) rather than the creation of a "self" that can "learn" to be intelligent. Therefore, following expert advice on the nature of self [Llinas, 2001; Hofstadter, 2007; Damasio, 2010], we embarked upon an effort to design (...) and implement a self-understanding, self-improving loop as the totality of a (seed) AI. As part of that, we decided to follow up on Richard Dawkins' [1976] speculation that "perhaps consciousness arises when the brain's simulation of the world becomes so complete that it must include a model of itself" by defining a number of axioms and following them through to their logical conclusions. The results combined with an enactive approach yielded many surprising and useful implications for further understanding consciousness, self, and "free-will" that continue to pave the way towards the creation of safe/moral autopoiesis. (shrink)

Some of the papers in this special issue distribute cognition between what is going on inside individual cognizers' heads and their outside worlds; others distribute cognition among different individual cognizers. Turing's criterion for cognition was individual, autonomous input/output capacity. It is not clear that distributed cognition could pass the Turing Test.

The concept of narrow content is still under discussion in the debate over mental representation. In the paper, one-factor dimensional accounts of representation are analyzed, particularly the case of Fodor's methodological solipsism. In methodological solipsism, semantic properties of content are arguably eliminated in favor of syntactic ones. If “narrow content” means content properties independent of external factors to a system (as in Segal's view), the concept of content becomes elusive. Moreover, important conceptual problems with one-factor dimensional account are pointed out (...) as a result of analysis arguments presented by J. Searle, S. Harnad and T. Burge. Furthermore, these problems are illustrated with psychological and ethological examples. Although understanding content as partially independent from contextual factors allows theorists to preserve content properties, it seems that understanding content in total abstraction from external factors of these properties is implausible. As a result, internalism is rejected in favor of externalism. (shrink)

Representationalists argue that phenomenal states are intentional states of a special kind. This paper offers an account of the kind of intentional state phenomenal states are: I argue that they are underived intentional states. This account of phenomenal states is equivalent to two theses: first, all possible phenomenal states are underived intentional states; second, all possible underived intentional states are phenomenal states. I clarify these claims and argue for each of them. I also address objections which touch on a range (...) of topics, including meaning holism and concept empiricism. I conclude with a brief discussion of the consequences of the proposed view for the project of naturalizing consciousness. (shrink)

The future rests under the sign of technology. Given the prevalence of technological neutrality and inevitabilism, most conceptualizations of the future tend to ignore moral problems. In this paper we argue that every choice about future technologies is a moral choice and even the most technology-dominated scenarios of the future are, in fact, moral provocations we have to imagine solutions to. We begin by explaining the intricate connection between morality and the future. After a short excursion into the history of (...) Artificial Intelligence, we analyse two possible scenarios, which show that building the future with technology is, first and foremost, a moral endeavor. (shrink)

This paper addresses two methodological paths in Artificial Intelligence: the paths of Babbage and anti-Cartesianism. While those researchers who have followed the latter have attempted to reverse the Cartesian dictum according to which machines cannot think in principle, Babbage’s path, which has been partially neglected, implies that the replacement of humans—and not the creation of minds—should provide the foundation of AI. In view of the examined paths, the claim that we support here is this: in line with Babbage, AI researchers (...) have recently concentrated upon the replacement of human labour, and thus upon the creation of Machine Learning systems. After presenting and analysing the paths, we characterise Machine Learning via its developments and an illustrative example. Then, we put forward an argument that shows that total replacement of human labour will not be feasible for practical and conceptual reasons despite the successful developments in recent AI systems. Our discussion finally leads to optimism and awareness: AI’s advances allow humans to dedicate themselves to higher level tasks, but these advances also require that we be vigilant about the responsibilities granted to ML-based systems. (shrink)

According to David Chalmers, the hard problem of consciousness consists of explaining how and why qualitative experience arises from physical states. Moreover, Chalmers argues that materialist and reductive explanations of mentality are incapable of addressing the hard problem. In this chapter, I suggest that Chalmers’ hard problem can be usefully distinguished into a ‘how question’ and ‘why question,’ and I argue that evolutionary biology has the resources to address the question of why qualitative experience arises from brain states. From this (...) perspective, I discuss the different kinds of evolutionary explanations (e.g., adaptationist, exaptationist, spandrel) that can explain the origins of the qualitative aspects of various conscious states. This argument is intended to clarify which parts of Chalmers’ hard problem are amenable to scientific analysis. (shrink)

