The paper examines locative expressions and shows that an adequate account of their meaning must be based on two essential understandings: First, the simple spatial relation, often given as the meaning of the spatial prepositions, is only an “ideal” from which there are deviations in context; second, a level of “geometric conceptualization” mediates between “the world as it is” and language. Pragmatic “near principles” are formulated to explain some deviations from the ideal and several other apparent irregularities of prepositional use. (...) A set of “use types” of the ideal meaning is proposed to account for conventional aspects of locative meaning. The paper concludes with a discussion of the consequences of this description of locative expressions for artificial intelligence and linguistics. (shrink)

By studying several cases of expert systems' use, a variety of difficulties were identified as directly depending on specific characteristics of experts and their tasks. This concerns more than the questions: “May experts be replaced by machines?” or “Is experts' knowledge explicable?”. The organisational structure of their work as well as the cyclic, non-plannable way of their task performing have further relevance. The paper introduces the concept of experts' systems to deal with diversities of their expertise and complexities of their (...) work. It draws a distinction between non-monotonic problem solving, exploration, medium and modification, and argues that these modes are not reducible to yet another improved input/output strategy or dialogue style but introduce additional functions supporting the human-computer interaction according to experts' needs. In the first few sections, the paper covers the theoretical and empirical results of our research, whereas Section 4 introduces our design suggestions for experts' systems. (shrink)

The more recent computer developments cause us to take a new look at human intelligence. The prevailing occidental view of human intelligence represents a very one-sided, logocentric approach, so that it is becoming more urgent to look for a more complete view. In this way, specific strengths of so-called human information processing are becoming particularly evident in a new way. To provide a general substantiation for this view, some elements of a phenomenological model for a dialectical coherence of human expressions (...) of life are briefly outlined. The starting point is the everyday experience of constantly being confronted with contradictory situations. A model of polar, or dualistic, dialectic is proposed, which attempts to systematically establish the contradictions and contingencies of human life in theoretical structures. It is assumed that formal logic fails to work — strictly speaking — when applied to real situations of human interaction. Instead, definite negations are supposed to be involved. In this way, four polarities, pairs of concepts which are mutually dependent on each other and negate each other definitely, are presented: process and structure, the individual and general (societal), acting and imagining, subject-subject-relation and subject-object-relation (love and work). The latter gives rise to the dialectic of emotion and cognition, which plays a decisive role in a comparison of human and computer-“intelligence”.To cope with the specific human strengths, which are expressed through these polarities, self-learning computers would have to be able to act and to love like human beings and to grow up in a society like people. Furthermore, the learning process would have to implement the process-structure-dialectic with its aspects of finality. In spite of the recent breath-taking achievements of computers, one can not imagine how computers would ever achieve this. Computers are, however, thought of, by virtue of their complexity, being qualitatively different from machines. But human abilities still represent a new level of complexity: the level of dialectic. (shrink)

The ArgumentIn this rejoinder to Gyorgy Markus, I argue that although there are nonphilosophical hermeneutical studies of communication among scientists from which much can be learned about scientific practices, there is also the philosophical genre of a hermeneutics of natural science, with which this paper is concerned. The former is the nonphilosophical use of hermeneutics in the study of texts and historical sources; the latter is a philosophy pursued within a working canon of philosophical works defined principally by the writings (...) of Heidegger and Husserl. There is also a hermeneutically sensitive analytic philosophy of science, such as in the work of Kuhn, Toulmin, and Elkana. These genres are distinguished by their literary canons and their basic phenomenologies or critical experiential givens; each genre comprises an exemplary phenomenology as understood with the help of a characteristic fundamental literary canon.I argue that analytic philosophy is pursued within a canon that makes it difficult to raise hermeneutical questions about natural science, and that it assumes a generally positivistic phenomenology. I argue that hermeneutical phenomenology currently defines itself in dialectical opposition to “science” as understood by analytic philosophy, and has failed to exploit the opportunity of making its own positive contribution to the philosophy of science by examining for itself the phenomenology of laboratory work, especially data production, and the transformation of the language of theory into a descriptive language of scientific phenomena. A “strong” hermeneutical philosophy of natural science, then, challenges both analytic philosophy and the existing tradition of hermeneutical phenomenology. (shrink)

