This article argues for an updated theoretical framework in fashion studies. It proposes that perspectives emphasizing the social role and the technological nature of dress should be considered complementary, and that their joint application can contribute to new understandings of fashion history. Employing ethnographic methods, this stance is explored through a comparative analysis of the sartorial practices of two groups of women living or working in Amsterdam during the 1950s and the 2010s. A theoretical framework integrating theories of identity (mainly based on the writings of Georg Simmel and Gabriel Tarde) and the philosophy of technology (in this case the device paradigm of Albert Borgmann) allows us to uncover a paradoxical history of fashion in which clothing shifts roles, transforming from “things of imitation” into “devices of differentiation.”
The idea that technologies influence society—both positively and negatively—is not new. This is mainly the terrain of the philosophy and the ethics of technolo-gy research. Similarly, design research aims to help create new technologies in line with individual, social, and societal needs and values. Against this backdrop, it seems essential to expose relations between design and philosophy of tech-nology research, particularly from a methodological perspective. The main goal of this paper is to suggest a preliminary overview of methods and approaches that can inspire and inform interdisciplinary collaboration and, with that, sys-tematic engagement with ethics in design processes. Through interdisciplinary exchange, we propose a preliminary typology of ethics-informed methods and approaches based on two main dimensions, namely theory-grounded approaches to theoretically-flexible techniques and assessment to accompaniment. This mapping intends to help navigate the ethical qualities of selected methods from both disciplines, and it aims to create a platform for fruitful interdisciplinary conversations.
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The idea that technologies influence society—both positively and negatively—is not new. This is mainly the terrain of the philosophy and the ethics of technolo-gy research. Similarly, design research aims to help create new technologies in line with individual, social, and societal needs and values. Against this backdrop, it seems essential to expose relations between design and philosophy of tech-nology research, particularly from a methodological perspective. The main goal of this paper is to suggest a preliminary overview of methods and approaches that can inspire and inform interdisciplinary collaboration and, with that, sys-tematic engagement with ethics in design processes. Through interdisciplinary exchange, we propose a preliminary typology of ethics-informed methods and approaches based on two main dimensions, namely theory-grounded approaches to theoretically-flexible techniques and assessment to accompaniment. This mapping intends to help navigate the ethical qualities of selected methods from both disciplines, and it aims to create a platform for fruitful interdisciplinary conversations.
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The focus of the research is 'Automated Analysis of Human Performance Data'. The three interconnected main components are (i)Human Performance (ii) Monitoring Human Performance and (iii) Automated Data Analysis . Human Performance is both the process and result of the person interacting with context to engage in tasks, whereas the performance range is determined by the interaction between the person and the context. Cheap and reliable wearable sensors allow for gathering large amounts of data, which is very useful for understanding, and possibly predicting, the performance of the user. Given the amount of data generated by such sensors, manual analysis becomes infeasible; tools should be devised for performing automated analysis looking for patterns, features, and anomalies. Such tools can help transform wearable sensors into reliable high resolution devices and help experts analyse wearable sensor data in the context of human performance, and use it for diagnosis and intervention purposes. Shyr and Spisic describe Automated Data Analysis as follows: Automated data analysis provides a systematic process of inspecting, cleaning, transforming, and modelling data with the goal of discovering useful information, suggesting conclusions and supporting decision making for further analysis. Their philosophy is to do the tedious part of the work automatically, and allow experts to focus on performing their research and applying their domain knowledge. However, automated data analysis means that the system has to teach itself to interpret interim results and do iterations. Knuth stated: Science is knowledge which we understand so well that we can teach it to a computer; and if we don't fully understand something, it is an art to deal with it.[Knuth, 1974]. The knowledge on Human Performance and its Monitoring is to be 'taught' to the system. To be able to construct automated analysis systems, an overview of the essential processes and components of these systems is needed.Knuth Since the notion of an algorithm or a computer program provides us with an extremely useful test for the depth of our knowledge about any given subject, the process of going from an art to a science means that we learn how to automate something.
