There is a broad consensus that existing disciplinary education needs to incorporate education on artificial intelligence (AI) from different perspectives relevant for different professional domains to efficiently develop and integrate AI and other transformative technologies in routines and infrastructures that build society and the welfare services provided by societal organisations. Moreover, education on aspects relating to responsible AI design and development has been highlighted by the European Commission. It has also been reported that further development of interdisciplinary education will be needed to educate professionals in different domains for current and future needs of competence.

The aim of this paper is to report on a workshop with the goal to prepare for developing course syllabuses on AI across disciplines and academic institutions that would further develop Swedish education. A group of 13 researchers with a research focus on AI, of multiple backgrounds across primarily the social sciences and humanities, and across nine academic organisations, participated.

Five themes emerged during the first part of the workshop: AI, diversity and human rights; Educating on the foundations of AI; Pushing the boundaries of theories and methodology; Building better AI (systems); and Educating professionals within certain disciplines – changing professions. The themes were compiled into a blueprint of a 60-credit program on advanced level, which could be extended to a 120-credit master’s program. The program consists of four basic modules: Foundations of AI in Society; AI in the Wild, focusing challenges in society; Pushing Boundaries Building better AI, with a focus on research methodology; and a thesis module.

The workshop and development of the blueprint was funded and conducted as a part of the WASP-ED program funded by Wallenberg Foundations, a joint effort between The Wallenberg AI, Autonomous Systems and Software Program (WASP) and The Wallenberg AI, Autonomous Systems and Software Program - Humanity and Society (WASP-HS).

The program would follow certain pedagogical principles to align the content with societal needs and across courses in the program: i) learning by doing; ii) real world challenges; and iii) engaging stakeholders in the courses to ground education in real-world challenges. To realise learning by doing, clinics and labs throughout the courses would be applied as well as case-based and project-based learning, with increase in technical complexity over time.

To evaluate the blueprint, it was mapped to the WASP-ED AI Curriculum, and different opportunities to extend the blueprint into a master’s program were proposed. The next step is to describe the content of the topics, the dependencies and progression between the topics, and to identify subsets of topics providing suitable educational pathways for different practitioners and professions.

The blueprint can be used by educational institutes to further develop new courses and programs to further develop disciplinary education and foster multidisciplinary understanding of the challenges and opportunities of AI in society.