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Presented By: Penny W Stamps School of Art & Design

Building Equitable Ecologies of Artificial Intelligence and Machine Learning

A mini-symposium with artists and data scientists

A colorful flowchout spells out Building Equitable Ecologies of Artificial Intelligence and Machine Learning A colorful flowchout spells out Building Equitable Ecologies of Artificial Intelligence and Machine Learning
A colorful flowchout spells out Building Equitable Ecologies of Artificial Intelligence and Machine Learning
Big Data and Artificial Intelligence (AI) have become a major force that impacts our daily lives in essential ways, from how political messaging and marketing are designed, to automating the process of deciding who gets hired or which neighborhood should be intensely patrolled. Big Data and AI can be an important agent for social justice and equality; or they can also be used to perpetuate injustice and hurt populations that are already disadvantaged and marginalized. Artists have been at the fore­front, together with scientists, in explor­ing ways in which AI sys­tems can be more equi­table, trans­par­ent and inclu­sive. This mini-symposium brings lead­ing voices in the field together, and is inspired by two projects at U-M:
Stephanie Dinkins: On
Love & Data, the first survey
exhibition of this prominent transmedia artist whose work creates platforms for
dialogue about AI as it intersects race, gender, aging and future histories.
This exhibit is organized by Stamps Gallery, Penny W. Stamps School of Art &
Design, from August 27 to October 23, 2021 and generously supported by the Andy
Warhol Foundation for the Visual Arts.Fair Representation in Arts and in Data: a collaboration between data scientists, artists and museum curators and funded by the U-M President’s Arts Initiative, the project team uses facial recognition technology to consider both the limitations of racial representation within UMMA’s collection and the limitations of the technology itself. The results culminate in an exhibit, "White Cube / Black Box", which will open at U-M Museum of Art on October 16, 2021.October 15, 2021 Mini-Symposium Program
Hybrid format / All events open to the public / RSVP for links to Zoom sessions
10:30 am: Opening Remarks
10:40 - noon: Stephanie Dinkins, Keynote and Q&A
12:30 - 1:45 pm: Art, Machine Learning and Data Justice Panel Discussion
Sophia Brueckner, Assistant Professor, Stamps
School of Art & Design, U-MH.V. Jagadish, Director, Michigan Institute for Data Science; Bernard A Galler
Collegiate Professor of Electrical Engineering and Computer Science,
U-MDiana Nucera (Mother Cyborg), Artist, Founder and Director of the Equitable Internet
InitiativeModerator: Srimoyee Mitra, Director, Stamps Gallery,
U-M2:30 - 4 pm: Data Science and Machine Learning for Artists WorkshopIn-Person Event / U-M Museum of Art, 525 S State St, Ann ArborKerby Shed­den (Director, Consulting for Statistics, Computing, and Analytics Research; Pro­fes­sor of Sta­tis­tics, Uni­ver­sity of Michigan) presents a non-technical exploration of methods and possibilities for the use of data science and machine learning in the arts. The workshop will cover a few of the ways that creative works can be viewed as data, and consider how methods for learning from data can be used to advance creation and insight in the arts. Students pursuing degrees at all levels in any field of arts are especially encouraged to attend. No prior exposure to data science or machine learning is expected. Registration required.
Co-orga­nized by Stamps Gallery, Penny W. Stamps School of Art &
Design, Dig­i­tal Stud­ies Insti­tute, Michi­gan Insti­tute of Data
Sci­ence, and Uni­ver­sity of Michi­gan Museum of Art. Gen­er­ously
sup­ported by the U-M Arts Initiative.

Program Committee:
Jing Liu, Managing Director, Michigan Institute for Data Science,
U-MSrimoyee Mitra, Director, Stamps Gallery, U-MMarisa Olson, Executive Director, Digital Studies Institute, U-MAccessibility
Stamps events are free and open to the public, and we are committed to making them accessible to all attendees. Virtual events will take place online using the Zoom platform with an auto-generated Live Transcript available.
If you anticipate needing any additional accommodations to participate, please email Jennifer Junkermeier-Khan at jenjkhan@umich.edu at least one week in advance of the scheduled event so we can arrange for your accommodation or an effective alternative.
A colorful flowchout spells out Building Equitable Ecologies of Artificial Intelligence and Machine Learning A colorful flowchout spells out Building Equitable Ecologies of Artificial Intelligence and Machine Learning
A colorful flowchout spells out Building Equitable Ecologies of Artificial Intelligence and Machine Learning

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