While calls to integrate ethics into computer science education go back decades, recent high-profile ethical failures related to computing technology by large technology companies, governments, and academic institutions have accelerated the adoption of computer ethics education at all levels of instruction. Discussions of how to integrate ethics into existing computer science programmes often focus on the structure of the intervention—embedded modules or dedicated courses, humanists or computer scientists as ethics instructors—or on the specific content to be included—lists of case studies (...) and essential topics to cover. While proponents of computer ethics education often emphasize the importance of closely connecting ethical and technical content in these initiatives, most do not reflect in depth on the variety of ways in which the disciplines can be combined. In this paper, I deploy a framework from cross- disciplinary studies that categorizes academic projects that work across disciplines as multidisciplinary, interdisciplinary, or transdisciplinary, depending on the degree of integration. When applied to computer ethics education, this framework is orthogonal to the structure and content of the initiative, as I illustrate using examples of dedicated ethics courses and embedded modules. It therefore highlights additional features of cross-disciplinary teaching that need to be considered when planning a computer ethics programme. I argue that computer ethics education should aim to be at least interdisciplinary—multidisciplinary initiatives are less aligned with the pedagogical aims of computer ethics—and that computer ethics educators should experiment with fully transdisciplinary education that could transform computer science as a whole for the better. (shrink)

Human behavior and thought often exhibit a familiar pattern of within group similarity and between group difference. Many of these patterns are attributed to cultural differences. For much of the history of its investigation into behavior and thought, however, cognitive science has been disproportionately focused on uncovering and explaining the more universal features of human minds—or the universal features of minds in general. -/- This entry charts out the ways in which this has changed over recent decades. It sketches the (...) motivation behind the cultural turn in cognitive science, and situates some of its central findings with respect to the questions that animate it and the debates that it has inspired. Woven throughout the entry are examples of how the cognitive science of culture, and especially its elevated concern with different forms of diversity and variation, continues to influence and be influenced by philosophers. -/- One cluster of philosophical work falls within the traditional subject matter of philosophy of science, in this case of the cognitive and social sciences. Philosophers have analyzed and assessed the methods and evidence central to the scientific study of cognition and culture, and have offered conceptual scrutiny, clarification, and synthesis. Research in a second vein sees philosophers themselves contributing more directly to cognitive scientific projects, (co)constructing theories, helping build computational models, even gathering empirical data. A third kind of work is naturalistic philosophy or philosophy of nature, wherein philosophers seek to use results from the cognitive science of culture to inform or transform debates over long-standing philosophical questions, including questions about the nature of philosophy and philosophical methodology itself. (shrink)

The guiding question for this essay is: who is the learner? The aim is to examine and criticize one answer to this question, sometimes referred to as the theory of the learning brain, which suggests that the explanation of human learning can be reduced to the transmitting and storing of information in the brain’s formal and representational architecture, i.e., that the brain is the learner. This essay will argue that this answer is misleading, because it cannot account for the way (...) people strive to learn in an attempt to lead a good life as it misrepresents the intentional life of the mind, which results in its counting ourselves out of the picture when it attempts to provide a scientific theory of the learning process. To criticize the theory of the learning brain, this essay will investigate its philosophical foundation, a theory of mind called cognitivism, which is the basis for the cognitive sciences. Cognitivism is itself built on three main tenets: mentalism, the mind-brain identity theory and the computer analogy. Each of these tenets will be criticized in turn, before the essay turns to criticize the theory of the learning brain itself. The focus of this essay is, in other words, mainly negative. The hope is that this criticism will lay the groundwork for an alternative view of mind, one that is better equipped to give meaningful answers to the important questions we have about what it means to learn, i.e., what we learn, how we do it and why. This alternative will emphasize the holistic and intentional character of the human mind, and consider the learning process as an intentional activity performed, not by isolated brains, but by people with minds that are extended, embodied, enacted and embedded in a sociocultural and physical context. (shrink)