In his article “If Loud Aliens Explain Human Earliness, Quiet Aliens are also Rare”, Robin Hanson proposes the Grabby Alien Hypothesis, which proposes that extraterrestrial civilizations (ETIs) exist outside of our observable universe and are gradually expanding to fill the universe. The existence of such grabby aliens in our future expanding to fill all available niches puts a cosmic deadline on independently originating sources of life. This cosmic cutoff offers an explanation for why human observers seem to be relatively early (...) in spacetime, why the red dwarf stars seem to be inadequate for independently originating life, and why the Fermi Paradox remains unsolved. However, we should worry about Hanson’s proposal, since the Grabby Alien Hypothesis has its own paradoxical implication, namely that most observers in most reference classes should be grabby aliens themselves (Bostrom, 2002). Thus, oddly, finding ourselves not to be grabby alien observers, it seems Hanson is beholden to explain why we are not. Some possibilities for grabby alien observer alternatives can be offered, though none are particularly explanatorily appealing. In what follows, we will 1) attempt to restate in simple terms Hanson’s assumptions, and then 2) reassemble Hanson’s arguments, showing they lead to a paradox, and 3) consider which assumptions should be rejected and at what cost. (shrink)

This paper follows directly from an earlier paper where we discussed the requirements for an artifact to be a moral agent and concluded that the artifactual question is ultimately a red herring. As...

Connectionism seems to avoid many of the problems of classical artificial intelligence, but has it avoided all of them? In this thesis I examine the problem that Intentionality, the directedness of thought to an object, raises for connectionism. As a preliminary approach, I consider the role of Intentionality in classical artificial intelligence from the programmer’s point of view. In this investigation, one problem I identify with classical artificial intelligence is that the Intentionality of the programmer seems to be projected onto (...) the system, rather than the programmer creating a system whereby Intentionality arises intrinsically within the system. -/- In considering the current practice of connectionism, the same problem with Intentionality reappears. The assignment of Intentional content to input or output nodes in a neural network likewise projects the Intentionality of the programmer onto the system, and that projection is often reinforced by the training process of the neural network. However, connectionism seems to have an advantage over classical artificial intelligence in this respect, in that there is a form of neural network in which the network itself organizes the output nodes. The challenge is to utilize these self-organizing networks without having the programmer project Intentionality onto the system in an act of interpretation. -/- I suggest that the way to overcome these problems in connectionism is to embody the neural network within a world, whether physical or virtual, and to allow the system to develop concepts purely empirically. In this manner, connectionism can make scientific observations concerning the nature of cognition without the risk of contamination from the programmer’s own Intentionality. (shrink)

In light of recent breakneck pace in machine learning, questions about whether near-future artificial systems might be conscious and possess moral status are increasingly pressing. This paper argues that as matters stand these debates lack any clear criteria for resolution via the science of consciousness. Instead, insofar as they are settled at all, it is likely to be via shifts in public attitudes brought about by the increasingly close relationships between humans and AI users. Section 1 of the paper I (...) briefly lays out the current state of the science of consciousness and its limitations insofar as these pertain to machine consciousness, and claims that there are no obvious consensus frameworks to inform public opinion on AI consciousness. Section 2 examines the rise of conversational chatbots or Social AI, and argues that in many cases, these elicit strong and sincere attributions of consciousness, mentality, and moral status from users, a trend likely to become more widespread. Section 3 presents an inconsistent triad for theories that attempt to link consciousness, behaviour, and moral status, noting that the trends in Social AI systems will likely make the inconsistency of these three premises more pressing. Finally, Section 4 presents some limited suggestions for how consciousness and AI research communities should respond to the gap between expert opinion and folk judgment. (shrink)

H.-J. Glock has made important contributions to discussions of rationality, reasons, and rules. This chapter addresses four conceptions of rationality that Glock identifies. One of these conceptions of rationality is that rationality consists in responsiveness to reasons. This chapter goes on to consider the idea that reasons became prominent in normative ethics because of their usefulness in articulating moral pluralism. The final section of the chapter connects reasons and rules and contends that both are ineliminable.

