Fundamentals of Design Competence for Our Digital Future

Acronym of the project: D-CoDE

Short description of the project:

A fundamentally new kind of design competence is needed to anticipate the digital transformation of society and create the conditions for responsible and sustainable futures. For this, D-CoDE will train a cohort of 15 PhD students in design, design anthropology, media studies, science and technology studies and data science, and equip them with the holistic understanding needed for the human-centric design of product service systems powered by Big Data, Machine Learning and Artificial Intelligence.

New foundations for design will require the interdisciplinary integration of five key research challenges identified in both engineering and the social sciences: (1) anthropological study and principled engineering of algorithms as foundation for shaping digital futures; (2) design of personally meaningful and socially appropriate forms of interaction with and across decentralised systems; (3) inclusive approaches to value creation in designing data-driven products, services and business models; (4) principles and mechanisms for public deliberation and governance of data flows across systems; (5) future design practices upholding anticipatory, deliberative and responsive innovation approaches.

To foster this holistic understanding – and the integration of knowledge across disciplines it requires – D-CoDE introduces a post-disciplinary mode of working called ‘prototeams’: teams of PhD students working in real-world contexts to develop and prototype future professional design roles and practices, including the scientific knowledge needed to support them. As these research challenges require both deep disciplinary expertise and knowledge that cuts across sectors, D-CoDE brings together an exceptional team of internationally leading researchers in the required subject areas, and non-academic partners that bring societal, economic and political practice to the project and provide multiple forums for the dissemination of knowledge, results and best practices.

Transport and Telecommunication Institute (TSI) will have a role in the following tasks:

WP1 — Data engineering methods for machine behaviour design. It will develop novel methods and tools for the design of machine behaviour through principled data engineering. The goal is to provide designers with meaningful and effective data-driven tools to shape, test and evolve machine behaviour. In particular, the research will investigate the adaptation of approaches drawn from data science and software engineering (e.g. semantic data modelling, data integration, requirements specification) for the principled design of machine learning training data.

Machine learning methods for sustainable design futures. It will explore the development of machine learning methods suitable for design tasks instead of the typical focus on efficiency and optimisation. In particular, the research will investigate what machine learning metrics are most apt for guiding these tasks and for navigating the associated design trade-offs (e.g., between accuracy and fairness) with human empowerment in mind.

WP2 — Designing for multi-intentional interaction. It will explore how human-machine interfaces can manifest the concurrent and conflicting needs of multiple users (“multi-intentionality”) of a data driven

product service system. The research will focus on how the use of techniques for scraping, visualising and interacting with data about the unstable interdependencies that exist among the system, its multiple users and the other systems to which it is connected, can provide an additional layer of legibility of a system’s behaviour and enable trust.

Total budget of the project: 4206200,40