Overview:
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Content Summary: This page provides an overview of the Axis research project, its goals, hypotheses, and outcomes, focusing on how AI-generated accessibility resources can impact the arts.
This page provides an overview of the Axis research project, what it set out to explore, and how the findings shifted once disabled and Deaf artists shared their actual experiences with AI.
This project is produced by grunt gallery and led by Kay Slater. It is possible thanks to funding from the Canada Council of the Arts.
The Axis research project began as an investigation into whether AI-generated accessibility resources could positively or negatively impact the arts — exploring tools that support non-auditory access, language and translation, non-visual access, and physical alternatives. What it became was something more grounded and more urgent: a portrait of how disabled and Deaf artists in British Columbia are actually living with AI right now.
How the research evolved
Spring 2026 – The original hypotheses assumed the conversation was primarily about developing better tools. After six months of reading, attending lectures, hosting conversations, and surveying disabled and Deaf artists in UBC, a different picture emerged.
“The artists I spoke with weren’t waiting for AI to get better. They were already using it, often out of necessity, while holding reasonable fears about what it might cost them.”
The most important finding was structural, not technological: for most respondents, AI fills gaps left by human support services that are unaffordable, unavailable after hours, or simply not budgeted for. It is not a preference. It is a survival strategy. And the most urgent concern is that AI will be used to declare accessibility “solved,” and funding for human interpreters, captioners, and support workers will be cut as a result.
The research also surfaced something that was largely absent from the broader national AI conversation: shame. Many disabled artists are hiding their AI use from their own communities, navigating judgment in spaces where the stakes of an unpopular opinion can mean real social and material isolation.
Author’s intention
“Ultimately, my goal with this report is not to condemn AI or celebrate it. Instead, they hope to show that the arts sector’s increasingly binary conversation: where AI is often framed as either inherently good or inherently harmful (and where “AI” frequently means generative AI without making that distinction) and leaves very little room for complexity. More importantly, it continues to overlook disability and Deaf perspectives and the everyday realities of people who are already adapting technology to reduce barriers.
grunt gallery is not putting forward the position that AI is “good.” We are actively developing our own internal policies and discussing where, when, and whether these tools should be used. Those conversations are important. But I believe it is equally important that we create an environment where people can speak honestly about how they are using these technologies, what concerns they have, and what possibilities they see.
When a community draws a hard line between “acceptable” and “unacceptable,” people rarely stop doing the thing being criticized. More often, they stop talking about it. Shame pushes behaviour underground. Once people begin hiding their use out of fear of criticism or professional consequences, we lose the opportunity to learn from one another. Policies become shaped by assumptions instead of lived experience, and discussions become dominated by those who have the greatest visibility, institutional power, educational privilege, or the confidence to speak first.
This worries me because disabled and Deaf communities have often survived by adapting tools in unconventional ways, long before those tools were considered acceptable or designed with accessibility in mind. If people cannot safely admit that they are experimenting with AI to reduce barriers (even as they continue to call for human services), we risk excluding exactly the voices that should be informing these conversations.
My hope is that this report encourages curiosity instead of certainty. Rather than asking whether AI is good or bad, I hope we ask different questions: Who benefits? Who is excluded? What assumptions are we making? Whose voices are missing? What barriers are being removed, and what new barriers are being created?
Those questions feel far more useful than drawing another line in the sand.”
A note on environmental impact
“Readers may notice that this report says relatively little about the environmental impact of AI. That omission was on purpose.
During this project, I spent time looking for research that could help quantify the environmental cost of personal AI use, particularly from the perspective of artists, galleries, and individual users. What I found was a rapidly changing landscape where one compelling statistic was often challenged by another equally reputable source. I found broad agreement that large-scale computing infrastructure, data centres, water use, electricity consumption, and hardware manufacturing all carry significant environmental consequences. What I could not confidently find was clear evidence that would allow me to speak responsibly about the impact of individual use within the arts, or how those impacts compare to the many other digital technologies that have become part of everyday life.
Interestingly, many of the artists and arts workers I spoke with already held strong opinions about AI’s environmental impact. Almost everyone had heard that “AI is bad for the environment,” but very few people could point to research that had informed that opinion. Instead, the information often came from trusted colleagues, social media, or broader community conversations. That doesn’t make the concern any less real, but it did reinforce my feeling that this deserves its own dedicated research project rather than a few paragraphs in this report.
I also worry that conversations about environmental responsibility too easily become focused on individual behaviour. We see this in many areas of climate justice, where consumers are encouraged to feel guilty about their personal choices, while the largest environmental impacts remain concentrated among governments, manufacturers, infrastructure providers, and multinational corporations. Individual choices matter, but systemic change requires systemic accountability.
Rather than speculate beyond the research I did, I chose to keep this report focused on accessibility, disability, and how AI is being used in practice. I hope someone else takes up this environmental impact research work because the arts sector deserves research that is as nuanced, transparent, and evidence-based as the conversations we are trying to have around accessibility. If we are going to advocate for environmental responsibility, I hope we do so by asking those with the greatest capacity to create change to be transparent and accountable, while also creating space for honest conversations about how and why individuals, especially disabled and Deaf people, choose to use these tools.”
Project Outcomes
The report is the primary outcome of the Axis project. It is available in HTML, plain text, audio with visual descriptions, and ASL video with a Deaf interpreter. All text and audio materials are shared under a Creative Commons Attribution-ShareAlike 4.0 licence. The ASL video is not available for remix or redistribution.
The 44-question survey is available as a template for other researchers to use, and is available on Google Forms for community members to take themselves. The published report will not be updated to include any surveys submitted (welcomed, but unverified).
A template letter for advocating to your employer or local government about AI policy is available, alongside the full survey instrument, which is also shared under Creative Commons.
Contact
Kay’s bio page is available on the grunt.ca website.