AI Futures Lab
Rights & Justice
AI is increasingly widespread, but poses a challenge for designers: it is complex, entangled, plural and indeterminate, and it changes over time. Harms that can result from poorly designed AI systems are both subtle and large scale, and socio-legal contexts evolve in response to the actions of computational systems. New understandings of rights and justice and flexible responses to a changing world are needed, which at the same time support human agency, human rights, wellbeing and justice.
The AI Futures Lab will address the current knowledge gap by combining Industrial Design Engineering (IDE) post-industrial design research and methodologies. These will be applied to machine ethnography, to experiential AI and to in-the-wild AI prototyping using Technology, Policy and Management (TPM) methodologies of comprehensive engineering and design for values. We will explore configurations of people and AI around rights and justice, aiming to expand both scientific knowledge and public understanding of AI capabilities. The empirical research focus of our lab extends from remote work to robotics and security. Our goal is a tangible and vibrant set of prototypes, experiences and theories that map out ways in which design can be engaged to deploy AI and machine learning in support of rights and justice. By prototyping new relationships ‘WITH AI’ that are respectful of agency, rights, and justice, we will open up spaces for new developments ‘IN AI’.
The AI Futures Lab is part of the TU Delft AI Labs programme.
- ID5235 Interdisciplinary AI Research Methods
- TBM020B Managing Start-ups: Teamwork, Leadership and AI
- ID4220-17 Interactive technology design (prototyping with and around AI)
- ID4216 Context and Conceptualisation (2022/23 Q1) – Track: Designing Human-AI Interactions for the Future of Work
- IFEEMCS520200 Interdisciplinary Advanced Artificial Intelligence Project (2022/23 Q1)
- TI3150TU - Capstone Applied AI project (2022/23 Q2)
- Activity recognition for product prototyping
- Design methods for prototyping relational AI
- Creative uses of lage models
- Interactive data physicalisation
- Respectful UX for AI Mediated Communication
- Designing AI with machine values
- Zhengquan Zhang -"Designing for explanation-driven trust in chatbots" | Konstantinos Tsiakas (mentor), Christina Schneegass (Chair)
- Meenu Sara Mathai Reji - Designing for transparent intentions in AI powered energy systems | Giaccardi, Elisa (mentor), Murray-Rust, D.S. (graduation committee)| Mueller, Nick (graduation committee)
- Rosa Elfering - Implementing care robot Tessa through general practitioners | Mooij, S.C. (mentor) | Murray-Rust, D.S. (mentor)
- Wei Zeng - Enabling Human- In-The-Loop Interpretability Methods of Machine Learning Models | Murray-Rust, D.S. (mentor), Bozzon, A. (graduation committee), Balayn, A.M.A. (graduation committee)
- Ji-Youn Jung - Ethics, Gender and Agents: The Role of Designers in Conversational Agent Design | Murray-Rust, D.S. (mentor) Gadiraju, Ujwal (mentor), Bozzon, A. (graduation committee),