Standards provide a consistent framework for developers and regulators, ensuring the broad applicability, interoperability, and trustworthiness of new technologies. Artificial intelligence (AI) is no exception. Multiple national and international organizations are actively developing AI standards to support these goals. The Applied Machine Learning (AML) research group plays an active role in shaping these efforts across various domains and levels.
On the national level, members of the AML group have contributed to the DIN/DKE German AI Standardization Roadmap. More than 300 experts have collaborated in working groups covering topics such as industrial automation, mobility and logistics, medicine, ethics, and quality and certification.
Internationally, AML group members are engaged in several key initiatives. For example, they participate in the “Global Initiative on Resilience to Natural Hazards through AI Solutions”, led by multiple UN agencies. This initiative is developing a roadmap for the effective and secure use of AI in managing natural disasters such as floods, avalanches, and heat waves, focusing on areas including data collection and management, improved modelling across spatiotemporal scales, and effective communication.
Additionally, AML members contribute to the Global Initiative on AI for Health, previously the Focus Group on "AI for Health", a joint project of the International Telecommunication Union (ITU) and the World Health Organization (WHO) with the goal to create a standardized assessment framework for AI methods in healthcare.