Transdisciplinary Views on Data and Data Practices

The notion of data is fundamental to the discussion on artificial intelligence (AI), especially within the WASP-HS network. Ethics, regulations, norms, and classification practices, access points, and knowledge modeling are a few of the areas where data emerges as material for reflection, exploration, and critique. This workshop draws from the multiplicity of expertise and epistemological stances within the WASP-HS network and seeks to establish areas of discussion, and critique along the themes of the nature of the data, the processes of data handling, the theories, methods and experiences of data collection and expression, and the risks, tensions, and stumbling blocks of working with data.

The workshop includes two rounds and modes of work. The first part focuses on the present and the participants’ research approaches to data-driven practices. During this part, the themes of the workshop are discussed, and participants have a chance to contribute with their experience, perspective, and positionality. The second part is future-oriented, seeking to explore the future agenda of data-driven matters in artifical intelligence as identified by this group of WASP-HS researchers.

There are no requirements and preparation for participation. Everyone is welcome to participate and contribute with their own experiences and expertise.