Cognitivism in psychology and philosophy is roughly the position that intelligent behavior can (only) be explained by appeal to internal that is, rational thought in a very broad sense. Sections 1 to 5 attempt to explicate in detail the nature of the scientific enterprise that this intuition has inspired. That enterprise is distinctive in at least three ways: It relies on a style of explanation which is different from that of mathematical physics, in such a way that it is not (...) basically concerned with quantitative equational laws; the states and processes with which it deals are in the sense that they are regarded as meaningful or representational; and it is not committed to reductionism, but is open to reduction in a form different from that encountered in other sciences. Spelling these points out makes it clear that the Cognitivist study of the mind can be rigorous and empirical, despite its unprecedented theoretical form. The philosophical explication has another advantage as well: It provides a much needed framework for articulating questions about whether the Cognitivist approach is right or wrong. The last three sections take that advantage of the account, and address several such questions, pro and con. (shrink)

The abject failure of Turing's first prediction (of computer success in playing the Imitation Game) confirms the aptness of the Imitation Game test as a test of human level intelligence. It especially belies fears that the test is too easy. At the same time, this failure disconfirms expectations that human level artificial intelligence will be forthcoming any time soon. On the other hand, the success of Turing's second prediction (that acknowledgment of computer thought processes would become commonplace) in practice amply (...) confirms the thought that computers think in some manner and are possessed of some level of intelligence already. This lends ever-growing support to the hypothesis that computers will think at a human level eventually, despite the abject failure of Turing's first prediction. (shrink)

Will robots ever be able to learn like humans? To answer that question, one first needs to ask: what is learning? Hubert and Stuart Dreyfus had a point when they claimed that computers and robots would never be able to learn like humans because human learning, after an initial phase of rule-based learning, is uncertain, context sensitive and intuitive under contract F49620-C-0063 with the University of California) Berkeley, February 1980.. Washington, DC: Storming Media. https://www.stormingmedia.us/15/1554/A155480.html. Accessed 10 Oct 2017, 1980). I (...) would add that learning also builds on prior learning, and that from the outset, human learning is a socio-cultural materially grounded collective epistemology. This posthuman acknowledgement shifts the focus from the individual learner to learning within collective phenomena. Dreyfus and Dreyfus do not seem to emphasise the essentially social and cultural nature of the human condition. Learning theory, new materialism and postphenomenology have emphasised in different ways the materially based socio-cultural nature of human learning. They thereby point towards a ‘posthuman’ learning that is far from the machine-like or enhanced creature envisioned by singularists. Until robots are essentially social and ground their epistemologies in socio-cultural materiality, I suggest that human-like AI is not possible. (shrink)

Technology design has social as well as technical determinants. These social factors, such as the political context and social philosophy, vary historically and cross-nationally. The work upon which this paper is based addresses the nature of process technology design in the United States and focuses on the underlying assumptions that guide technology design, based on both historical analysis and survey and case studies of current design practices. Central to this work is an analysis of how the US approaches compare to (...) some of the other industrial nations and the assumptions and implications of different social design concepts such as human-centered design, skill-based design, and human factors. (shrink)

John D. Barrow and Frank J. Tipler's recently published Anthropic Cosmological Principle is an encyclopedic defense of melioristic evolutionary cosmology. They review the history of the idea from ancient times to the present, and defend both a “weak” version, and two “strong” versions of the anthropic principle. I argue the weak version of the anthropic principle is true and important, but that neither of the two strong versions are well grounded in fact. Their “final” anthropic principle is a revision of (...) Teilhard de Chardin's evolutionary cosmology. They rectify Teilhard's factual errors but commit even more serious psychological and religious errors of their own. (shrink)