Many transhumanists see their respective movement as being rooted in ancient ethical thought. However, this alleged connection between the contemporary transhumanist doctrine and the ethical theory of antiquity has come under attack. In this paper, we defend this connection by pointing out a key similarity between the two intellectual traditions. Both traditions are committed to the “radical transformation thesis”: ancient ethical theory holds that we should assimilate ourselves to the gods as far as possible, and transhumanists hold that we should (...) enhance ourselves beyond the physical and intellectual parameters of being human so as to become posthuman. By considering the two views in tandem, we develop an account of the assimilation directive that is palatable to contemporary readers and provide a view of posthumanism worth wanting. (shrink)

In this position paper, we argue that careless reliance on AI to answer our questions and to judge our output is a violation of Grice’s Maxim of Quality as well as a violation of Lemoine’s legal Maxim of Innocence, performing an (unwarranted) authority fallacy, and while lacking assessment signals, committing Type II errors that result from fallacies of the inverse. What is missing in the focus on output and results of AI-generated and AI-evaluated content is, apart from paying proper tribute, (...) the demand to follow a person’s thought process (or a machine’s decision processes). In deliberately avoiding Neural Networks that cannot explain how they come to their conclusions, we introduce logic-symbolic inference to handle any possible epistemics any human or artificial information processor may have. Our system can deal with various belief systems and shows how decisions may differ for what is true, false, realistic, unrealistic, literal, or anomalous. As is, stota AI such as ChatGPT is a sorcerer’s apprentice. (shrink)

Tomando en cuenta las críticas más importantes a la teoría de los individuos transmundanos, así como algunos argumentos en relación con el esencialismo de origen, este artículo trata el problema de la identidad de aquellos individuos a través de mundos posibles. Proponemos la noción de mundo admisible como un tipo especial de modelo en Lógica Intensional, que, dentro de otro modelo, permite el mapeo de la historia e identidad de los individuos en diferentes mundos posibles. Esta propuesta sugiere una solución (...) plausible para determinar propiedades esenciales empíricamente relevantes ostentadas por los individuos transmundanos, un método eficaz para evaluar su identidad y, finalmente, una nueva perspectiva desde la cual reexaminar el clásico debate entre realismo y antirrealismo en la Filosofía del Lenguaje. (shrink)

Speech Acts, Criteria and Intentions What makes a speech act a speech act? Which are its necessary and sufficient conditions? I claim in this paper that we cannot find an answer to those questions in Austin's doctrine of the infelicities, since some infelicities take place in fully committing speech acts, whereas others prevent the utterance from being considered as a speech act at all. With this qualification in mind, I argue against the idea that intentions—considered as mental states accomplishing a (...) causal role in the performance of the act—should be considered among the necessary conditions of speech acts. I would thus like to deny a merely ‘symptomatic’ account of intentions, according to which we could never make anything but fallible hypotheses about the effective occurrence of any speech act. I propose an alternative ‘criterial’ account of the role of intentions in speech acts theory, and analyse Austin's and Searle's approaches in the light of this Wittgensteinian concept. Whether we consider, with Austin, that speech acts ‘imply’ mental states or, with Searle, that they ‘express’ them, we could only make sense of this idea if we considered utterances as criteria for intentions, and not as alleged behavioural effects of hidden mental causes. (shrink)

