@techreport{GagrčinSchaetzRakowskietal.2021,
  author    = {Gagrčin, Emilija and Schaetz, Nadja and Rakowski, Niklas and Toth, Roland and Renz, Andr{\´e} and Vladova, Gergana and Emmer, Martin},
  title     = {We and AI},
  publisher = {Weizenbaum Institute for the Networked Society - the German Internet},
  address   = {Berlin},
  doi       = {10.34669/wi/1},
  pages     = {70},
  year      = {2021},
  language  = {en}
}
@article{WeyerTiberiusBicanetal.2021,
  author    = {Weyer, Julia and Tiberius, Victor and Bican, Peter and Kraus, Sascha},
  title     = {Digitizing grocery retailing},
  series = {International journal of innovation and technology management},
  volume    = {17},
  journal   = {International journal of innovation and technology management},
  number    = {08},
  publisher = {World Scientific Publishing},
  address   = {Singapore},
  issn      = {0219-8770},
  doi       = {10.1142/S0219877020500583},
  year      = {2021},
  abstract  = {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.},
  language  = {en}
}
@incollection{ThimGrumSchueffleretal.2021,
  author    = {Thim, Christof and Grum, Marcus and Sch{\"u}ffler, Arnulf and Roling, Wiebke and Kluge, Annette and Gronau, Norbert},
  title     = {A concept for a distributed Interchangeable knowledge base in CPPS},
  series = {Towards sustainable customization: cridging smart products and manufacturing systems},
  booktitle = {Towards sustainable customization: cridging smart products and manufacturing systems},
  editor    = {Andersen, Ann-Louise and Andersen, Rasmus and Brunoe, Thomas Ditlev and Larsen, Maria Stoettrup Schioenning and Nielsen, Kjeld and Napoleone, Alessia and Kjeldgaard, Stefan},
  publisher = {Springer},
  address   = {Cham},
  isbn      = {978-3-030-90699-3},
  doi       = {10.1007/978-3-030-90700-6_35},
  pages     = {314 -- 321},
  year      = {2021},
  abstract  = {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.},
  language  = {en}
}
@article{EbersHochRosenkranzetal.2021,
  author    = {Ebers, Martin and Hoch, Veronica R. S. and Rosenkranz, Frank and Ruschemeier, Hannah and Steinr{\"o}tter, Bj{\"o}rn},
  title     = {The European Commission's proposal for an Artificial Intelligence Act},
  series = {J : multidisciplinary scientific journal},
  volume    = {4},
  journal   = {J : multidisciplinary scientific journal},
  number    = {4},
  publisher = {MDPI},
  address   = {Basel},
  issn      = {2571-8800},
  doi       = {10.3390/j4040043},
  pages     = {589 -- 603},
  year      = {2021},
  abstract  = {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).},
  language  = {en}
}