Background: Interdisciplinarity is one of the current trends in the scientific world today, that began with the uneasiness about the loss of the unity of science. This trend also opens possibilities for explaining complex phenomena more comprehensively and creating more advanced applications and implementations of scientific theories. One of the biggest challenges to conducting interdisciplinary research is theoretical integration, how can we combine theories from various disciplines such that the combination is fruitful? Method: This dissertation attempts to answer this challenge (...) by analyzing the intertheoretical connections of some theories from various disciplines for some real interdisciplinary research. The structuralist metatheory of science is applied as the basic theory to model the intertheoretical connections formally. This research begins with modeling the scientific theories in question before modeling the intertheoretical connections and some modifications needed. This research focuses on some researches in cognitive science that involve psychology, neuroscience, and artificial intelligence. The first research is the research conducted by van Veen et al., who research the activity of neurons in a brain's field called dorsal Anterior Cingulate Cortex during a phase of dissonance between cognitions. This research serves as a context for the analysis of intertheoretical reduction between the Festinger theory of cognitive dissonance and the Hawkins-Kandel computational neuroscientific theory. The other research is the consonance model of simulation built by Shultz and Lepper, which implements the Hopfield network to build a simulation of the cognitive dissonance. The third research is the connectionist model of simulation built by van Overwalle and Jordens, which implements the two-layers feed-forward perceptron and the delta rule as its learning rule to build a simulation of forced compliance dissonance. Result: Through this research, the author concludes that the structuralist metatheory of science can be applied for modeling and analyzing intertheoretical connections in the same discipline and between disciplines in real scientific research. The structuralist metatheory of science enables us to model and analyze the structure of the theories and their intertheoretical connections with great detail and brings very fruitful results. This research delivers some results not only for the structuralist theory science itself but also for the philosophy of science in general and interdisciplinary researches, especially cognitive science. First, by analyzing the models, a revision of the definition of intertheoretical specialization, and specialization of the concept of theory-holon according to the structuralist theory of science, called the V-pattern and strategy for combining scientific theories, are proposed. These V-pattern and strategy can serve as a tool for combining scientific theories. Second, unlike other approaches on intertheoretical reduction such as the GNS model, the structuralist metatheory of science does not intend to formulate a generalized model of reduction nor focus only on intertheoretical reduction. It provides us powerful tools for modeling various intertheoretical relations, including intertheoretical reduction, case by case. Although the intertheoretical reduction in the structuralist model is more epistemological than ontological, the structuralist models show how the reduction has empirical claims and intended applications by applying the r* function that maps the T-theoretical level to T-non-theoretical level. Third, related to the notion of the unity of science, this dissertation still sees that the unity of science is still a plausible and essential agenda for the philosophy of science and the scientific world in general. This dissertation's idea of the unity of science proposed does not assume essentialism, reductionism, and epistemological monism. This dissertation sees that the unity of science is closely related to scientific practice. Fourth, for interdisciplinary research, primarily cognitive science, this dissertation proposes an approach to model and analyze intertheoretical connections for any scientific research or any philosophical school in philosophy of science related to the idea of intertheoretical relation. This dissertation is the first example of such modeling and analysis. (shrink)

Este artículo defiende la relevancia de la filosofía en el estudio contemporáneo de conceptos. Con el desarrollo de la ciencia cognitiva, la teorización naturalista e interdisciplinaria acerca de los conceptos ha cobrado impulso. En este contexto, se ha argumentado recientemente que las teorías filosóficas de conceptos no son acerca del tipo de cosas que interesan a los psicólogos, descartando así la pertinencia científica de la contribución filosófica mencionada. Presentamos y discutimos dos casos que sugieren lo contrario, como un intento de (...) reivindicar el papel crucial que tiene la filosofía en el desarrollo de teorías empíricas de conceptos. (shrink)

The increased interactivity and connectivity of computational devices along with the spreading of computational tools and computational thinking across the fields, has changed our understanding of the nature of computing. In the course of this development computing models have been extended from the initial abstract symbol manipulating mechanisms of stand-alone, discrete sequential machines, to the models of natural computing in the physical world, generally concurrent asynchronous processes capable of modelling living systems, their informational structures and dynamics on both symbolic and (...) sub-symbolic information processing levels. Present account of models of computation highlights several topics of importance for the development of new understanding of computing and its role: natural computation and the relationship between the model and physical implementation, interactivity as fundamental for computational modelling of concurrent information processing systems such as living organisms and their networks, and the new developments in logic needed to support this generalized framework. Computing understood as information processing is closely related to natural sciences; it helps us recognize connections between sciences, and provides a unified approach for modeling and simulating of both living and non-living systems. (shrink)