Contingency, Control, & Creativity
April 18-20, 2023 ~ Adelphi Manhattan Center
This interdisciplinary conference will bring together different perspectives from across the humanities and sciences to discuss the nature of learning under algorithmic conditions.
Conference focus. This three-day working conference provides a forum for collaborative and applied philosophical inquiry, exploring the ways that contingency, control and creativity are at work under algorithmic conditions.
This alliterative cluster of three key concepts is meant to keep us focused on:
the play of contingency at the heart of speculative-mathematical models
the practices of control in digital governance and bodily subjection, and
the force of creativity and art in resisting and repurposing data and digital media.
This conference invites critical and creative approaches to the following questions:
How are theories of learning and cognition reconfigured through computational practices? How are doubt, uncertainty and abstraction recast in machine learning? What kinds of artful algorithmic experiments shed light on digital life? In what ways is expertise newly linked to neuro-symbolic imaginaries? How are environment, body, affect, and sensation designed by various digital pedagogies? How does education policy mobilize algorithmic self-regulation? How should we make sense of the incomputable in digital learning environments? How might algorithmic plausible reasoning shed light on posthuman eco-cognition?
Schedule
April 18, Tuesday, 9:30-16:30
April 19, Wednesday, 9:30-16:30
April 20, Thursday, 9:30-12:30
Speakers
Patricia Clough, CUNY Graduate Center
Felicity Colman, University of the Arts, London
Matthew X. Curinga, Adelphi University
Elizabeth de Freitas, Adelphi University
Ezekiel Dixon-Romàn, Columbia University
Henry Osman, Brown University
Reuben Feinman, New York University
Alexander Galloway, New York University
Chieh Lü, University of British Columbia
Raphaël Milliére, Columbia University
Luciana Parisi, Duke University
Arkady Plotnitsky, Purdue University
Goda Klumbytė, University of Kassel
Warren Sack, University of California
Sam Sellar, University of South Australia
Dave Wagner, University of New Brunswick
Taylor Webb, University of British Columbia
Ben Williamson, University of Edinburgh
Learning Under Algorithmic Conditions is co-sponsored by Adelphi University, Columbia University, University of South Australia, and Social Sciences and Humanities Research Council of Canada