This paper maintains that post Lave and Wenger VET has overlooked the relation between vocational curricula and workplace practice. The paper attributes this oversight to Kant's legacy in the ‘situated’ tradition in VET and critics of that tradition. The paper argues that when Vygotsky's concept of mediation is allied to the recent work of Robert Brandom and John McDowell, it is possible to formulate a non‐dualisitic conception of the relation between mind and world that goes beyond the Kantian separation of (...) mind and allows us to grasp the interdependency of theory and practice. The paper concludes by outlining the implications of this philosophical and theoretical claim for vocational curriculum and vocational pedagogy. (shrink)

The aim of this paper is to grasp the relevant distinctions between various ways in which models and simulations in Artificial Intelligence (AI) relate to cognitive phenomena. In order to get a systematic picture, a taxonomy is developed that is based on the coordinates of formal versus material analogies and theory-guided versus pre-theoretic models in science. These distinctions have parallels in the computational versus mimetic aspects and in analytic versus exploratory types of computer simulation. The proposed taxonomy cuts across the (...) traditional dichotomies between symbolic and embodied AI, general intelligence and symbol and intelligence and cognitive simulation and human/non-human-like AI. -/- According to the taxonomy proposed here, one can distinguish between four distinct general approaches that figured prominently in early and classical AI, and that have partly developed into distinct research programs: first, phenomenal simulations (e.g., Turing’s “imitation game”); second, simulations that explore general-level formal isomorphisms in pursuit of a general theory of intelligence (e.g., logic-based AI); third, simulations as exploratory material models that serve to develop theoretical accounts of cognitive processes (e.g., Marr’s stages of visual processing and classical connectionism); and fourth, simulations as strictly formal models of a theory of computation that postulates cognitive processes to be isomorphic with computational processes (strong symbolic AI). -/- In continuation of pragmatic views of the modes of modeling and simulating world affairs, this taxonomy of approaches to modeling in AI helps to elucidate how available computational concepts and simulational resources contribute to the modes of representation and theory development in AI research—and what made that research program uniquely dependent on them. (shrink)

The problem of epistemic opacity in Artificial Intelligence is often characterised as a problem of intransparent algorithms that give rise to intransparent models. However, the degrees of transparency of an AI model should not be taken as an absolute measure of the properties of its algorithms but of the model’s degree of intelligibility to human users. Its epistemically relevant elements are to be specified on various levels above and beyond the computational one. In order to elucidate this claim, I first (...) contrast computer models and their claims to algorithm-based universality with cybernetics-style analogue models and their claims to structural isomorphism between elements of model and target system. While analogue models aim at perceptually or conceptually accessible model-target relations, computer models give rise to a specific kind of underdetermination in these relations that needs to be addressed in specific ways. I then undertake a comparison between two contemporary AI approaches that, although related, distinctly align with the above modelling paradigms and represent distinct strategies towards model intelligibility: Deep Neural Networks and Predictive Processing. I conclude that their respective degrees of epistemic transparency primarily depend on the underlying purposes of modelling, not on their computational properties. (shrink)

The entwinement of affects and the public dimension seems an enigma. We cannot resolve this problem if we continue to refer to the Freudian analysis that deals with the classic dualisms opposing violence to order, love to death, and the body to social order. A feminist analysis, reworking psychoanalytical knowledge, offers another thesis. Taking the concept of `affects' – defined as one's corporeal drives in their sociocultural expression – a different analysis and new political practices emerge. This concerns recognizing a (...) necessary tension between an irreducible singularity and the `being-together' dimension, which is beyond the classic dualism opposing the body to the Law. (shrink)

Can mind be modeled as a Turing machine? If you find such questions irrelevant, e.g. because the subject is already exhausted, then you need not read the book Mind versus Computer (Gams et al., 1991). If, on the other hand, you do find such questions relevant, then perhaps you need not read Dunlop's review of the book (Dunlop, 2000). (...).

