The focus of this project was building shared understandings of future AI systems through design. Based on the literature study on the Explainability of AI, two main gaps were identified: the stakeholder's backgrounds are not accounted for during the design of systems and there is a need for a more holistic approach considering social and technical implications. To address these gaps, the project aimed to move from explainability to building situated understandings that accommodate multiple stakeholders' perspectives and backgrounds.

A criteria for shared understandings was defined based on literature and research: functionality, relatability, situatedness, and expectations. The main design approaches chosen were speculative design and the stack from Freedom Lab. While speculative design, provided immersion and context, the stack facilitated the breakdown and analysis of system layers. A case study on residential shared mobility was chosen as the focus of the project. The stakeholders included a real estate company, municipality officials, a transport provider, and behavioral and technology researchers. The goal was to bring tensions and challenges within the system to the surface and establish a shared understanding among the stakeholders. The project involved seven participants, including direct stakeholders and external individuals, for critical discussions. The participants were interviewed to understand their current understanding, backgrounds, and future visions of the system. Insights from the interviews revealed different interpretations of shared mobility, varying stakeholder priorities, and the challenges related to behavior change and technology implementation.

Four speculative artifacts were designed to surface tensions in the system. These artifacts represented future objects related to shared mobility. The participants interacted with the objects individually, followed by group discussions to explore the implications and challenges. The stack from FreedomLab was used to collect ideas and facilitate group discussions. The sessions aimed to sensitize participants to the case study, encourage their active involvement and gather their perspectives and reflections. Overall, the fostering of shared understandings of future AI systems was sought by the project through the consideration of stakeholder backgrounds, the employment of design methodologies, and the addressing of social and technical implications. The project helped shed light on three aspects. The case study of residential shared mobility, how an ideal system can be achieved, and the role of different stakeholders in this future. Reflection on the process of using speculative design and stack in combination to support each other. Finally insight into shared understandings as an approach to explainability.