SUMMARY Major theories of philosophical psychology and philosophy of mind are examined on the basis of the fundamental questions of ontology, metaphysics, epistemology, semantics and logic. The result is the choice between language of eliminative reductionism and dualism, neither of which answers properly the relation between mind and body. In the search for a non–dualistic and non–reductive language, Wittgenstein’s notion of language–games as the representative links between language and the world is considered together with Peirce’s semeiosis of cognition. The result (...) is a redefined notion of cognition as the goal–oriented ability to instantiate strategies from the rules of the language–games. Cognition is considered within the four-dimensional languagegames: rules/strategies, primitive/complete language-games, family-resemblances/forms of life, and non-temporal continuum as the language-games’ modality. Cognition is seen as a continuum process of non–individualized elements that unites perception, volition, emotion, will and thought against the commonly accepted understandings of cognition in exclusive terms of perception and thinking. The alternative to the mind/body problem is the continuity of cognition where rules and strategies, syntax and semantics, are considered inseparable within language–games. This continuity of cognition is explained in terms of virtual (univocal) identity, replacing the old philosophical paradigm of the mind/body problem. -/- SOMMARIO Le teorie maggiori della psicologia filosofica e filosofia della mente sono esaminate a partire dalle questioni fondamentali di ontologia, metafisica, epistemologia, semantica e logica. Il risultato è la scelta tra un linguaggio riduzionista eliminativo e un dualismo che però non confronta in modo adeguato la relazione tra mente e corpo. Nella ricerca per un linguaggio non-dualistico e non-riduttivo, viene considerata la nozione del gioco linguistico di Wittgenstein come un legame rappresentativo tra il linguaggio e il mondo insieme con la semiosi cognitiva di Peirce. Il risultato è la nozione ridefinita della cognizione come abilità goal-orientata di creare le strategie dalle regole dei giochi linguistici. La cognizione è considerata entro le quattro dimensioni dei giochi linguistici: regole/strategie, giochi linguistici primitivi/completi, somiglianze di famiglia/forme di vita, e la continuità atemporale come la modalità dei giochi linguistici. La cognizione diventa un processo continuo degli elementi non-individualizzati che tende ad unificare la percezione, volizione, emozione, la volontà e il pensiero contro un concetto generalmente accettato di vedere la cognizione nei termini esclusivamente di percezione e di pensiero. L’alternativa al problema della mente/corpo è la continuità della cognizione, dove le regole e le strategie, la sintassi e la semantica, sono considerate inseparabili nei giochi linguistici. Questa continuità della cognizione è spiegata nei termini dell’identità virtuale (univoca) sostituendo un paradigma filosofico previo del problema della mente/corpo. (shrink)

Self-consciousness relates to important themes, such as sentience and personhood, and is often the cornerstone of moral theories (Warren, 1997). However, not much attention is given to future moral creatures of the earth: robots. This may be due to the unsettled status of their experience, which is why I have chosen to find the necessary features of self-consciousness in them. Philosophy of mind is also my interest which I have developed since I rejected the idea of souls and could not (...) account for my own phenomenal experiences. Among the current answers to the hard problem of consciousness (Chalmers, 1995) one stood out to me – Daniel Dennett’s multiple drafts model of consciousness presented in “Consciousness Explained” (Dennett, 1991) and his other works. Daniel Dennett is a self-described illusionist (Dennett, 2016) and a functionalist. His position is synonymous to holding self-conscious experiences, such as deliberating over one’s pain or reflecting over one’s actions insufficient to postulate existence of a metaphysical self. He believes instead that experiences are functional realizations which do not require any self, and the feeling of being conscious or self-conscious is actually a ”user-illusion” (Dennett, 1991), a term describing the unjustified belief of being in control of one’s actions. In his views, a selfhood as it is popularly conceived is contradictory. Therefore, he rejects realism about mental events, a position also called naïve realism (Siegel, 2011), on the basis that it is unverifiable and there are insufficient grounds to accept mental events (Dennett, 1988). He adopts a similar scepticism towards other theories of minds, hence nearing eliminative materialism in self-consciousness and related theme of pain (Dennett, 1978). His multiple drafts model of consciousness seeks to ground our beliefs about self-consciousness in the specific architecture of mind, which is particular to every species and kind of being. As such it is a particularly flexible theory that examines experiences of non-humans without falling into binary thinking – believing that a being has as rich inner life as humans do or none. This is why it is a great starting point for establishing necessary conditions for consciousness in robots. In this essay, I will often use words computer, programme, robot interchangeably for the purpose of clarity and take as the working definition “autonomous machines capable of sensing their environment, making decision and performing tasks similar to human actions”. I chose to explore self-consciousness instead of committing to the issue of consciousness, because consciousness can be defined in a weak sense, in which even a thermostat is “conscious” of the temperature, and consciousness in a strong sense, which invokes the internalism and externalism debate that is less connected to the nature of experiences than self-consciousness. My exploration pertains first and foremost to the philosophy of mind, of which I will examine the most relevant positions and decide to commit to functionalism (Block, 1980). Then I will advocate for explaining away of some of phenomena of self-consciousness and believing self-consciousness to be a sort of illusion. From there I will conclude that robots could fall for the same illusion of self-consciousness and therefore become self-conscious. I will argue, that self-consciousness can be established using a modified Turing Test, which would determine if a robot believed in a meaningful narrative about itself (Ricoeur, 1991) and hence be self-conscious. This will lead to answering the question of this essay: what are the features necessary for a self-conscious robot in the light of “Consciousness Explained” by Daniel Dennett? (shrink)

Eliminativism is a position most readily associated with the eliminative materialism of the Churchlands, denying that there are such things as propositional states. This position has created much controversy, despite the fact that intentionality has long been seen as perhaps the core problem for naturalistic philosophy. There is a more radical interpretation of eliminativism, however, denying not only mental states, such as beliefs and desires, but also intentionality (i.e., aboutness) on a global level. This position traces its contemporary origin back (...) to Quine, but has generally been assumed to undermine naturalism or, worse, to be incoherent by the majority of philosophers who maintain that there clearly are things or mental states that are about others. In a recent paper, Hutto and Satne (2015a) offer an update that tries to revive John Haugeland’s baseball analogy from his influential 1990 review paper The Intentionality All-Stars on the state of the game to argue that the failure of Neo-Cartesians, Neo- Behaviorists, and Neo-Pragmatists should urge us to make them work together to naturalize content and “win the game.” But Hutto and Satne misunderstand what the game is ultimately about. The goal of the Intentionality All-Stars is not to naturalize content against eliminativism but to defend a naturalist “thirdperson” view of the problem against first-person phenomenalists. For this goal, a naturalist defense of global content eliminativism would equally enable them to emerge victorious. Revisiting Haugeland, I will offer my own analysis of the current state of play to argue that global content eliminativism has not received sufficient attention and deserves a more prominent place in the debate than it currently occupies. (shrink)

Artificial intelligence (AI) technologies are used in various domains of human activities, and one of these domains is scientific research. Now, researchers in many scientific areas try to apply AI technologies to their research and automate it. These researchers claim that the ‘automation of science’ will liberate people from non-creative tasks in scientific research, and radically change the overall state of science and technology so that large-scale innovation results. As I see it, the automation of science is remarkable in another (...) respect: since science is one of the most distinctive human activities, the tendency of automating it prompts us to reconsider the aspects of our humanity itself. One of these aspects is concerned with human creativity, on which this article focuses. In this article, I address two questions concerning the automation of science: first, ‘Can AI makes creative discovery?’; second, ‘What implications may the automation of science have on science and society?’. Scientific discovery is said to be one of the most creative phases of scientific research. I show that, though there are no reasons in principle why AI could not make creative discovery, we do not at present have enough knowledge how to realize it. If the automation of science nevertheless proceeds, the cultural values science as a creative activity has might be reduced, and it might alter the state of scientific community and its relationship with society in some undesirable way. Therefore, I conclude, we need to specify desirable ways of introducing AI technologies into science and devise measures against demerits of automating science. (shrink)

Whether it was John Searle’s Chinese Room argument (Searle, 1980) or Roger Penrose’s argument of the non-computable nature of a mathematician’s insight – an argument that was based on Gödel’s Incompleteness theorem (Penrose, 1989), we have always had skeptics that questioned the possibility of realizing strong Artificial Intelligence (AI), or what has become known by Artificial General Intelligence (AGI). But this new book by Landgrebe and Smith (henceforth, L&S) is perhaps the strongest argument ever made against strong AI. It is (...) a very extensive review of what building a mind essentially amounts to drawing on insights and results from biology, physics, linguistics, computability, philosophy, and mathematics. (shrink)

Investigamos o problema da continuidade entre (1) cognições básicas e (2) complexas, especificamente em relação à linguagem. Nossa hipótese é a de que visões contemporâneas da linguagem não inviabilizam necessariamente a abordagem bottom-up ― abordagens tipicamente enativistas. Primeiro apresentamos a posição de Daniel Hutto e Erik Myin (2013, 2017), representantes do Radically Enactive Cognition (REC), a qual assume o desafio da continuidade e identifica na linguagem o critério para uma distinção de tipo entre (1) e (2). Em seguida, estabelecemos a (...) posição Wittgensteiniana defendida por Moyal-Sharrock (2019), na qual a linguagem seria apenas mais uma habilidade de possível desenvolvimento para (1) e (2). Haveria, portanto, somente uma distinção de grau , não de tipo. Por mais que a avaliação de Moyal-Sharrock seja interessante no sentido de que parece evitar um ceticismo de continuidade (identificado por ela no REC), também encontramos problemas em sua visão. (shrink)

In philosophy of mind, zombies are imaginary creatures that are exact physical duplicates of conscious subjects but for whom there is no first-personal experience. Zombies are meant to show that physicalism—the theory that the universe is made up entirely out of physical components—is false. In this paper, I apply the zombie thought experiment to the realm of morality to assess whether moral agency is something independent from sentience. Algorithms, I argue, are a kind of functional moral zombie, such that thinking (...) about the latter can help us better understand and regulate the former. I contend that the main reason why algorithms can be neither autonomous nor accountable is that they lack sentience. Moral zombies and algorithms are incoherent as moral agents because they lack the necessary moral understanding to be morally responsible. To understand what it means to inflict pain on someone, it is necessary to have experiential knowledge of pain. At most, for an algorithm that feels nothing, ‘values’ will be items on a list, possibly prioritised in a certain way according to a number that represents weightiness. But entities that do not feel cannot value, and beings that do not value cannot act for moral reasons. (shrink)

Our goal in this paper is to establish a set of criteria for understanding the meaning and sources of attributing (un)fairness to AI algorithms. To do so, we first establish that (un)fairness, like other normative notions, can be understood in a proper primary sense and in secondary senses derived by analogy. We argue that AI algorithms cannot be said to be (un)fair in the proper sense due to a set of criteria related to normativity and agency. However, we demonstrate how (...) and why AI algorithms can be qualified as (un)fair by analogy and explore the sources of this (un)fairness and the associated problems of responsibility assignment. We conclude that more user-driven AI approaches could alleviate some of these difficulties. (shrink)

Scientific understanding is a fundamental goal of science. However, there is currently no good way to measure the scientific understanding of agents, whether these be humans or Artificial Intelligence systems. Without a clear benchmark, it is challenging to evaluate and compare different levels of scientific understanding. In this paper, we propose a framework to create a benchmark for scientific understanding, utilizing tools from philosophy of science. We adopt a behavioral conception of understanding, according to which genuine understanding should be recognized (...) as an ability to perform certain tasks. We extend this notion of scientific understanding by considering a set of questions that gauge different levels of scientific understanding, covering information retrieval, the capability to arrange information to produce an explanation, and the ability to infer how things would be different under different circumstances. We suggest building a Scientific Understanding Benchmark (SUB), formed by a set of these tests, allowing for the evaluation and comparison of scientific understanding. Benchmarking plays a crucial role in establishing trust, ensuring quality control, and providing a basis for performance evaluation. By aligning machine and human scientific understanding we can improve their utility, ultimately advancing scientific understanding and helping to discover new insights within machines. (shrink)

