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Today’s societal challenges in fields such as healthcare, mobility or sustainability are complex since they involve high contextual interdependence, scalability and a large number of stakeholders with dynamic objectives and requirements. Designers are well-known complex problem solvers. However, traditional design methods do not allow for creating the necessary systemic understanding of the behaviors of different people and how these behaviors could be or will be changed through design interventions. Moreover, designers lack ways to measure existing trends and the longitudinal impact of their design intervention. The recent shift in society towards a prevalent adoption of Artificial Intelligence (AI), seems to provide opportunities for designers to develop new design methods that support them in getting a systemic understanding of and longitudinal view on the system they design for. This is because the AI-based systems generate data that could (continuously) be incorporated into the design process. The umbrella term for emerging design methods that rely on data, generated by the AI solution, is data-enabled design.

In this thematic collection, we are interested in the recent developments in data-enabled design. We welcome papers that are conceptual, theoretical, or empirical. Conceptual papers might reflect on emerging topics. Papers that are theory-driven could explore one perspective or create an in-depth comparison between different theories and their application to designing systems with data. Empirical papers perhaps report on field studies, experiments, or research-through- design studies on applying and developing data-enabled design methods.

Together, the papers are intended to show an overview of the emerging field of data-enabled design. Whatever the type of contribution offered, we wish the authors to refer to basic tenets of the theoretical perspective employed and make its applicability and usefulness for design practice and research explicit.

We welcome papers that relate to, but are not limited to the following topics:

• Role of designers with data and AI
• Design in a data-driven society
• Responsibility and values in designing with data
• Literacy of data-enabled design
• Co-analysis with data subjects, crowd-sourcing or AI
• Co-creation with data
• Data as a new design material
• Data as creative material
• Never-ending data-enabled design process
• Tools for data-enabled design
• Prototyping with data and AI
• Data analytics and design (processes)
• Qualitative and quantitative data orchestration
• Evidence-based design at scale

Instruction for submissions

All submissions will be anonymously reviewed by at least three reviewers. The selection for publication would be made on the basis of these reviews.

Information about the format and style required for AIEDAM papers, as well as about submission, can be found at: https://www.cambridge.org/core/journals/ai-edam/information/instructions-contributors

Note that all queries and information about submissions for special issues should be addressed to the Guest Editors, and not to the Editor in Chief. Please submit your paper through the ScholarOne system online at: http://mc.manuscriptcentral.com/aie You need to create a user account first if you are a new user. During your submission process, pay attention to the following two steps:

• Step 1 (Type, title & abstract), "Thematic Collection"
  • If Yes, select "Data-enabled Design" for "Thematic Collection Name",
  • Else select “NA”

The following acronym will be used to refer to the special issue: DED

Important dates:

Guest editors: