The continuous and rapid development of AI-based systems comes along with an increase in automation of tasks and, therewith, a qualitative shift in opportunities and challenges for occupational safety and health. A fundamental aspect of humane working conditions is the ability to exert influence over different aspects of one's own work. Consequently, stakeholders contribute to the prospect of maintaining the workers' autonomy albeit increasing automation and summarize this aspiration with the human in control principle. Job control has been part of multiple theories and models within the field of occupational psychology. However, most of the models do not include specific technical considerations nor focus on task but rather on job level. That is, they are possibly not able to fully explain specific changes regarding the digitalization of tasks. According to the results of a large-scale study on German workers (DiWaBe), this seems to be the case to some extend: the influence of varying degrees of automation, moderated by perceived autonomy, on workers' wellbeing was not consistent. However, automation is a double-edged sword: on a high level, it can be reversely related to the workers' job control while highly autonomous and reliable systems can also create opportunities for more flexible, impactful and diverse working tasks. Consequently, automation can foster and decrease the factor of job control. Models about the optimal level of automation aim to give guidelines on how the former can be achieved. The results of the DiWaBe study indicate that automation in occupational practice does not always happen in line with these models. Instead, a substantial part of automation happens at the decision-making level, while executive actions remain with the human. From an occupational safety and health perspective, it is therefore crucial to closely monitor and anticipate the implementation of AI in working systems. Constellations where employees are too controlled by technology and are left with a high degree of demands and very limited resources should be avoided. Instead, it would be favorable to use AI as an assistance tool for the employees, helping them to gather and process information and assisting them in decision-making.
Using a real workplace as an example, this paper describes how digital human modelling software facilitates planning and simulating work processes. This is closely connected to the ongoing activities and results from the SOPHIA project in which the inferred parameters are used for ergonomic assessments. Moreover, multiple options for digital human modelling, developed in the SOPHIA project, will be presented. In this context, the development process of personalized human models within the project to optimize the worker’s ergonomics when performing tasks with a robotic system or exoskeleton will be described. The paper closes with a short description of what still needs to be addressed to ensure personalized, reliable and robust digital human modelling for an industrial setting.Practical Relevance: This paper shows the scientific process within the SOPHIA project on the subject of digital human models. This provides an overview of the current state of research, as well as available and innovative approaches for modelling people at the workplace. It is shown to what extent the goal of creating personalized human models to optimize the ergonomics of employees that work with robotic systems or exoskeletons has already been achieved. Therewith, it is displayed which developments can already be used and which components are still missing in order to better simulate and thus enrich the interaction between humans and robots/exoskeletons.
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