Disertační práce se zabývá problematikou připisování myšlení jiným entitám, a to pomocí imitační hry navržené v roce 1950 britským filosofem Alanem Turingem. Jeho kritérium, známé v dějinách filosofie jako Turingův test, je podrobeno detailní analýze. Práce popisuje nejen původní námitky samotného Turinga, ale především pozdější diskuse v druhé polovině 20. století. Největší pozornost je věnována těmto kritikám: Lucasova matematická námitka využívající Gödelovu větu o neúplnosti, Searlův argument čínského pokoje konstatující nedostatečnost syntaxe pro sémantiku, Blockův návrh na použití brutální síly pro (...) řešení imitační hry, Frenchova teorie subkognitivních informací a Michieho skepticismus ohledně možnosti umělého vědomí. Závěr práce zachycuje současný stav recepce Turingova testu a představuje pokusy o jeho praktickou realizaci, například v každoroční soutěži o Loebnerovu cenu. Autor práce zastává názor, že ani po více než šedesáti letech od uveřejnění Turingova paradigmatického eseje stále neexistují žádné vážné důvody pro zamítnutí jeho tvrzení. Tradiční komputační funkcionalismus možná není ideální teorií vysvětlující činnost myslí a jako slibnější se může jevit vývoj v neurálních vědách, ale Turingův test je přesto užitečným a snad i jediným nástrojem pro detekci inteligence u lidmi vytvořených strojů. (shrink)

According to a recent philosophical claim, “works of fiction are thought experiments” (Elgin 2007: 47), though there are relevant differences, as the role of spoilers shows—they can ruin a novel but improve the understanding we can gain through a thought experiment. In the present article I will analyze the role of spoilers and argue for a more differentiated perspective on the relation between literature and thought experiments. I will start with a short discussion of different perspectives on thought experiments and (...) argue that the mental-model view and the conception of games of make-believe are most promising for developing the present analogy. Then I will assess the similarities and differences between thought experiments and other works of fiction. I will focus on the role of spoilers and, more generally, on the foretaste context, of which they are part. This context guides readers of literary works of art to draw their attention to the literary and aesthetic quality of the text. In the case of thought experiments, on the other hand, it (i) prompts them to accept the presence of fictional elements in worldly-cognitive works and (ii) draws their attention towards cognitively relevant elements of the story. A discussion of Borges’ Pierre Menard in the last part will show that literary works of art become thought experiments if they are embedded in an appropriate foretaste context. Spoilers, thus, unveil that even works which—due to their length or plenty of detail—usually are not considered thought experiments, can perform similar cognitive functions. (shrink)

In this paper, I argue that absences pose a challenge to our understanding of physicalism that has not been properly appreciated. I do this by setting out a thought experiment involving a being in whom absence properties occupy the causal roles that functionalists take to define mental properties, in which case these absence properties realize the being’s mental properties. Such a being should be compatible with the truth of physicalism, I argue, even though its mental properties are neither themselves physical (...) properties nor are they realized/grounded in physical properties—instead, they are realized/grounded in (nonphysical) absence properties. I argue that the case serves as a counterexample to leading formulations of physicalism that appeal to realization or grounding, but not to standard supervenience-based formulations of physicalism, because the latter typically include negative truths in their supervenience base in addition to physical truths. I show how realization- and grounding-based formulations of physicalism might be revised to handle the problem, but also recommend that we rethink how we understand physicalism and the role that negative entities can play for physicalists. (shrink)

This paper investigates the prospects of Rodney Brooks’ proposal for AI without representation. It turns out that the supposedly characteristic features of “new AI” (embodiment, situatedness, absence of reasoning, and absence of representation) are all present in conventional systems: “New AI” is just like old AI. Brooks proposal boils down to the architectural rejection of central control in intelligent agents—Which, however, turns out to be crucial. Some of more recent cognitive science suggests that we might do well to dispose of (...) the image of intelligent agents as central representation processors. If this paradigm shift is achieved, Brooks’ proposal for cognition without representation appears promising for full-blown intelligent agents—Though not for conscious agents. (shrink)

