I’m an Associate Professor at TU Delft, working in human-algorithm interaction - exploring the messy terrain between people, data and things through a combination of making and thinking. Current research questions include: How can we understand the algorithmically mediated society that we are heading towards? How can we ensure that there is space for people within computational systems, preserving privacy, choice, identity and humanity while making use of the possibilities of emerging technology? How can we work with things that have an increasing sense of agency, from sensing to responding to shaping the world around them? See info on academic work, with more detail on research, teaching and PhD supervision.

In my creative practice I engage with interactions between people and technology. I make music using computers and controllers, and our laptop trio Raw Green Rust has played in many interesting places. I create artworks that explore technological and social phenomena that have been shown internationally (ZKM, Creativity and Cognition, Scottish National Gallery of Modern Art, Talbot Rice Gallery) and have won multiple awards (Lumen Prize, New Technology Art Award).

Upcoming public events

Speculative AI Summer School 2/9/2024 Politecnico Torino (Organising)
Design and AI Symposium 22/10/2024 Dutch Design Week, TU Eindhoven (Organising)

(see all events)

Selected recent papers

  1. (Un)Making AI Magic: A Design Taxonomy Lupetti, Maria Luce and Murray-Rust, Dave (2024) Proceedings of the CHI Conference on Human Factors in Computing Systems

    (Un)Making AI Magic: A Design Taxonomy

    This paper examines the role that enchantment plays in the design of AI things by constructing a taxonomy of design approaches that increase or decrease the perception of magic and enchantment. We start from the design discourse surrounding recent developments in AI technologies, highlighting specific interaction qualities such as algorithmic uncertainties and errors and articulating relations to the rhetoric of magic and supernatural thinking. Through analyzing and reflecting upon 52 students’ design projects from two editions of a Masters course in design and AI, we identify seven design principles and unpack the effects of each in terms of enchantment and disenchantment. We conclude by articulating ways in which this taxonomy can be approached and appropriated by design/HCI practitioners, especially to support exploration and reflexivity.

  1. Unpacking Human-AI Interactions: From Interaction Primitives to a Design Space Tsiakas, Konstantinos and Murray-Rust, Dave (2024) ACM Transactions on Interactive Intelligent Systems

    Unpacking Human-AI Interactions: From Interaction Primitives to a Design Space

    This paper aims to develop a semi-formal representation for Human-AI (HAI) interactions, by building a set of interaction primitives which can specify the information exchanges between users and AI systems during their interaction. We show how these primitives can be combined into a set of interaction patterns which can capture common interactions between humans and AI/ML models. The motivation behind this is twofold: firstly, to provide a compact generalisation of existing practices for the design and implementation of Human-AI interactions; and secondly, to support the creation of new interactions by extending the design space of HAI interactions. Taking into consideration frameworks, guidelines and taxonomies related to human-centered design and implementation of AI systems, we define a vocabulary for describing information exchanges based on the model’s characteristics and interactional capabilities. Based on this vocabulary, a message passing model for interactions between humans and models is presented, which we demonstrate can account for existing HAI interaction systems and approaches. Finally, we build this into design patterns which can describe common interactions between users and models, and we discuss how this approach can be used towards a design space for HAI interactions that creates new possibilities for designs as well as keeping track of implementation issues and concerns.

  1. Spatial Robotic Experiences as a Ground for Future HRI Speculations Murray-Rust, Dave and Lupetti, Maria Luce and Ianniello, Alessandro and Gorbet, Matt and Van Der Helm, Aadjan and Filthaut, Liliane and Chiu, Adrian and Beesley, Philip (2024) Companion of the 2024 ACM/IEEE International Conference on Human-Robot Interaction

    Spatial Robotic Experiences as a Ground for Future HRI Speculations

    This work illustrates how artistic robotic systems can provide a reservoir of unfamiliarity and a basis for speculation, to open the field toward new ways of thinking about HRI. We reflect on a collaborative project between design students, a media art studio, and design researchers working with the baggage handling department of a strategic European airport. Engaging with the industrial context, we developed ’meta-behaviours’ - abstracted ideas of processes carried out on the worksite and passed these over to the students who translated them into robotic enactions based on hardware and a form language developed by the media art studio. The resulting visit experience challenges the audience to decode the installation in terms of meta-behaviours and their possible relations to industrial HRI. We used this to reflect on the value of conducting artistic and speculative work in HRI and to distil actionable recommendations for future research.

  1. Experiential AI: Between Arts and Explainable AI Hemment, Drew and Murray-Rust, Dave and Belle, Vaishak and Aylett, Ruth and Vidmar, Matjaz and Broz, Frank (2024) Leonardo

    Experiential AI: Between Arts and Explainable AI

    Experiential artificial intelligence (AI) is an approach to the design, use, and evaluation of AI in cultural or other real-world settings that foregrounds human experience and context. It combines arts and engineering to support rich and intuitive modes of model interpretation and interaction, making AI tangible and explicit. The ambition is to enable significant cultural works and make AI systems more understandable to nonexperts, thereby strengthening the basis for responsible deployment. This paper discusses limitations and promising directions in explainable AI, contributions the arts offer to enhance and go beyond explainability and methodology to support, deepen, and extend those contributions.

  1. Grasping AI: Experiential Exercises for Designers Murray-Rust, Dave and Lupetti, Maria Luce and Nicenboim, Iohanna and van der Hoog, Wouter (2023) AI & Society

    Grasping AI: Experiential Exercises for Designers

    Artificial intelligence (AI) and machine learning (ML) are increasingly integrated into the functioning of physical and digital products, creating unprecedented opportunities for interaction and functionality. However, there is a challenge for designers to ideate within this creative landscape, balancing the possibilities of technology with human interactional concerns. We investigate techniques for exploring and reflecting on the interactional affordances, the unique relational possibilities, and the wider social implications of AI systems. We introduced into an interaction design course (n=113) nine ‘AI exercises’ that draw on more than human design, responsible AI, and speculative enactment to create experiential engagements around AI interaction design. We find that exercises around metaphors and enactments make questions of training and learning, privacy and consent, autonomy and agency more tangible, and thereby help students be more reflective and responsible on how to design with AI and its complex properties in both their design process and outcomes.

