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Digitization: Learnings from Ancient Disruptions, AI and the Digital Trio’s Functional Stage, and AI Superpowers Disrupting Us

Stefan H. Vieweg ()
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Stefan H. Vieweg: RFH - University of Applied Sciences Cologne

Chapter 6 in AI for the Good, 2021, pp 95-142 from Springer

Abstract: Abstract “Digitization,” the buzzword of the 2010s, along with “disruption” characterizes a fundamental change to individuals and societies. Initially in this chapter, a little trust is built up by setting the current digital transformation into a historical context. Examples that show the potential and risks emerging from AI-based applications are discussed. Obviously, disruption is not new and key lessons can be learnt from the past. The “digital trio” (Robot Process Automation, blockchain, and quantum/supercomputing), i.e., digital technologies surrounding and contributing to AI, is explained for non-engineers and the performance is critically reflected. Using openly accessible AI platform Kaggle, a demonstration illustrates the output dependency on both key ingredients for AI: data and algorithms. Readers can immediately recheck calculation results themselves (without any software coding skills required): Based on a test dataset, different AI algorithms are used in an early warning system. It will be shown that even slight variations in the parametrization will lead to significantly different results. Obviously, this indicates a key problem of AI applications discussed as well in Part III, as misalignment on data and algorithms will ultimately lead to biased decisions and hence discrimination. The AI world emerged with an exponential pace. While there is a broad awareness of AI potential, for the last few years there is a clear duopoly on driving the AI agenda. The technologies used, the applications derived, and the impact on individuals’ and social lives will be illustrated by contrasting the two superpowers, the USA and China, in their approach to rule in the digital age. Despite the ethical consequences of the two very different endeavors, the USA with a so-called surveillance capitalism and China with the so-called market Leninism, there are massive implications not only on the social lives but as well on resource consumption, which provokes an exponential increase in energy demand (and with that realistically an increase in CO2) as well as costs.

Keywords: ADS; AI; BCT; Bitbucket; Bitcoin; Block chain technology; CCTV; Crypto currencies; Cryptograph; DAO; Digitization; Disruption; DLT; Facial detection; GAFAM; Github; Hash; Kaggle notebook; Market Leninism; Machine learning; Megvii; ML; Python; Optical character recognition; OCR; PKC; PKI; Qubits; Quantum computing; Robot process automation; RPA; RSA; SCIKIT-LEARN; SHA; Smart contracts; Supercomputing; Supervised learning; Surveillance capitalism; Unsupervised learning (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:mgmchp:978-3-030-66913-3_6

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DOI: 10.1007/978-3-030-66913-3_6

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