Which notion of computation (if any) is essential for explaining cognition? Five answers to this question are discussed in the paper. (1) The classicist answer: symbolic (digital) computation is required for explaining cognition; (2) The broad digital computationalist answer: digital computation broadly construed is required for explaining cognition; (3) The connectionist answer: sub-symbolic computation is required for explaining cognition; (4) The computational neuroscientist answer: neural computation (that, strictly, is neither digital nor analogue) is required for explaining cognition; (5) The extreme (...) dynamicist answer: computation is not required for explaining cognition. The first four answers are only accurate to a first approximation. But the “devil” is in the details. The last answer cashes in on the parenthetical “if any” in the question above. The classicist argues that cognition is symbolic computation. But digital computationalism need not be equated with classicism. Indeed, computationalism can, in principle, range from digital (and analogue) computationalism through (the weaker thesis of) generic computationalism to (the even weaker thesis of) digital (or analogue) pancomputationalism. Connectionism, which has traditionally been criticised by classicists for being non-computational, can be plausibly construed as being either analogue or digital computationalism (depending on the type of connectionist networks used). Computational neuroscience invokes the notion of neural computation that may (possibly) be interpreted as a sui generis type of computation. The extreme dynamicist argues that the time has come for a post-computational cognitive science. This paper is an attempt to shed some light on this debate by examining various conceptions and misconceptions of (particularly digital) computation. (shrink)

With recent advancements in technology and computer science, we have reached a point where we can clearly state that thinking is no longer the exclusive privilege of living minds. Artificial intelligence can gather and process information in a manner fairly similar or even superior to our thinking process. AI can use this processed information in a reasoning process to make decisions and execute them. However, what makes our mind distinct from AI is the addition of “I,” that is, an entity (...) composed of two mental processes of awareness-based choice selection and discretionary selection of information for attention that are the fundamental core function of decision making and awareness processes, respectively. ABCS allows the coexistence of free will alongside—but unrestrained by—the chain of causality in the decision-making process with the help of awareness. “I” also allows for DSIA, which is a key step in the awareness process. This intertwined process is crucial for our consciousness. Similar to AI, the mind is devoid of any form of self-recognition without awareness. Self-awareness is a collaborative function of “I” and the mind. “I” is instrumental in the sense of self-awareness, but on its own, it is selfless. Additionally, “I” is the heart of the decision-making process. Therefore, AI is missing “I,” a selfless master of the mind. (shrink)

Advances in artificial intelligence and robotics stand to change many aspects of our lives, including our values. If trends continue as expected, many industries will undergo automation in the near future, calling into question whether we can still value the sense of identity and security our occupations once provided us with. Likewise, the advent of social robots driven by AI, appears to be shifting the meaning of numerous, long-standing values associated with interpersonal relationships, like friendship. Furthermore, powerful actors’ and institutions’ (...) increasing reliance on AI to make decisions that may affect how people live their lives may have a significant impact on privacy while also raising issues about algorithmic transparency and human control. In this paper, building and expanding on previous works, we will look at how the deployment of Artificial Intelligence technology may lead to changes in identity, security, and other crucial values. We will discuss what challenges we may face in the process, while critically reflecting on whether such changes may be desirable. Finally, drawing on a series of considerations underlying virtue ethics, we will formulate a set of preliminary suggestions, which—we hope—can be used to more carefully guide the future roll out of AI technologies for human flourishing; that is, for social and moral good. (shrink)

MICHAEL WHEELER Cambridge, MA: MIT Press, 2005432 pages, ISBN: 0262232405 (hbk); $35.001.When I was teaching at MIT in the 1960s, students from the Artificial Intelligence Laboratory would come to...

As societies become increasingly technologised, the need for careful and critical assessment rises. However, attempts to assess or normatively evaluate technological development invariably meet with an antinomy: both structurally and historically, technologies display multistable possibilities regarding uses, effects, side effects and other outcomes. Philosophers, usually expected to play applied ethics roles, often come to the scene after these effects are known. But others who participate at the research and development stages find even more difficulties with prognosis. Recent work on ‘revenge’ (...) effects (Tenner) and negative side effects (Kevles) are examined, as well as several cases of philosophers in ‘R&D’ roles. After sketching the antinomy,I outline a heuristic pragmatics of prognosis that addresses this quandary. (shrink)

