Towards a practical framework to "ethics by design" data sharing and machine learning applications

Responsible AI and data-driven applications can only be developed when teams integrate the ethical principles directly into the development process. An important prerequisite is the involvement of a diverse group of stakeholders who build and are affected by AI and data systems. We present a practical framework that helps teams build trustworthy AI systems and data strategies by combining expertise and training from philosophy, law, machine learning and design.

These Slides were presented in the context of the "A first approach to an ELSA Curriculum for Data Scientists-The FAIR Data Spaces Project as a Use Case " Workshop, which took place on 14.6.2023, online and was organized in the context of the BMBF Fair Data Spaces project.