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DTSTART;TZID=Europe/Helsinki:20230505T080000
DTEND;TZID=Europe/Helsinki:20230506T170000
DTSTAMP:20260406T103846
CREATED:20230322T111543Z
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SUMMARY:European Traditions of Philosophy of Science: Unexpected Varieties
DESCRIPTION:Workshop organized by \nc:o/re\, Aachen University & Dr. Andrei Mărășoiu \nTo understand the context-sensitive justificatory practices at work in scientific pursuits\, an understanding of research cultures and the variation therein is necessary. In this light\, this workshop addresses the interaction between logic and metaphysical models in scientific practices and social and cultural approaches to these practices. \nIn criticism of Western-centric or Eurocentric tendencies in the sociology and historiography of science\, we aim to better evince the many varieties of knowledge by focusing on certain regional philosophical schools within the European continent. By exploring local pluralities of knowledge production\, we aim to reflect on the usefulness or irrelevance of distinctions between Western\, Central and Eastern European philosophy. \nA currently important debate where knowledge systems may display their different metaphysical underpinnings revolves around articulating the idea of formal resources needed to lay the foundations of the scientific enterprise. By tackling such concerns\, the workshop is poised to join historians\, philosophers\, and sociologists of science\, representing distinct schools of thought\, to reflect on epistemic practices and current trends in the philosophy and sociology of science. \nThe event will be hosted by the Faculty of Philosophy at the University of Bucharest  \nFull Program can be found here. \nThis Workshop is part of c:o/re Series Varieties of Science \n \n 
URL:https://khk.rwth-aachen.de/event/european-traditions-of-philosophy-of-science-unexpected-varieties/
LOCATION:University of Bucharest\, Splaiul Independenței nr. 204\, București\, 060024\, Romania
CATEGORIES:Workshops
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ORGANIZER;CN="c%3Ao/re":MAILTO:events@khk.rwth-aachen.de
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BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20230510T170000
DTEND;TZID=Europe/Helsinki:20230510T183000
DTSTAMP:20260406T103846
CREATED:20230301T113338Z
LAST-MODIFIED:20260116T104132Z
UID:5920-1683738000-1683743400@khk.rwth-aachen.de
SUMMARY:Neither Good nor Old-Fashioned: On the Curious Complexity of Soviet AI - Benjamin Peters
DESCRIPTION:“Neither Good nor Old-Fashioned: On the Curious Complexity of Soviet AI” by Benjamin Peters (University of Tulsa). \nAbstract: \nThis public talk will explore the material media philosophies of Soviet artificial intelligence research and its precursors. In particular\, it will examine the case for not-anthropomorphic\, even invisual imaginations of smart technologies in the wartime wake of the Soviet experience with damaged bodies. \nBenjamin Peters is Hazel Rogers Associate Professor and former Chair of the Department of Media Studies at the University of Tulsa with appointments in the School of Cyber Studies and Russian Studies Program. He is also affiliated fellow at the Information Society Project at Yale Law School and alumnus of Columbia’s Communication PhD program in 2010. He is the author of How Not to Network a Nation: the Uneasy History of the Soviet Internet (MITP 2016\, winner of three awards in three fields)\, editor of Digital Keywords: A Vocabulary of Information Society & Culture (Princeton UP 2016)\, and coeditor of Your Computer is on Fire (MITP 2021). He has published extensively across the fields of media theory and history\, the transnational history and philosophy of information technology & society\, and technology criticism with an emphasis on the causes and consequences of the information age in the Soviet century. He is currently conducting research on alternative genealogies of artificial intelligence. \nThis event is part of our summer semester 2023 lecture series “Complexity“.
URL:https://khk.rwth-aachen.de/event/lecture-series-complexity-benjamin-peters/
LOCATION:Stadtpalais/Online\, Theaterstraße 75\, Aachen\, 52062\, Germany
CATEGORIES:Lecture Series,Lecture Series 2024
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ORGANIZER;CN="c%3Ao/re":MAILTO:events@khk.rwth-aachen.de
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DTSTART;TZID=Europe/Helsinki:20230517T170000
DTEND;TZID=Europe/Helsinki:20230517T183000
DTSTAMP:20260406T103846
CREATED:20230301T113509Z
LAST-MODIFIED:20260116T104125Z
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SUMMARY:Complexity – From Natural and Social Sciences to Artificial Intelligence - Klaus Mainzer
DESCRIPTION:“Complexity – From Natural and Social Sciences to Artificial Intelligence” – Klaus Mainzer (TU Munich). \nAbstract: \nAccording to several prominent authors\, including Stephen Hawking\, a main part of 21st century science will be on complexity research. The intuitive idea is that global patterns and structures emerge from locally interacting elements like atoms in laser beams\, molecules in chemical reactions\, proteins in cells\, cells in organs\, neurons in brains\, transistors in electronic systems etc. (Mainzer 2007). Complex pattern formation has been reported from many disciplines (e.g.\,  physics\, chemistry\, biology\, brain research\, engineering). The causes of complex pattern formation have been analyzed from various perspectives such as Schrödinger’s (1948) order from disorder\, Prigogine’s (1980) dissipative structure\, Haken’s (1983) synergetics\, Langton’s (1990) edge of chaos etc. But concepts of complexity are often based on examples or metaphors only. We argue for a mathematically precise and rigorous definition of local activity as the cause of complex pattern formation which can be tested in natural as well as technical sciences by constructive methods. \nRecently\, these results of complexity research have become important for machine learning of AI (artificial intelligence) systems (e.g.\, neural networks\, cognitive AI-systems\, robots). Instead of complex pattern formation in nature\, complex pattern recognition of AI-systems is considered which is modeled in statistical learning theory. But statistical correlations of data cannot replace causal explanations of events. Algorithms of causal learning are necessary to detect causal models behind the statistical distributions of data. Causal learning would be a first step from weak AI with probabilistic learning to strong AI. \nReferences: K. Mainzer\, Thinking in Complexity\, Springer: Berlin 5th edition 2007; K. Mainzer/L. Chua\, Local Activity Principle. The Cause of Complexity\, World Scientific Singapore 2013; K. Mainzer\, Artificial Intelligence. When do Machines take over? Springer: Berlin 2nd edition 2019; K. Mainzer/ R. Kahle\, Grenzen der Künstlichen Intelligenz – theoretisch\, praktisch\, ethisch\, Springer. Berlin 2022. \nKlaus Mainzer is professor emeritus at the Technical University Munich of the School of Social Sciences and Technology. While obtaining a PhD in the philosophy of the basics of mathematics\, more precisely constructive and algorithmically grounded procedures\, he habilitated on their application in geometry and physics. He is a member of The Academy of Europe (Academy Europaea)/London\, the European Academy of Science and Arts\, the German Academy of Science of Technology\, president of the German-Japanese Society for Integrative Science and board member of the Udo Keller Stiftung (Hamburg). From the vantage point of contemplating the computability of the world\, he works as a science philosopher of the foundations and future perspectives of science and technology and as a complexity researcher focussed on complex systems in nature\, technology\, economy and society\, as well as the foundations of AI and Big Data. His research seeks for constructively founded solutions\, methods and evidentiary procedures which allow to control the algorithmization and digitalization of technology and society. \nThis event is part of our summer semester 2023 lecture series “Complexity“.
URL:https://khk.rwth-aachen.de/event/lecture-series-complexity-klaus-mainzer/
LOCATION:Stadtpalais/Online\, Theaterstraße 75\, Aachen\, 52062\, Germany
CATEGORIES:Lecture Series,Lecture Series 2024
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