This paper discusses the role of cultural anthropology in Cognitive Science. Culture is described as a very large pool of information passed along from generation to generation, composed of learned “programs” for action and understanding. These cultural programs differ in important ways from computer programs. Cultural programs tend to be unspecified and inexplicit rather than clearly stated algorithms learned through a slow process of guided discovery, and involve the manipulation of content based rather than formal symbol systems. Cultural symbol systems (...) often have affective as well as objective referents, giving them a strong directive effect. The argument is made that in the process of repeated social transmission and use, cultural programs come to take forms which have a good “fit” to the natural capacities and constraints of the human information processing system. (shrink)

I present experimental and computational research, inspired by the perspective of Embodied Embedded Cognition, concerning various aspects of language as supporting Everett’s interactionist view of language. Based on earlier and ongo- ing work, I briefly illustrate the contribution of the environment to the syste- maticity displayed in linguistic performance, the importance of joint attention for the development of a shared vocabulary, the role of (limited) traveling for language diversification, the function of perspective taking in social communica- tion, and the bodily (...) nature of understanding of meaning. (shrink)

I present experimental and computational research, inspired by the perspective of Embodied Embedded Cognition, concerning various aspects of language as supporting Everett's interactionist view of language. Based on earlier and ongoing work, I briefly illustrate the contribution of the environment to the systematicity displayed in linguistic performance, the importance of joint attention for the development of a shared vocabulary, the role of (limited) traveling for language diversification, the function of perspective taking in social communication, and the bodily nature of understanding (...) of meaning. (shrink)

Engaging with the question of the extent to which the so-called human, economic or social sciences are actually sciences, this book moves away from the search for a criterion or definition that will allow us to sharply distinguish the scientific from the non-scientific. Instead, the book favours the pursuit of clarity with regard to the various enterprises undertaken by human beings, with a view to dissolving the felt need for such a demarcation. In other words, Read pursues a ‘therapeutic’ approach (...) to the issue of the status and nature of these subjects. Discussing the work of Kuhn, Winch and Wittgenstein in relation to fundamental question of methodology, Wittgenstein among the Sciences undertakes an examination of the nature of (natural) science itself, in the light of which a series of successive cases of putatively scientific disciplines are analysed. A novel and significant contribution to social science methodology and the philosophy of science and ‘the human sciences’, this book will be of interest to social scientists and philosophers, as well as to psychiatrists, economists and cognitive scientists. (shrink)

Is it true that if zombies---creatures who are behaviorally indistinguishable from us, but no more conscious than a rock-are logically possible, the computational conception of mind is false? Are zombies logically possible? Are they physically possible? This paper is a careful, sustained argument for affirmative answers to these three questions.

The dominant scientific and philosophical view of the mind – according to which, put starkly, cognition is computation – is refuted herein, via specification and defense of the following new argument: Computation is reversible; cognition isn't; ergo, cognition isn't computation. After presenting a sustained dialectic arising from this defense, we conclude with a brief preview of the view we would put in place of the cognition-is-computation doctrine.

Bill Joy’s deep pessimism is now famous. Why the Future Doesn’t Need Us, his defense of that pessimism, has been read by, it seems, everyone—and many of these readers, apparently, have been converted to the dark side, or rather more accurately, to the future-is-dark side. Fortunately (for us; unfortunately for Joy), the defense, at least the part of it that pertains to AI and robotics, fails. Ours may be a dark future, but we cannot know that on the basis of (...) Joy’s reasoning. On the other hand, we ought to fear a good deal more than fear itself: we ought to fear not robots, but what some of us may do with robots. (shrink)

In this article, I argue that the artificial components of hybrid bionic systems do not play a direct explanatory role, i.e., in simulative terms, in the overall context of the systems in which they are embedded in. More precisely, I claim that the internal procedures determining the output of such artificial devices, replacing biological tissues and connected to other biological tissues, cannot be used to directly explain the corresponding mechanisms of the biological component(s) they substitute (and therefore cannot be used (...) to explain the local mechanisms determining an overall biological or cognitive function replicated by such bionic models). I ground this analysis on the use of the Minimal Cognitive Grid (MCG), a novel framework proposed in Lieto (Cognitive design for artificial minds, 2021) to rank the epistemological and explanatory status of biologically and cognitively inspired artificial systems. Despite the lack of such a direct mechanistic explanation from the artificial component, however, I also argue that the hybrid bionic systems can have an indirect explanatory role similar to the one played by some AI systems built by using an overall structural design approach (but including the partial adoption of functional components). In particular, the artificial replacement of part(s) of a biological system can provide i) a local functional account of that part(s) in the context of the overall functioning of the hybrid biological–artificial system and ii) global insights about the structural mechanisms of the biological elements connected to such artificial devices. (shrink)

