Artists who build the machines they think with.

Machines We Imagine is an official UAL Group that supports research led by artists who build computational systems while making art. We also study how making these tools, in turn, can inform creative practice.

Software, circuit boards, interfaces, models, and datasets can encode an artist's values. When code is treated as a material, it shapes the cognition of the artist who makes it. By extension, it can also change the people who encounter the art or use the system. Where the dominant model of tech equates scale with success, Machines We Imagine holds that a more subtle process is at play. Artists are proposing possible future directions for society.

Announcement

Autumn meetings 2026

Open to UAL staff and researchers. Come along and see what the group is working on.

Wed 7 October 2026 3–5pm Room PR_B501E
Wed 4 November 2026 3–5pm Room PR_B501E
Wed 2 December 2026 3–5pm Room PR_B501E

Who we are 01

Research lead

Dr Phoenix Perry

Reader, UAL Creative Computing Institute

Phoenix studies cognitive models for AI, embodied interaction, and small-data machine learning. She makes embodied games, installations, and the tools behind them, working across human-computer interaction, interactive machine learning, and play. As research lead of Held in Common and The Antigravity Machine, they are currently focused on developing an ethical AI stack for artists. Their most recent art, Resonate Thrum, explores biosyncrony in groups via sound, light and haptic biofeedback loops.

phoenixperry.com

Research lead

Dr Matthew Plummer-Fernández

Course Leader, BA Fine Art: Computational Arts, Camberwell College of Arts

A British/Colombian artist working across algorithmic systems, popular culture, and contemporary issues, in the traditions of generative art, critical design, and internet art. His works are held in the permanent collection of Centre Pompidou and received an Award of Distinction at Ars Electronica.

plummerfernandez.com

Research lead

Prof Nick Bryan-Kinns

Professor of Creative Computing, UAL Creative Computing Institute

Nick researches how artists build, use, and trouble AI in their creative practice and how AI shapes and reframes their creative practice. His current research explores what he terms Praxis GenAI with Intangible Cultural Inheritors, Responsible AI and music, and Explainable AI for the Arts.

nickbknickbk.github.io

Research lead

Prof Rebecca Fiebrink

Professor of Creative Computing, UAL Creative Computing Institute

Rebecca builds technologies for new forms of human expression, creativity, and embodied interaction, combining human-computer interaction with machine learning. She created Wekinator, the interactive machine learning tool for real-time gestural design, and co-created InteractML, RAPID-MIX, Sound Control, and MIMIC.

UAL research profile

Research lead

Prof Mick Grierson

Professor and Research Leader, UAL Creative Computing Institute

Mick has worked where AI meets the creative industries for 25 years. Founder of the discipline of Creative Computing and co-founder of the Creative Computing Institute, Mick leads its Deep Learning Research Group. The lab's early Creative AI work includes AutoEncoding Bladerunner, Learning to See, and the MAGNet generative audio system used by Massive Attack for Mezzanine Vs MAGNET.

UAL research profile

Research lead

Prof Sarah Fdili Alaoui

Professor, UAL Creative Computing Institute

Sarah works at the intersection of human–computer interaction and dance, and is also a choreographer, dancer, and Laban Movement Analyst. Moving between studio, stage, and research lab, Sarah develops interactive performances and generative systems with dancers, choreographers, and technologists, exploring new ways of composing, learning, documenting, and archiving movement.

saralaoui.com

We are a growing group of UAL artists and researchers who build. Join us.

Remit: Three commitments 02

The creation of software by artists warrants more research and support.

Machines We Imagine (MWI) works on the instruments of computational creative practices: model architectures, interfaces, datasets, controllers, and the governance frameworks that decide how each may be used.

We study what a tool encodes about creative work, how it shapes the experience of the person using it, and how a tool built for exploration differs from one built for resolution in its outputs. We prioritize this as artist-led research.

We are artists who build tools.

Artists build tools as part of the art-making process, deliberately, and sometimes to make something easier for the next artist to come along. This can lead to thousands or millions of people learning something new, discovering a new possible form of expression, or nothing at all, except a single work of art. MWI gives that work a research home, technical infrastructure, and a route to funding.

Creative practice tool-building as the method.

Tools are developed through practice, tested with the practitioners who will use them, and assessed by their impact on work rather than by output-centric metrics alone. The studio's methods include autoethnography, participatory co-design, and relational, interpretive evaluation frameworks that explode and explore process.

Future key activities 03

Tool development

The studio designs and releases creative tools as concrete artifacts: prototype systems, open-source repositories, and documentation that enables independent practitioners to adopt them.

Grant mentoring

“How do I fund this?” is often one of the questions artists ask themselves. As artists who have worked out how to fund, publish, and share their work, we aspire to make it easier for early-career researchers to do the same.

iii

Practice-led research and publication

Each tool is paired with a research output. The studio produces position papers, technical systems papers, and evaluation frameworks for venues across HCI, digital humanities, and creative AI, so that the knowledge generated by building a tool returns to the field and to the practitioners who informed it.

Funding small prototypes 04

Seed funding for prototypes that grow into grants.

We get a small amount of budget each year from UAL. We want to support the creation of prototypes and research that will generate grant funding and drive public engagement and knowledge exchange at UAL more broadly. If you're at UAL and want to join us, get in touch!

Get in touch

Current work 05

In early development

The Antigravity Machine

A real-time, code-free interface for training models through gesture and movement, and navigation tools that make the structure of a model's latent space legible and steerable rather than opaque. This project is in early development.

Running funded research projects from our members 06

Held in Common

Research lead: Phoenix Perry
Site: heldincommon.org
Funder: UKRI AHRC Braid

A Federated Data Commons and Governance Framework.

This UKRI AHRC Braid-funded research is developing a federated, community-governed approach to creative data, allowing practitioners to curate, control, and share the datasets that train their tools under conditions they define.

Contact 07

If you are building a tool as part of your creative practice and want to get in touch, we want to hear from you.

An official UAL Group.

Email us