Together with Maaike Kleinsmann, we prepare a Special Issue on Data-Enabled Design for the journal Artificial Intelligence for Engineering Design, Analysis and Manufacturing (AI-EDAM).
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
Special Issue Website
- Submission deadline for full papers October 31st 2020
- Notification & reviews due to authors December 20th 2020
- Revised version submission deadline January 20 2021
- Second round of reviews due February 28 2020
- Final version due March 15 2021
- Issue Appears Fall 2021