Is attention both necessary and sufficient for consciousness? Call this central question of this treatise, “Q.” We commonly have the experience of consciously paying attention to something, but is it possible to be conscious of something you are not attending to, or to attend to something of which you are not conscious? Where might we find examples of these? This treatise is a quest to find an answer to Q in two parts. Part I reviews the foundations upon which the (...) discourse on Q is built. Different inputs to Q produce different answers. After consideration of the many ways “attention” and “consciousness” have been defined, I settle upon phenomenal consciousness and Executive Attention (defined as a suite of strategies for structuring cognition for further processing implemented by the executive of working memory) as the most interesting inputs to Q, and the ones on which Part II focuses. Attention without consciousness seems relatively easy to establish empirically, but consciousness without attention is much harder. The putative candidates all seem to have major problems, but I build a strong abductive case for the hitherto ignored case of foveal phenomenal overflow. We consciously see far more detail in our foveal fields than we can Executively Attend, although there is a serious obstacle to our ever confirming that empirically—identifying conscious content relies on Executive Attentional report. Triangulating the capacity limitations of attention, consciousness, and working memory strengthens this case for consciousness without attention, and suggests that cognition must work something like my “Witches’ Hat Model,” on which content can become conscious outside of Executive Attention or working memory. I conclude with some reflections on the implications of my arguments for the discourse on Q, and for other discourses such as the ontologies of attention and consciousness, theories of consciousness, some other cognitive concepts, and ethical considerations in humans, animals, and machines. A conclusive answer to Q continues to elude us. It may perhaps be an ultimately insoluble conundrum. But it is the very essence of humanity to seek an answer, and in so doing, to improve our understanding of our own nature: “The proper study of mankind is man.”1. (shrink)

An investigation is presented in which a computer simulation model (DIAGNOSER) is used to develop and test predictions for behavior of subjects in a task of medical diagnosis. The first experiment employed a process‐tracing methodology in order to compare hypothesis generation and evaluation behavior of DIAGNOSER with individuals at different levels of expertise (students, trainees, experts). A second experiment performed with only DIAGNOSER identified conditions under which errors in reasoning in the first experiment could be related to interpretation of specific (...) data items. Predictions derived from DIAGNOSER's performance were tested in a third experiment with a new sample of subjects. Data from the three experiments indicated that (1) form of diagnostic reasoning was similar for all subjects trained in medicine and for the simulation model, (2) substance of diagnostic reasoning employed by the simulation model was parable with that of the more expert subjects, and (3) errors in subjects' reasoning were attributable to deficiencies in disease knowledge and the interpretation of specific patient data cues predicted by the simulation model. (shrink)

This article examines how experimental psychology experienced a revolution as cognitive science replaced behaviorism in the mid-20th century. This transition in the scientific account of human nature involved making normal what had once been normative: borrowing ideas of democratic thinking from political culture and conceptions of good thinking from philosophy of science to describe humans as active, creatively thinking beings, rather than as organisms that simply respond to environmental conditions. Reflexive social and intellectual practices were central to this process as (...) cognitive scientists used anti-positivist philosophy of science simultaneously to justify their own work as valid and also as a model of human thinking. In the process, the normative philosophy of science or ‘good academic thinking’ that cognitive scientists used to reshape the discipline of psychology and characterize themselves became, at the same time, the descriptive model of human nature. (shrink)

The well-known game of chess has traditionally been modeled in artificial intelligence studies by search engines with advanced pruning techniques. The models were thus centered on an inference engine manipulating passive symbols in the form of tokens. It is beyond doubt, however, that human players do not carry out such processes. Instead, chess masters instead carry out perceptual processes, carefully categorizing the chunks perceived in a position and gradually building complex dynamic structures to represent the subtle pressures embedded in the (...) positions. In this paper we will consider two hypotheses concerning the underlying subcognitive processes and architecture. In the first hypothesis, a multiple-leveled chess representational structure is presented, which includes distance graphs (with varying levels of quality) between pieces, piece mobilities, and abstract roles. These representational schemes seem to account for numerous characteristics of human player’s psychology. The second hypothesis concerns the extension of the architecture proposed in the Copycat project as central for modeling the emergent intuitive perception of a chess position. We provide a synthesis on how the postulated architecture models chess intuition as an emergent mixture of simultaneous distance estimations, chunk perceptions, abstract role awareness, and intention activations. This is an alternative model to the traditional AI approaches, focusing on the philosophy of active symbols. (shrink)

Cognitive activity, which essentially consistsof the use of signs, does not only depend onthe internal (mental, or brain) processes. Thefirst part of the paper presents severalversions of the idea of the external andcultural organization of individual''s mentalprocesses. The second part of the paperconsiders a future development of cognitivescience as a science of the extended andsocially constructed mind. KazimierzTwardowski''s theory of intentionality and histheory of actions and products provide theconceptual framework of the undertaken analysis.

