TY - RPRT A1 - Gagrčin, Emilija A1 - Schaetz, Nadja A1 - Rakowski, Niklas A1 - Toth, Roland A1 - Renz, André A1 - Vladova, Gergana A1 - Emmer, Martin T1 - We and AI BT - living in a datafied world : experiences & attitudes of young Europeans KW - sociology & anthropology KW - technology (applied sciences) KW - sociology of science KW - sociology of technology KW - research on science and technology KW - technology assessment KW - artificial intelligence KW - digitalization KW - educational technology KW - decision making KW - data security KW - monitoring KW - data protection KW - automation KW - Europe KW - attitude KW - young adult KW - technological change KW - new technology Y1 - 2021 U6 - https://doi.org/10.34669/wi/1 PB - Weizenbaum Institute for the Networked Society - the German Internet CY - Berlin ER - TY - JOUR A1 - Weyer, Julia A1 - Tiberius, Victor A1 - Bican, Peter A1 - Kraus, Sascha T1 - Digitizing grocery retailing BT - the role of emerging technologies in the value chain JF - International journal of innovation and technology management N2 - Multiple emerging technologies both threaten grocers and offer them attractive opportunities to enhance their value propositions, improve processes, reduce costs, and therefore generate competitive advantages. Among the variety of technological innovations and considering the scarcity of resources, it is unclear which technologies to focus on and where to implement them in the value chain. To develop the most probable technology forecast that addresses the application of emerging technologies in the grocery value chain within the current decade, we conduct a two-stage Delphi study. Our results suggest a high relevance of almost all technologies. The panel is only skeptical about three specific projections. As a consequence, grocers are advised to build up knowledge regarding the application of these technologies in the most promising areas of their value chain. KW - Delphi study KW - technological forecasting KW - grocery retailing KW - artificial intelligence KW - augmented reality KW - big data analytics KW - blockchain technology KW - drones KW - RFID Y1 - 2021 U6 - https://doi.org/10.1142/S0219877020500583 SN - 0219-8770 SN - 1793-6950 VL - 17 IS - 08 PB - World Scientific Publishing CY - Singapore ER - TY - CHAP A1 - Thim, Christof A1 - Grum, Marcus A1 - Schüffler, Arnulf A1 - Roling, Wiebke A1 - Kluge, Annette A1 - Gronau, Norbert ED - Andersen, Ann-Louise ED - Andersen, Rasmus ED - Brunoe, Thomas Ditlev ED - Larsen, Maria Stoettrup Schioenning ED - Nielsen, Kjeld ED - Napoleone, Alessia ED - Kjeldgaard, Stefan T1 - A concept for a distributed Interchangeable knowledge base in CPPS T2 - Towards sustainable customization: cridging smart products and manufacturing systems N2 - As AI technology is increasingly used in production systems, different approaches have emerged from highly decentralized small-scale AI at the edge level to centralized, cloud-based services used for higher-order optimizations. Each direction has disadvantages ranging from the lack of computational power at the edge level to the reliance on stable network connections with the centralized approach. Thus, a hybrid approach with centralized and decentralized components that possess specific abilities and interact is preferred. However, the distribution of AI capabilities leads to problems in self-adapting learning systems, as knowledgebases can diverge when no central coordination is present. Edge components will specialize in distinctive patterns (overlearn), which hampers their adaptability for different cases. Therefore, this paper aims to present a concept for a distributed interchangeable knowledge base in CPPS. The approach is based on various AI components and concepts for each participating node. A service-oriented infrastructure allows a decentralized, loosely coupled architecture of the CPPS. By exchanging knowledge bases between nodes, the overall system should become more adaptive, as each node can “forget” their present specialization. KW - learning KW - distributed knowledge base KW - artificial intelligence KW - CPPS Y1 - 2021 SN - 978-3-030-90699-3 SN - 978-3-030-90702-0 SN - 978-3-030-90700-6 U6 - https://doi.org/10.1007/978-3-030-90700-6_35 SP - 314 EP - 321 PB - Springer CY - Cham ER - TY - JOUR A1 - Ebers, Martin A1 - Hoch, Veronica R. S. A1 - Rosenkranz, Frank A1 - Ruschemeier, Hannah A1 - Steinrötter, Björn T1 - The European Commission’s proposal for an Artificial Intelligence Act BT - a critical assessment by members of the Robotics and AI Law Society (RAILS) JF - J : multidisciplinary scientific journal N2 - On 21 April 2021, the European Commission presented its long-awaited proposal for a Regulation “laying down harmonized rules on Artificial Intelligence”, the so-called “Artificial Intelligence Act” (AIA). This article takes a critical look at the proposed regulation. After an introduction (1), the paper analyzes the unclear preemptive effect of the AIA and EU competences (2), the scope of application (3), the prohibited uses of Artificial Intelligence (AI) (4), the provisions on high-risk AI systems (5), the obligations of providers and users (6), the requirements for AI systems with limited risks (7), the enforcement system (8), the relationship of the AIA with the existing legal framework (9), and the regulatory gaps (10). The last section draws some final conclusions (11). KW - artificial intelligence KW - machine learning KW - European Union KW - regulation KW - harmonization KW - Artificial Intelligence Act Y1 - 2021 U6 - https://doi.org/10.3390/j4040043 SN - 2571-8800 VL - 4 IS - 4 SP - 589 EP - 603 PB - MDPI CY - Basel ER -