An Occupational Safety and Health Perspective on Human in Control and AI.

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.

Evaluation of Trueness and Precision of a Bench-Top Laboratory Glucose Analyzer Using Reference Materials.

SUPER GL compact is a bench-top analyzer for glucose, lactate, and hemoglobin concentrations. Glucose measurements in the biosensor are based on an enzymatic-amperometric reaction of glucose with glucose oxidase.In this study, trueness and precision were assessed with Standard Reference Material 965b (National Institute of Standards and Technology, Gaithersburg, MD) for 2 SUPER GL compact (S1 and S2) and 1 YSI 2300 STAT Plus (Y) device, using a protocol based on CLSI EP05-A3.Precision was similar among S1, S2, and Y. S1 and S2 exhibited negative bias at low concentrations and positive bias at high concentrations, whereas Y showed negative bias that increased with higher concentrations. Overall, SUPER GL compact's performance was comparable to that of YSI 2300 STAT Plus.

The YSI 2300 Analyzer Replacement Meeting Report.

This is a summary report of the most important aspects discussed during the YSI 2300 Analyzer Replacement Meeting. The aim is to provide the interested reader with an overview of the complex topic and propose solutions for the current issue. This solution should not only be adequate for the United States or Europe markets but also for all other countries. The meeting addendum presents three outcomes of the meeting.