Work is changing. Who works, where and when they work, which tools they use, how they collaborate with others, how they are trained, and how work interacts with wellbeing – all these aspects of work are currently undergoing rapid shifts. A key source of changes in work is the advent of computational tools which utilize artificial intelligence (AI) technologies. AI will increasingly support workers in traditional and non-traditional environments as they perform manual-visual tasks as well as tasks that predominantly require cognitive skills.

Given this emerging landscape for work, the theme of this Dagstuhl Seminar is human-AI interaction for work in both traditional and non-traditional workplaces, and for heterogeneous and diverse teams of remote and on-site workers. We will focus on the following research questions:

1. How do we allocate tasks between humans and automation in practical settings?
2. How can interfaces allow for the appropriate level of human understanding of the roles of human and machine, for the appropriate trust in machines, and how can they reduce incorrect use and confusion?
3. How do we support user attention for different tasks, teams, and work environments?
4. How can human-automation interaction technology support both work and worker wellbeing?

At the seminar we will discuss these questions considering their interconnected nature. To promote this approach, we invite computer scientists/engineers, electrical engineers, human factors engineers, interaction designers, UI/UX designers, and psychologists from industry and academia to join this Dagstuhl Seminar.

We expect the following key results from the Dagstuhl Seminar:

1. Outline of best practices and pitfalls. Which current practices for creating human-AI interfaces lead to positive outcomes for workers? And what are the known pitfalls that designers should avoid?
2. List of challenges and hypotheses. Perhaps the most significant contribution of the seminar will be a list of important challenges, or research problems, and accompanying hypotheses. We expect that in the coming 3 to 10 years these problems and hypotheses will serve as inspiration for the research of the seminar attendees, and more broadly the communities involved in designing human-AI interfaces that support work.
3. Roadmap(s) for research. The seminar report will include a roadmap for addressing the challenges and hypotheses – the roadmap will outline proposed research collaborations, recommended funding mechanisms, and it will lay out plans for disseminating results such that members of our community are well-informed, and such that they can effectively interact with researchers and practitioners in related communities, including human-computer interaction, human-factors, user experience, automotive engineering, psychology, and economics.

Creative Commons BY 4.0

Susanne Boll, Andrew Kun, Bastian Pfleging, and Orit Shaer