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What does digital inclusion look like in the age of AI? Over 6,000 of the world’s 7,000-plus living languages remain digitally disadvantaged.
What does digital inclusion look like in the age of AI? Over 6,000 of the world’s 7,000-plus living languages remain digitally disadvantaged.
AI+Science: Accelerating Discovery is an interdisciplinary conference bringing together researchers across physics, mathematics, chemistry, biology, neuroscience, and more to examine how AI is reshaping scientific discovery. Experts will separate hype from reality, spotlighting where AI is already enabling genuine breakthroughs and where its limits and risks remain.
AI+Science: Accelerating Discovery is an interdisciplinary conference bringing together researchers across physics, mathematics, chemistry, biology, neuroscience, and more to examine how AI is reshaping scientific discovery. Experts will separate hype from reality, spotlighting where AI is already enabling genuine breakthroughs and where its limits and risks remain.
While Large Language Models (LLMs) show promise in many domains, relying on them for direct policy generation in games often results in illegal moves and poor strategic play.
While Large Language Models (LLMs) show promise in many domains, relying on them for direct policy generation in games often results in illegal moves and poor strategic play.
HAI Weekly Seminar
In this talk, Lindsey D. Felt introduces a framework that locates disability innovation, artistry, and crip politics as central to the development of AI and technology. From M Eifler’s Prosthetic Memory to Paola Prestini’s Sensorium Ex, these examples of AI art highlight the erasures of disability from training data and refuse AI’s optimization against disability. Historically, technologies have been designed to diagnose, rehabilitate, normalize, and even cure disabilities. Though this approach has arguably improved the quality of life for many disabled people, it codes disability as an “undesirable” and “outlier” trait, operating on the false premise of a “norm” that is not reflective of the human condition’s heterogeneity. Researchers have demonstrated how machine learning tools are mirroring this trajectory, from autonomous vehicles that don’t recognize wheelchair users, to Natural Language Processing models that classify texts mentioning disability as more “toxic.” These biases are equally important to consider alongside racial and gender inequities for their wide-ranging social implications.
In conversation with artist-technologist M Eifler, Felt discusses approaches to human-centered AI art that are designed for self-care, mutual aid, and social justice-informed world-building. Felt and Eifler consider Prosthetic Memory, a digital memory bank created by Eifler that uses machine learning to retrieve self-recorded videos for the artist to navigate their memory dysregulation. Sensorium Ex, an experimental AI opera that introduces a new composite voice from an algorithm trained on non-normative speech patterns, similarly models the possibilities for a non-ableist AI. These works reflect the yearning for what scholar Alison Kafer calls “crip futurity,” a future where disabled people’s experiences, practices, stories, and ways of knowing are valued.
Lindsey FeltLeonardo CripTech Incubator Co-founder and Co-director; Lecturer in Program in Writing and Rhetoric, Stanford University
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