IEEE ISTAS 2021 AI for Literacy

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#IEEE ISTAS 2021 #Artificial intelligence #literacy #technology # bias #data #discrimination #equity #governance

This special session fosters an interdisciplinary conversation with the audience on AI literacy through a roundtable discussion consisting of archivists, digital humanists, literary scholars, and philosophers from several disciplinary backgrounds. The group engages in an open conversation to address a two-part question, namely: how can scholars and the university intervene against technology systems that disproportionately marginalize or discriminate against minorities? And how can they use this intervention to simultaneously platform individuals or groups who can surface counter-narratives within critical discourse surrounding representative technology and its role within the broader fields of policy, geopolitics, and governance? The discussion focuses on (1) the overarching ethical principles guiding collection, processing, and reuse of data; (2) algorithmic bias, including racial bias in data and discriminatory values in design; (3) the situated and relational nature of data, data practices, and data interpretation; and (4) the practical importance of equitable, open-sourced design within public and private institutions.

The "Artificial Intelligence (AI) For Literacy—A Cross-Disciplinary Exploration" Special Session took place during IEEE ISTAS 2021 on 29 October 2021.
Moderator: Jason Lajoie, University of Waterloo

Presenters:

  • Kem-Laurin Lubin, Ph.D. Candidate, University of Waterloo
  • Joseph Shea-Carter, Ph.D. Student, Literary Studies, School of English and Theatre Studies, University of Guelph
  • Kathryn Harvey, Archivist, Archival and Special Collections, University of Guelph Library; Senior Associate Editor, Archivaria
  • Asen O. Ivanov, Michael Ridley Postdoctoral Fellow in Digital Humanities, University of Guelph

This session fosters a conversation with the audience on AI literacy through a roundtable discussion to address a two-part question: How can academic institutions intervene against technology systems that disproportionately work against minorities? And how can they use this intervention to platform individuals or groups who can surface counter-narratives within critical discourse surrounding representative technology?

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