Questions are currently being posed concerning the implications of the clinical uptake of psychedelics. While enthusiasm surrounds the potential therapeutic benefits of psychedelics and critique surrounds their appropriation to commercial ends, limited attention has been given to the role of psychedelics in generating social transformation. Herbert Marcuse contended radical change requires ‘new imaginaries of liberation’. We consider whether clinical uptake of psychedelics may produce the perceptual shifts necessary to generate social transformation surrounding contemporary alienating conditions. Economic structures contributing to these (...) alienating conditions are highly resistant to change and may neuter psychedelics’ revolutionary potential. We illustrate how psychedelics may be instrumentalised: regulating individuals into unjust systems; redirecting psychedelic usage away from therapeutic ends towards productivity; distracting or diverting attention from systemic forms of control; usurping non- ordinary states into the domain of self-care; and fetishistically commodifying psychedelic experience as a consumable. There are, however, reasons to believe that psychedelics, in raising consciousnesses, may prove resistant to co-option. In particular, psychedelics induce perceptual experiences that: challenge the paradigmatic assumptions of industrial society by provoking alternative epistemologies and meta- physics; generate expanded or ecological constructions of selfhood, thereby offering resignifications of meanings, desires, and life potentials; and offer the enriched phenomenological insight into self, other, and world called for in combating ubiquitous social alienation. In this way, psychedelics may induce the revolution in perception necessary to imagine liberatory potentials and spark the desire for collective emancipation. (shrink)

Some think that issues to do with scientific method are last century's stale debate; Popper was an advocate of methodology, but Kuhn, Feyerabend, and others are alleged to have brought the debate about its status to an end. The papers in this volume show that issues in methodology are still very much alive. Some of the papers reinvestigate issues in the debate over methodology, while others set out new ways in which the debate has developed in the last decade. The (...) book will be of interest to philosophers and scientists alike in the reassessment it provides of earlier debates about method and current directions of research. (shrink)

Online collection of papers by Devitt, Dretske, Guarino, Hochberg, Jackson, Petitot, Searle, Tye, Varzi and other leading thinkers on philosophy and the foundations of cognitive Science. Topics dealt with include: Wittgenstein and Cognitive Science, Content and Object, Logic and Foundations, Language and Linguistics, and Ontology and Mereology.

Philosophers since the ancient Greeks have investigated the nature of different kinds of inference. Although deductive inference in the form of Aristotelian syllogisms and Fregean formal logic has predominated, much attention has also been paid to induction, inference where the conclusion does not follow necessarily from the premises.

Recent works in philosophy of mind and the cognitive sciences draw an “unconventional” picture of cognitive processes and of the mind. Instead of conceiving of cognition as a process that takes place within the boundaries of the skull and the skin, some contemporary theories claim that cognition is a situated process that encompasses the human agent’s boundaries. In particular, the Extended Mind Hypothesis (EMH) and the Enactive approach to cognition claim that embodied action is constitutive of cognitive processes, and thus (...) of the mind. Although both theories give an “extended” or “extensive” picture of cognition and of the mind, they disagree on the epistemic value of internal representations. The EMH claims that we need to posit internal action- oriented representations (AORs). AORs would account for action-selection, action-control, and for the prediction of incoming perceptual information. The enactive approach to cognition argues against AORs. The concept of AOR does not fulfill the representational conditions necessary to talk about representations properly. Furthermore, AORs are expressive of an internalistic prejudice, which makes the EMH weak. Moreover, a semiotic analysis of AORs shows that these items called “representations” are not active at all. Therefore, the epistemic posit of AOR plays no interesting job in the project of extending the mind in virtue of a reassessment of the concept of representation aimed at making it embodied and active. Therefore I claim that the concept of AOR has to be rejected. Action- control, action-selection, and the anticipation of aspects of action-perception loops can be explained in a more enactive way. Embodied action in a field of affordances explains how agents respond selectively to environmental features and how action-perception loops are anticipated by the “affective agent”. Furthermore, the enactive approach to cognition - especially if coupled with a semiotic description of cognitive niches and with some insights from the affective sciences (e.g. appraisal of core relational themes) - gives an explanation of action that, in contrast to the EMH, is actually able to “extend the mind”. (shrink)