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Dilemmas of artificial intelligence development - sociological considerations around industry 4.0 and sustainability

Suchacka Małgorzata, Horáková Nicole

Quality Production Improvement - QPI

2020

Vol. 2, Iss. 1

87--94

Ongoing progress in the introduction of new technologies, rapid social adaptation to the fourth industrial revolution, implementation of new solutions related to information and communication become incentives to conduct interdisciplinary scientific analyses. The following paper is a review article and the presented analysis to a large extent is based on theoretical considerations referring to studies of other authors. Presenting the sources of this notion in the context of industry 4.0 and sustainable development is a foundation for possible further experimental research. However, the primary aim of this article is to demonstrate the sources of scientific interest in artificial intelligence, directions of research on this notion and potential sociological research areas related to AI. Another goal of this article is to indicate the implications that can be used in planned research projects. The scope of the analysis is largely based on the study of literature.

Towards artificial intelligence. Sociological reflections on the relationship man - organization - device

Suchacka Małgorzata, Horáková Nicole

System Safety : Human - Technical Facility - Environment

2019

Vol. 1, nr 1

912--920

The main goal of the study will be to pay attention to technologization of the learning process and its social dimensions in the context of artificial intelligence. The reflection will mainly cover selected theories of learning and knowledge management in the organization and its broadly understood environment. Considering the sociological dimensions of these phenomena is supposed to lead to the emphasis on the importance of the security of the human-organization-device relationship. Due to the interdisciplinary nature of the issue, the article will include references to the concept of artificial intelligence and machine learning. Difficult questions will arise around the ideas and will become the conclusion of the considerations.