Artificial intelligence (AI) is a digital technology that will be of major importance for the development of humanity in the near future. AI has raised fundamental questions about what we should do with such systems, what the systems themselves should do, what risks they involve and how we can control these. - After the background to the field (1), this article introduces the main debates (2), first on ethical issues that arise with AI systems as objects, i.e. tools made and (...) used by humans; here, the main sections are privacy (2.1), manipulation (2.2), opacity (2.3), bias (2.4), autonomy & responsibility (2.6) and the singularity (2.7). Then we look at AI systems as subjects, i.e. when ethics is for the AI systems themselves in machine ethics (2.8.) and artificial moral agency (2.9). Finally we look at future developments and the concept of AI (3). For each section within these themes, we provide a general explanation of the ethical issues, we outline existing positions and arguments, then we analyse how this plays out with current technologies and finally what policy conse-quences may be drawn. (shrink)

David Lewis defends the following "non-circular definition of personhood": "something is a continuant person if and only if it is a maximal R-interrelated aggregate of person-stages. That is: if and only if it is an aggregate of person-stages, each of which is R-related to all the rest (and to itself), and it is a proper part of no other such aggregate." I give a counterexample, involving a person who is a part of another, much larger person, with a separate mental (...) life. I then offer an easy repair, which preserves the virtues of Lewis's definition without introducing any new vices. (shrink)

In this reply to James H. Fetzer’s “Minds and Machines: Limits to Simulations of Thought and Action”, I argue that computationalism should not be the view that (human) cognition is computation, but that it should be the view that cognition (simpliciter) is computable. It follows that computationalism can be true even if (human) cognition is not the result of computations in the brain. I also argue that, if semiotic systems are systems that interpret signs, then both humans and computers are (...) semiotic systems. Finally, I suggest that minds can be considered as virtual machines implemented in certain semiotic systems, primarily the brain, but also AI computers. In doing so, I take issue with Fetzer’s arguments to the contrary. (shrink)

This book contains a representationalist theory of self-consciousness and of the phenomenal first-person perspective. It draws on empirical data from the cognitive and neurosciences.

In the Fall of 1983, I offered a junior/senior-level course in Philosophy of Artificial Intelligence, in the Department of Philosophy at SUNY Fredonia, after returning there from a year’s leave to study and do research in computer science and artificial intelligence (AI) at SUNY Buffalo. Of the 30 students enrolled, most were computerscience majors, about a third had no computer background, and only a handful had studied any philosophy. (I might note that enrollments have subsequently increased in the Philosophy Department’s (...) AI-related courses, such as logic, philosophy of mind, and epistemology, and that several computer science students have added philosophy as a second major.) This article describes that course, provides material for use in such a course, and offers a bibliography of relevant articles in the AI, cognitive science, and philosophical literature. (shrink)

Este trabajo examina si la pregunta “¿puede pensar una máquina?” ha sido respondida de manera satisfactoria. La primera sección, justamente, examina el dictum cartesiano según el cual una máquina no puede pensar en principio. La segunda trata sobre una rebelión en contra de Descartes, encabezada por Babbage. A su vez, la tercera describe una segunda rebelión encabezada por Turing. En ambas se examina, primero el lenguaje mentalista/instrumentalista para describir a una máquina programada y segundo, el reemplazo de la pregunta por (...) el Juego de la Imitación. En la cuarta sección sostengo que la evidencia aportada por dicho juego nos devuelve a la pregunta, pese a Turing. Por último, la quinta sección versa sobre cómo la Habitación China de Searle, paradójicamente, apoya el dictum cartesiano, y lo hace porque tal experimento mental se basa en una capacidad mental falible: la introspección. Se concluye que la pregunta acerca de si puede pensar una máquina es derivada de otra pregunta filosófica compleja: la de la naturaleza de lo mental y el problema mente-cuerpo. (shrink)

Interdisciplinary investigations marry the methods and concerns of different fields. Computer science is the study of precise descriptions of finite processes; semantics is the study of meaning in language. Thus, computational semantics embraces any project that approaches the phenomenon of meaning by way of tasks that can be performed by following definite sets of mechanical instructions. So understood, computational semantics revels in applying semantics, by creating intelligent devices whose broader behavior fits the meanings of utterances, and not just their form. (...) IBM’s Watson (Ferrucci, Brown, Chu-Carroll, Fan, Gondek, Kalyanpur, Lally, Murdock, Nyberg, Prager, Schlaefer & Welty 2010) is a harbinger of the excitement and potential of this technology. (shrink)