As humans, we use the power of thinking to make scientific discoveries, develop technologies, manage social interactions, and transmit knowledge to the next generations. With the ability to think, we can trace back and discover the origin of the universe, the natural world, and ourselves. The content of this book, Mindsponge Theory, is part of that discovery process. -/- Product Details -/- Publisher ‏ : ‎ Walter de Gruyter (December 6, 2022) Publication date ‏ : ‎ December 6, 2022 Language (...) ‏ : ‎ English Hardcover ‏ : ‎ 214 pages ISBN-10 ‏ : ‎ 8367405145 ISBN-13 ‏ : ‎ 978-8367405140 Dimensions ‏ : ‎ 6.3 x 0.71 x 9.29 inches -/- . (shrink)

This paper examines the development and technological mediation of the concept of solidarity. We focus on the workplace as a focal point of solidarity relations, and utilise a phenomenological approach to describe and analyse those relations. Workplace solidarity, which has been historically concretised through social objects such as labor unions, is of particular political relevance since it has played an outsize role in the broader struggle for social, economic, and political rights, recognition, and equality. We argue that the use of (...) automated decision support systems in labor process management may negatively affect the formation of these relations. As solidarity motivates collective political action and risk-taking, the mediation and potential obstruction of solidarity relations by ADS is politically significant. We contribute to the growing literature on the “future of work” problem in elucidating the technological mediation of workplace solidarity. (shrink)

This article considers the issue of opacity as a problem for socially consequential mechanisms of classification and ranking, such as spam filters, credit card fraud detection, search engines, news trends, market segmentation and advertising, insurance or loan qualification, and credit scoring. These mechanisms of classification all frequently rely on computational algorithms, and in many cases on machine learning algorithms to do this work. In this article, I draw a distinction between three forms of opacity: opacity as intentional corporate or state (...) secrecy, opacity as technical illiteracy, and an opacity that arises from the characteristics of machine learning algorithms and the scale required to apply them usefully. The analysis in this article gets inside the algorithms themselves. I cite existing literatures in computer science, known industry practices, and do some testing and manipulation of code as a form of lightweight code audit. I argue that recognizing the distinct forms of opacity that may be coming into play in a given application is a key to determining which of a variety of technical and non-technical solutions could help to prevent harm. (shrink)