Dreyfus’s work is widely known for its critique of artificial intelligence and still stands as an example of how to do excellent philosophical work that is at the same time relevant to contemporary technological and scientific developments. But for philosophers of technology, especially for those sympathetic to using Heidegger, Merleau-Ponty, and Wittgenstein as sources of inspiration, it has much more to offer. This paper outlines Dreyfus’s account of skillful coping and critically evaluates its potential for thinking about technology. First, it (...) is argued that his account of skillful coping can be developed into a general view about handling technology which gives due attention to know-how/implicit knowledge and embodiment. Then a number of outstanding challenges are identified that are difficult to cope with if one remains entirely within the world of Dreyfus’s writings. They concern questions regarding other conceptualizations of technology and human–technology relations, issues concerning how to conceptualize the social and the relation between skill, meaning, and practices, and the question about the ethical and political implications of his view, including how virtue and skill are related. Acknowledging some known discussions about Dreyfus’s work, but also drawing on other material and on the author’s previous writings, the paper suggests that to address these challenges and develop the account of skillful coping into a wider scoped, Dreyfus-inspired philosophy of technology, it could take more distance from Heidegger’s conceptions of technology and benefit from engagement with work in postphenomenology, pragmatism, the later Wittgenstein, and virtue ethics. (shrink)

If the Trade Descriptions Act were applied to academic labels, cognitive scientists would be in trouble. For what they do is much wider than the name suggests—and wider, too, than most philosophers assume. They give you more for your money than you may have expected.

Currently, our official rationality is still of a Cartesian kind; we are still embedded in a mechanistic order that takes it that separate, countable entities (spatial forms), related logically to each other, are the only ‘things’ that matter to us—an order clearly suited to advances in robotics. Unfortunately, it is an order that renders invisible ‘relational things’, non-objective things that exist in time, in the transitions from one state of affairs to another, things that ‘point’ toward possibilities in the future, (...) which mean something to us. I have called such things, hermeneutical–dialogical ‘things’ as they gradually emerge in our back-and-forth, step-by-step relations to the others and otherneses in our surroundings; they consist in the ‘promissory’ things sustaining our trust in each other and in our authorities, in our social organizations and social institutions, and in our culture. Clearly, we need to understand better, not only what robots can, and cannot do, but also the long-term ethical and political implications of inserting robotic activities into our everyday ways of relating ourselves to our surroundings if we are to avoid the dystopian futures envisaged by some. Descartes’ aim of “making ourselves, as it were, masters and possessors of nature,” forgets our larger task of our making ourselves into human beings—of doing together in dialog what we cannot do apart. (shrink)

In this four part exchange, Evan Selinger starts by stating that Collins’s empirical evidence in respect of linguistic socialization and its bearing on artificial intelligence and expertise is valuable; it advances philosophical and sociological understanding of the relationship between knowledge and language. Nevertheless, he argues that Collins mischaracterizes the data under review and thereby misrepresents how knowledge is acquired and understates the extent to which expert knowers are embodied. Selinger reconstructs the case for the importance of the body in the (...) initial acquisition of language and challenges Collins to show how a disembodied entity could become fluent in any language at all.Collins responds by accepting that his approach does not demonstrate quite as much about the irrelevance of the body as he thought it did but that even though he accepts all of Selinger’s claims, ‘the body’ as needed by the philosophical approach set out by Selinger is still a vestigial thing. Collins’s main point, however, is that the philosophical view of the body—the world is divided into embodied agents and unembodied entities—distracts attention from the more interesting empirically researchable question of how the ability to become socialized diminishes, if it does, as the body become more and more minimal. The right research question is not about whether a person can extrapolate from minimal sensory input but how much extrapolation is possible under different circumstances and how it is done.Dreyfus, having seen the whole of the exchange so far, agrees that both have a point but argues that Collins’s approach still misses the well established importance of bodily engagement for full understanding.Collins responds to this by trying to set out more clearly the position associated with the idea of interactional expertise.Keywords: Interactional expertise; Phenomenology; Turing test; Embodiment; Tacit knowledge; Socialization. (shrink)

Harry Collins interprets Hubert Dreyfus’s philosophy of embodiment as a criticism of all possible forms of artificial intelligence. I argue that this characterization is inaccurate and predicated upon a misunderstanding of the relevance of phenomenology for empirical scientific research.

In I used Turing machine arguments to show that computers can recognize humanly recognizable patterns in principle. In 1978 James D. Heffernan has expressed some doubts about such arguments. He does not question the propositions that I defend in the paper, nor the specific arguments in their support. What he does criticize are certain background assumptions.

In this paper I argue that human pattern recognition can be simulated by automata. In particular, I show that gestalt recognition and recognition of family resemblances are within the capabilities of sufficiently complex Turing machines. The argument rests on elementary facts of automata and computability theory which are used to explicate our preanalytic, informal concepts concerning gestalt patterns and recognition. The central idea is that of a machine which "knows" its own structure. Although the paper thus aims to support mechanism, (...) especially as a framework hypothesis for perception, it contains suggestions for philosophy of science and philosophy of language as well. Some of these suggestions are sketched in the final section. (shrink)

For those who find Dreyfus’s critique of AI compelling, the prospects for producing true artificial human intelligence are bleak. An important question thus becomes, what are the prospects for producing artificial non-human intelligence? Applying Dreyfus’s work to this question is difficult, however, because his work is so thoroughly human-centered. Granting Dreyfus that the body is fundamental to intelligence, how are we to conceive of non-human bodies? In this paper, I argue that bringing Dreyfus’s work into conversation with the work of (...) Mark Bickhard offers a way of answering this question, and I try to suggest what doing so means for AI research. (shrink)