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Bard Professor Suzanne Kite Interviewed for ArtNews

Suzanne Kite, aka Kite, distinguished artist in residence, assistant professor of American and Indigenous Studies, and director of the Wihanble S’a Center for Indigenous AI at Bard, was interviewed by ArtNews about her work in ensuring that Indigenous artists are involved throughout the development of AI systems. “I think that what we call AI is soon going to be split into its many, very separate systems, instead of this blanket calling everything AI,” said Kite, an Oglála Lakȟóta artist who has been using machine learning in artwork since 2018. “There are so many different things happening. If there is not diversity of thought, even basic cultural thought—but real diversity of thought—then we will just end up at a dead end with things.” Kite discusses earlier models of machine learning which she used to create art, how her work at Bard focuses on developing ethical AI frameworks deeply rooted in indigenous methodologies, and her public art project Cosmologyscape, in collaboration with Alisha B Wormsley, which solicits dreams from the public that are translated into quilting patterns generated from 26 Black and Lakota symbols and which will debut as sculptures at Ashland Plaza in Brooklyn from September 22 to November 3.

Post Date: 09-17-2024

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Professor Valerie Barr: “Visualizing Progress in Broadening Participation in Computing: The Value of Context”

Valerie Barr, Margaret Hamilton Distinguished Professor of Computer Science at Bard College, together with Carla E. Brodley and Manuel Pérez-Quiñones, examines in a new study how institutions of higher learning should reconsider the metrics by which they measure data to improve diversity and broadening participation in computing analysis and assessment. “Concerns about representation in computing within the US have driven numerous activities to broaden participation,” they write. However, as Barr points out, “the standard analysis of computer science degree data does not account for the changing demographics of the undergraduate population in terms of overall numbers and relative proportion of federally designated gender, race, and ethnicity groupings.” The study argues that the consideration of students’ intersectional identities, along with using multiple data-analysis methods, would aid in more accurate assessments of the effectiveness of curricular, pedagogic, and institutional interventions for expanding representation in computing.

Post Date: 07-09-2024