  1. Respect as a Lens for the Design of AI Systems Seymour, William and Van Kleek, Max and Binns, Reuben and Murray-Rust, Dave (2022) Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society

    Respect as a Lens for the Design of AI Systems

    Critical examinations of AI systems often apply principles such as fairness, justice, accountability, and safety, which is reflected in AI regulations such as the EU AI Act. Are such principles sufficient to promote the design of systems that support human flourishing? Even if a system is in some sense fair, just, or ’safe’, it can nonetheless be exploitative, coercive, inconvenient, or otherwise conflict with cultural, individual, or social values. This paper proposes a dimension of interactional ethics thus far overlooked: the ways AI systems should treat human beings. For this purpose, we explore the philosophical concept of respect: if respect is something everyone needs and deserves, shouldn’t technology aim to be respectful? Despite its intuitive simplicity, respect in philosophy is a complex concept with many disparate senses. Like fairness or justice, respect can characterise how people deserve to be treated; but rather than relating primarily to the distribution of benefits or punishments, respect relates to how people regard one another, and how this translates to perception, treatment, and behaviour. We explore respect broadly across several literatures, synthesising perspectives on respect from Kantian, post-Kantian, dramaturgical, and agential realist design perspectives with a goal of drawing together a view of what respect could mean for AI. In so doing, we identify ways that respect may guide us towards more sociable artefacts that ethically and inclusively honour and recognise humans using the rich social language that we have evolved to interact with one another every day.

  1. Metaphors for Designers Working with AI Murray-Rust, Dave and Nicenboim, Iohanna and Lockton, Dan (2022) DRS Biennial Conference Series

    Metaphors for Designers Working with AI

    In this paper, we explore the use of metaphors for people working with artificial intelligence, in particular those that support designers in thinking about the creation of AI systems. Metaphors both illuminate and hide, simplifying and connecting to existing knowledge, centring particular ideas, marginalising others, and shaping fields of practice. The practices of machine learning and artificial intelligence draw heavily on metaphors, whether black boxes, or the idea of learning and training, but at the edges of the field, as design engages with computational practices, it is not always apparent which terms are used metaphorically, and which associations can be safely drawn on. In this paper, we look at some of the ways metaphors are deployed around machine learning and ask about where they might lead us astray. We then develop some qualities of useful metaphors, and finally explore a small collection of helpful metaphors and practices that illuminate different aspects of machine learning in a way that can support design thinking.

  1. Blockchain and Beyond: Understanding Blockchains through Prototypes and Public Engagement Murray-Rust, Dave and Elsden, Chris and Nissen, Bettina and Tallyn, Ella and Pschetz, Larissa and Speed, Chris (2022) Transactions on Computer-Human Interaction

    Blockchain and Beyond: Understanding Blockchains through Prototypes and Public Engagement

    This paper presents an annotated portfolio of projects that seek to understand and communicate the social and societal implications of blockchains, distributed ledgers and smart contracts. These complex technologies rely on human and technical factors to deliver cryptocurrencies, shared computation and trustless protocols but have a secondary benefit in providing a moment to re-think many aspects of society, and imagine alternative possibilities. The projects use design and HCI methods to relate blockchains to a range of topics, including global supply chains, delivery infrastructure, smart grids, volunteering and charitable giving, through engaging publics, exploring ideas and speculating on possible futures. Based on an extensive annotated portfolio we draw out learning for the design of blockchain systems, broadening participation and surfacing questions around imaginaries, social implications and engagement with new technology. This paints a comprehensive picture of how HCI and design can shape understandings of the future of complex technologies.

  1. Enacting the Last Mile: Experiences of Smart Contracts in Courier Deliveries Tallyn, Ella and Revans, Joe and Morgan, Evan and Fisken, Keith and Murray-Rust, Dave (2021) Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems

    Enacting the Last Mile: Experiences of Smart Contracts in Courier Deliveries

    Smart contract systems could change the nature of last-mile delivery for the better through enhanced precision, coordination and accountability. However, technological complexity poses a challenge for end-users participating in the design process, making it hard to explore their experiences and incorporate their perspectives. We describe a case study where technological prototypes create smart contract experiences for professional couriers and receptionists, allowing them to speculate about emerging possibilities, whilst remaining grounded in their current practices. Participants enacted a series of deliveries, choreographed by smart contracts, and their responses were explored in post-experience, one-to-one interviews. Working with professionals to explore the potential impact of smart contract technologies, revealed the systemic webs of value underlying their existing work practices. This has implications for design of such technologies, in which increased automation, efciency and accountability must be delicately balanced with the benefts of sustaining personal values, relationships and agency.

Recent events

Relational AI Interaction Design

Turing AI and Arts Seminar (26/4/2024) More Info

Artificial Otoacoustics

iii Flipchart (10/10/2023) More Info

Mitbewohner - Live

Kunstverein Gallery, Baden (7/8/2023)

Antagonistic Sextet

Inspace, Edinburgh (4/5/2023) More Info

Human-Machine Inter-Agencies

Design Informatics Seminars (15/10/2020) More Info

Raw Green Rust

Beyond Symposium, Experimenta Heilbronn (28/09/2019)

Human-Machine Interagencies

IoT India Congress, Bangalore (23/08/2019)

(see all past event media)