Artificial intelligence in application: Legal aspects, application potentials and use scenariosКНИГИ » ПРОГРАММИНГ
Название: Artificial Intelligence in application: Legal aspects, application potentials and use scenarios Автор: Thomas Barton, Christian Muller Издательство: Springer Год: 2024 Страниц: 197 Язык: английский Формат: pdf (true), epub Размер: 15.0 MB
The book shows application potentials of Artificial Intelligence (AI) in various industries and presents application scenarios on how a practical implementation can take place. The starting point is the description of legal aspects, which includes a European regulation for Artificial Intelligence and addresses the question of the permissibility of automated decisions. The description of various application potentials, mostly industry-related, and the presentation of some application scenarios form the focus of the topic volume.
Four mobility scenarios, in which cars are privately owned or shared on the one hand and are driven by a driver or move autonomously on the other, are changing the most important business processes in the automotive trade, such as car sales, maintenance, repairs and used car purchases. In all processes, application scenarios for the Artificial Intelligence (AI) subfields computer vision, natural language processing (NLP) and machine learning can be identified. The analysis shows that the current degree of implementation varies widely, from the already widespread predictive maintenance in maintenance, to the first approaches of computer vision for diagnosis in repair and used car purchase, to the still novel use of chatbots in consulting and Machine Learning in recommendation processes. For car dealers, the question arises of specialization, e.g. as a service factory or for the fleet management of a mobility service provider, each of which requires different AI scenarios.
Machine Learning and neural networks are very present due to spectacular results. There is a rapidly increasing number of applications that make use of their methods. There is a veritable euphoria that by analyzing very extensive data sets with Machine Learning or neural network methods, it should be possible to solve almost any problem. As so-called black-box AI, these methods have the disadvantage that an explanation for the occurrence of a result is not possible or only possible to a limited extent. In comparison, in the natural sciences and especially in physics it is not only self-evident but even indispensable to explain scientific phenomena on the basis of cause and effect. The mathematical methods of statistical inference offer the opportunity to introduce causal thinking in the form of Artificial Intelligence methods even in scientific disciplines in which explanations based on cause and effect have not previously been considered indispensable. An example of this is the subject area of marketing.
The book is based on the question of how Artificial Intelligence can be used in entrepreneurial practice. It offers important information that is just as relevant for practitioners as for students and teachers.
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