The use of AI-based products and services in the economy, working life and society is expected to increase and lead to massive changes. These changes require sound analysis and evaluation at different levels.
By means of a series of measures, the Federal Ministry of Labour and Social Affairs (BMAS) is especially addressing the political challenges associated with work and society in dealing with AI. BMAS wants to ensure that the further development of AI applications is based on a broad social discussion process and is thus focused mainly on people and the common good. This is a key prerequisite for the successful spread of AI and enabling innovation potential to flourish (“investing at least as much in people as in technology”).
The AI Observatory, one of the outcomes of the Federal Government’s AI strategy, has a key role to play in this context. The tasks of the AI Observatory include observing, further developing and participating in shaping artificial intelligence in society and working and economic life. The development and operation of the AI Observatory is the responsibility of BMAS, where it is embedded in the structures of Policy Lab Digital, Work & Society.
The AI Observatory is seeking to engage in dialogue with experts from all areas of development and application of artificial intelligence as well as with members of the wider society. These include representatives of trade unions, businesses, academia, the media and civil society. The AI experimental spaces, the East and West future centres, and the Civic Technology model project are important interfaces within BMAS for the AI Observatory. At an international level, the direct cooperation partners include the European Commission/institutions of the European Union, the OECD and the International Labour Organization (ILO).
Tasks and goals at a glance:
Analysis and evaluation
Impact analysis, scenario development and trend monitoring in order to develop guidelines, audits and frameworks for action for the use of AI in the working world
Frameworks and AI benchmarking
Development of procedures and methods for the checking and traceability of algorithmic forecasting and decision-making systems
Participation and dialogue
Facilitate access to the issue of AI and social dialogue on it and enable cooperation with AI observatories at transnational level
Transparency and knowledge transfer
Guidelines, studies, documentation and practice cases in order to enhance skills and respond to key qualifications and qualification needs