The general process view of learning, which guided research into learning for the first half of this century, has come under attack in recent years from several quarters. One form of criticism has come from proponents of the so-called biological boundaries approach to learning. These theorists have presented a variety of data showing that supposedly general laws of learning may in fact be limited in their applicability to different species and learning tasks, and they argue that the limitations are drawn (...) by the nature of each species' adaptation to the particular requirements of its natural environment. The biological boundaries approach has served an important critical function in the move away from general process learning theory, but it is limited in its ability to provide an alternative to the general process approach. In particular, the biological boundaries approach lacks generality, it is in some respects subservient to the general process tradition, and its ecological content is in too many cases limited toex post factoadaptive explanations of learning skills. A contrasting, ecological approach to learning, which can provide a true alternative to general process theory, is presented. The ecological approach begins by providing an ecological task description for naturally occurring instances of learning; this step answers the question:Whatdoes this animal learn to do? The next step is an analysis of the means by which learning occurs in the course of development, answering the question:Howdoes the animal learn to do this? On the basis of such analyses, local principles of adaptation are formulated to account for the learning abilities of individual species. More global principles are sought by generalization among these local principles and may form the basis for a general ecological theory of learning. (shrink)

Science and technology studies and the emerging field of data science share surprising elective affinities. At the growing intersections of these fields, there will be many opportunities and not a few thorny difficulties for STS scholars. First, I discuss how both fields frame the rollout of data science as a simultaneously social and technical endeavor, even if in distinct ways and for diverging purposes. Second, I discuss the logic of domains in contemporary computer, information, and data science circles. While STS (...) is often agnostic about the borders between the sciences or with industry and state—occasionally taking those boundaries as an object of study—data science takes those boundaries as its target to overcome. These two elective affinities present analytic and practical challenges for STS but also opportunities for engagement. Overall, in addition to these typifications, I urge STS scholars to strategically position themselves to investigate and contribute to the breadth of transformations that seek to touch virtually every science and newly bind spheres of academy, industry, and state. (shrink)

Science aims to transform the subjectivity of individual observations and ideas into more objective and universal knowledge. Yet if there is any area in which first-person experience holds a particularly special and delicate role, it is the sciences of the mind. According to a widespread view, first-person methods were largely discarded from psychology after the fall of introspectionism a century ago and replaced by more objective behavioral measures, a step that some authors have begun to criticize. To examine whether these (...) views are sufficiently informed by actual scientific practice, we conducted a review of methodological approaches in the cognitive science literature. We found that reports of subjective experience are in fact still widely used in a broad variety of different experimental paradigms, both in studies that focus on subjective experience, and in those that make no explicit reference to it. Across these studies, we documented a diverse collection of approaches that leveraged first-person reports, ranging from button presses to unstructured interviews, while continuing to maximise experimental reproducibility. Common to these studies were subjects acting as sensors, intentionally communicating their experience to the experimenter, which we termed “second-person” methods. We conclude that, despite views to the contrary, first-person experience has always been and is still central to investigations of the mind even if it is not recognized as such. We suggest that the conversation ought to be reframed: instead of debating whether to accept subjects’ first-person knowledge we should discuss how best to do so. (shrink)

In this paper the difficulties arising out of a necessary examination of expert systems as to the ‘correctness’ of functioning are outlined. The argumentation is based on the problematic use of the knowledge term in expert system development and the design perspectives connected with the cognitivistic knowledge concept. It becomes obvious that fundamental problems in system development will involve negative consequences for utilization. The perspective developed from this analysis is assuming that these problems have to be taken into account in (...) development and have to be elucidated for utilization. (shrink)

The goals of public education, as well as conceptions of human intelligence and learning, are undergoing a transformation through the application of military-sponsored information technologies and information processing models of human thought. Recent emphases in education on thinking skills, learning strategies, and computer-based technologies are the latest episodes in the postwar military agenda to engineer intelligent components, human and artificial, for the optimal performance of complex technological systems. Public education serves increasingly as a “human factors” laboratory and production site for (...) this military enterprise, whose high performance technologies and command and control paradigms have also played central roles in the emergence of the information economy. (shrink)