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Learning Under Algorithmic Conditions

Updated: Apr 6, 2023

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


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