Views from the Machine | Workshop Digest
A playful interpretation of how we can reclaim our attention, foster agency, and recognize that what the machine “sees” often extends beyond the picture presented to “it.”
Developed and facilitated by Benjamin Lappalainen & Luisa Ji
When we speak of AI, we tend to relate the term to a broad philosophical concept. In many cases, we refer to them by their brand names: ChatGPT, Gemini, Copilot, Claude, etc. When we describe AI, we often use language that humans can relate to. Attention is one of them.
In 2017, researchers at Google co-authored “Attention is All You Need,” a paper that introduced the transformer, a machine learning architecture that rapidly accelerated the mainstream applications of machine learning. The “GPT” in ChatGPT stands for Generative Pre-trained Transformer. Today, the familiar brand-name AI products built on this architecture are capable of complex, multi-step reasoning and of processing and generating text, images, audio, and video in mere seconds.
Human attention
When you meet someone for the first time, what catches your attention?
There is no beginning or end to this process of “paying attention” — we continually try to make sense of our context. We take notes, make quick sketches, use verbal cues, and mark other psychological landmarks, sometimes with our phones’ cameras, to capture what we focus on daily.
Attention is a skill that can be learned and developed, and it is just as easily hacked, overloaded, or misdirected.
Machine attention
How machines “see” the world is often heavily anthropomorphized. The assumption that what a vision model processes is similar to human ocular processing creates a gap in comprehending how machine vision technologies are integrated into other systems — systems that can be technological and automated, or cultural, political, and social.
Views from the Machine highlights a brief selection of tools, each with specific use cases, to help participants better understand the implications of each “AI.” We explored examples from a self-supervised vision transformer, purpose-specific detection models, and a visual language model to bring everything together.
Indexing AI
AI is littered everywhere. It is presented to us as a monolith, with its own mythological qualities.
Along with the opportunity to peek at a handful of machine vision tools, we encouraged indexing them — tools that would otherwise be communicated as simply “AI,” even though their use cases carry specific real-life implications.
What is its purpose?
Who and what can it help?
In what ways could it be misused?
What are some of its alternatives?
Art and the Art of (not) Being Seen
UKAI Projects is run by artists. We each have our own practices and methods of making sense of the world. Where we converge is that art is a place where we learn about rules, bend them, and make our own.
When AI is sold to us through its speed and efficiency in “generating art,” art as a spectacle to be consumed or pure technical excellence becomes less relevant. Art, as a conduit for agency, relationship-building, and attention, creates new possibilities for how we want to live in an AI-saturated world.
We asked participants to think of a game we could play while being “watched” by one of the models we tested, and to specify the conditions for winning. With simple rules, we jumped into action to play the game of how not to be a person.
Views from the Machine is a playful interpretation of how we can reclaim our attention, foster agency, and recognize that what the machine “sees” often extends beyond the picture presented to “it.”
Work with us
At UKAI Projects, we turn abstract ideas into engaging experiences. When it comes to challenging topics like AI, we work from both technical and philosophical aspects to untangle the messy reality of AI adoption and implementation in cultural work.
Our program participants walk away with:
A personal framework for engaging critically and creatively with digital technologies
Clarity in articulating their own values and perspectives on algorithmic systems
Message UKAI Projects to collaborate with us on experiences tailored to the challenges you face — workplace culture, innovation, public life, tech education, and more. You can also select from our previous projects and learning programs to apply in new contexts.
Programs and Workshops
Saturday March 28, 2026 - 1pm-4pm
568 Richmond St. W, Toronto, Canada
A workshop on computer perception: attention, models, and how algorithms understand our world.
We spend a lot of time being seen by machines — cameras, phones, algorithms sorting through images of us without us knowing. Most of us are left with only a vague sense that something is happening, and no real way to look back.
Views from the Machine is for cultural practitioners, educators, facilitators, and curious thinkers who want to move beyond abstract conversations about AI and into direct, embodied experience with how these systems actually work.
Through hands-on exercises in drawing, collaging, and making — and watching what various vision models pay attention to in real time — participants develop an intuitive, grounded understanding of computer perception that no explainer article can provide.
Over the course of the workshop, we invite participants to:
Experience firsthand how machine attention differs from human perception
Develop playful, low-stakes methods for demystifying algorithmic systems
Build confidence in explaining abstract technical concepts through tangible, embodied practice
Engage critically with AI outside the familiar frames of productivity, efficiency, or fear
Participants in Views from the Machine will walk away with:
Tangible facilitation methods for introducing algorithmic literacy to non-technical audiences
A personal framework for engaging critically and creatively with digital technologies
Clarity in articulating their own values and perspectives on algorithmic systems
A shared experience with a small community of people asking the same kinds of questions
No technical background required. No computers to bring. Just your hands, your attention, and your willingness to be a little surprised by what the machine finds interesting.