مقاله انگلیسی رایگان در مورد هوش مصنوعی در عوامل انسانی و کارپژوهی – اسپرینگر 2021

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Abstract

The development of artificial intelligence (AI) technologies continues to advance. To fully exploit the potential, it is important to deal with the topics of human factors and ergonomics, so that a smooth implementation of AI applications can be realized. In order to map the current state of research in this area, three systematic literature reviews with different focuses were conducted. The seven observation levels of work processes according to Luczak and Volpert (1987) served as a basis. Overall n = 237 sources were found and analyzed. It can be seen that the research critically deals with human-centered, effective as well as efficient work in relation to AI. Research gaps, for example in the areas of corporate education concepts and participation and voice, identify further needs in research. The author postulates not to miss the transition between forecasts and verifiable facts.

Introduction

The term artificial intelligence (AI) is not new. In 1956, the research discipline of AI was founded at the Dartmouth Conference in New Hampshire [1]. Since then, this technology has become a relevant application in academia as well as in private and work contexts. It has been called the next universal technology after the steam engine, electrification, and the Internet [2, 3]. The 2018 PR Neswire study forecasts the AI market to grow from USD 21.46 billion in 2018 to USD 190 billion by 2025 [4]. Moreover, from 2011 to 2017 alone, AI funding for startups increased 50-fold [5]. Chatbots or virtual agents as AI applications are currently used by many companies as a means of communication with customers. In production, in addition to digitization approaches, smart factories are also being enhanced with AI applications to make processes even faster and more effective.

Since there is no generally valid definition for human intelligence, there is no such definition for AI either. In research, a distinction is often made between weak and strong AI. This definition is difficult for current research in that there are no strong AI technologies yet and such a development must be awaited [6]. Often, the literature talks about methodologies of AI technologies, such as machine learning (ML) or deep learning (DL). For the current state of research presented in this paper, care was taken not to include studies in the field of automation only. In studies on AI, whether weak or strong, ML and DL were accepted.

However, in order to be able to use the potential of AI technologies in a meaningful way, including the aspects of human factors and ergonomics plays an important role [7,8,9]. These research areas aim to design a working system that is both humane and effective and efficient. Here effectiveness and efficiency represent the results of humane working conditions [7]. When work processes and conditions change through the use of AI applications, it is important to help shape such applications from an occupational science perspective, to accompany the changes and to develop and implement concepts for humane design. In the last few years, several AI failures have occurred that might have been prevented or minimalized if the above aspects had been considered before implementation. The lexalytics.com website features various failures, including chatbots, political gaffs, autonomous driving accidents, facial recognition mixups, and angry neighbors. A good example is a developed AI by Amazon that was supposed to support the selection of new employees and became anti-women based on the training data [10].