A Mini-Symposium with Artists & Data Scientists

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

10:30am Opening Remarks


10:40-noon  Keynote and Q&A


Stephanie Dinkins

12:30-1:45 Art, Machine Learning and Data Justice Panel Discussion


Sophia Bruckner
Assistant Professor, Stamps School of Art & Design

H.V. Jagadish
Director, Michigan Institute for Data and AI in Society

Diana Nucera (Mother Cyborg)
Artist, Founder and Director of the Equitable Internet Initiative

Srimoyee Mitra [Moderator]
Director, Stamps Gallery, U-M 

2:30-4:00 Data Science and Machine Learn­ing for Artists work­shop

U-M Museum of Art, 525 S State St, Ann Arbor

This will be a non-technical exploration of methods and possibilities for the use of data science and machine learning in the arts. We 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. 

Kerby Shed­den
Consulting for Statistics, Computing, and Analytics Research; Pro­fes­sor of Sta­tis­tics, U-M

Program Committee

Jing Liu
Managing Director, Michigan Institute for Data and AI in Society, U-M

Srimoyee Mitra
Director, Stamps Gallery, U-M 

Marisa Olson
Executive Director, Digital Studies Institute, U-M

This mini symposium is co-orga­nized by Stamps Gallery, Penny W. Stamps School of Art & Design, Dig­i­tal Stud­ies Insti­tute, Michi­gan Insti­tute of Data Sci­ence, Uni­ver­sity of Michi­gan Museum of Art, and ArtsEngine. Gen­er­ously sup­ported by the U-M Arts Initiative.