Junior Research Group on Artificial Intelligence (AI)

The application of artificial Intelligence (AI) is one of the major scientific and technological challenges of our time. AI is expected to bring about far-reaching, even revolutionary transformations in many domains of life – especially in the world of work.

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Like other technological innovations, the application of AI offers opportunities and poses risks for human centered work design. Building competencies is therefore particularly important as a basis to be able to address AI systems at the levels of academic research, regulation, and workplace practice.

With the establishment of its Junior Research Group on Artificial Intelligence (AI) in a Safe and Healthy World of Work, the Federal Institute for Occupational Safety and Health (Bundesanstalt für Arbeitsschutz und Arbeitsmedizin, BAuA) has started laying the academic foundations for the competences that will be needed. The Junior Research Group is being funded by the AI Observatory of the Policy Lab Digital, Work and Society, part of the Federal Ministry of Labour and Social Affairs (Bundesministerium für Arbeit und Soziales, BMAS). The Group’s research activities in the AI field are focussed on safety and health at work, with attention being paid to various aspects of two main topics - "Machinery Safety and AI", as well as "AI and its Sociotechnical Effects". The issues addressed include:

  • Risk assessment of machines and work systems, AI risk management
  • Formulation of specifications, design principles for work tools and their use, implementation through standards and norms
  • Information and findings for European and international standardisation activities
  • Monitoring and opportunities to apply AI
  • Technology assessment
  • Effects, opportunities, and risks for employers and individuals, workplace parameters, organisation
  • Options for the application of AI in occupational safety and health and work design

The Junior Research Group on AI is embedded in several of BAuA’s cooperative networks, such as the Research Alliance Ruhr with the Research Center Trustworthy Data Science and Security, as well as a range of collaborative arrangements with university institutes and professorial chairs. It seeks to define concrete research questions connected with the issues listed above, which are then examined in doctoral projects.

Further BAuA projects on AI in the world of work

Project "Overview of Policies, Research and Practices in Relation to Advanced Robotics and AI-based Systems for Automation of Tasks and Occupational Safety and Health"

A range of reports and policy briefings on the latest developments in research into, and the application of, robotic and AI-based systems in the workplace have been published as part of a project funded by EU-OSHA. Among other things, they address recent research results relating to AI applications and their impacts on safety and health at work. Furthermore, the project has involved drawing up case studies in which companies from all over Europe present the processes by which they develop and implement these technologies, expanding upon previous literature-based findings with their practical knowledge.

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Project "Potential Benefits of Artificial Intelligence for the Analysis of Occupational Safety Risks"

This project is looking at AI-based systems as tools for occupational safety and health. The data available within organisations, explicable algorithms, and users’ interactions with such systems are among the challenges that have been encountered. Field access is currently being arranged with a large company, which will enrich the often theoretical findings arrived at to date by comparing them what is happening in the real world. Further details of the project can be found in the publications that discuss its results.

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Project "Safety-related risk assessment of a cyber-physical model system for industry 4.0 applications"

Cyber-physical systems (CPSs) are made up of mechanical components, software, and modern information technologies. The software components may consist of a variety of elements, including self-learning algorithms such as machine learning processes or forms of artificial intelligence (AI).

The risk analysis methods common in industrial practice are no longer capable of adequately evaluating such complex systems.

This project is therefore intended to investigate a modular, adaptable, networked production line and assess it using a range of quantitative risk analysis procedures. The aim is to generate practical recommendations about risk analysis that can later be drawn on for standardisation activities and other purposes. The project's results will therefore help ensure employees’ safety is assessed appropriately in emerging industry 4.0 scenarios.

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