Miller ICA Symposium and Panel Discussion

  • Carnegie Mellon Campus
  • Miller Gallery
Panel Discussion

This panel discussion explores the ways bias is inherently built into the structure and function of Machine Learning. In order to make predictions or identify patterns, AI requires that a person set specific instructions that have the potential to reinforce bias and oppressive social structures, particularly when ML is being used in everything from policing to determining someone’s credit score. This panel will also explore the role that contemporary art can play in challenging and refiguring these biases by calling into question the frameworks underpinning our assumptions. As ML and AI continue to influence more aspects of everyday life, conversations around how we can use these tools to undo harmful biases, as opposed to reinforcing them, is increasingly urgent.

Panel members:

Manuela Veloso
Manuela Maria Veloso is the Head of the Machine Learning Department at Carnegie Mellon University & Herbert A. Simon University Professor in the School of Computer Science at Carnegie Mellon University. She served as president of Association for the Advancement of Artificial Intelligence (AAAI) until 2014, and the co-founder and a Past President of the RoboCup Federation. She is a fellow of AAAI, Institute of Electrical and Electronics Engineers (IEEE), American Association for the Advancement of Science (AAAS), and Association for Computing Machinery (ACM). She is an international expert in artificial intelligence and robotics. In May 2018 she was hired by JPMorgan Chase as to head its artificial intelligence research.

Alexandra Chouldechova
Alexandra is an Assistant Professor of Statistics and Public Policy at Carnegie Mellon University's Heinz College of Informations Systems and Public Policy.  She received her B.Sc. from the University of Toronto in 2009, and in 2014 she completed her Ph.D. in Statistics at Stanford University. While at Stanford, she also worked at Google and Symantec on developing statistical assessment methods for information retrieval systems.   Alexandra's main research interests are in high dimensional statistics and large scale hypothesis testing. She is particularly interested in estimation and statistical inference in settings where the data is spatially or temporally structured. Her current research focuses on developing inferential procedures for anomaly detection problems in cases where multiple anomalies are expected to occur. 

Sey Min
Sey Min is a data visualization artist and designer, who is interested in dealing with live data sets in various media formats. She makes projects that reimagine how humans relate to technologies, to societies and cities, and to environments. Combining elements of environmental studies, visual art, programming, and data storytelling, her projects range from building a real-time interactive information graphics system for a music club (Gender Ratio, 2007) to visualizing Seoul City expenditure data (City DATA: Seoul Daily Expenditure, 2014).Her work has been shown at NIPS 2018, National Museum of Modern and Contemporary Art, Korea; TED 2011; TEDGlobal 2012; Art Center Nabi in Seoul, and Lift Conference, and featured on CNN Asia, Lift09 etc. After serving as  an urban information design researcher at MIT SENSEable City Lab,  She was selected as a 2011 TED Fellow and Senior Fellow from 2012 to 2013. Her work is also available at ttoky.com

Jillian Mayer
Jillian Mayer’s artistic practice is a means of processing how our physical world and bodies are impacted and reshaped by our participation in a digital landscape. Through videos, photography, painting, performance, sculpture and installation, my projects explore how technology affects our identities, lives, and experiences. Mayer explores the points of tension between our online and physicals worlds and make work that attempts to inhabit the increasingly porous boundary between the two. Her works and performances have been premiered at galleries and museums internationally such as MoMA, MoCA:NoMi, BAM, Bass Museum, MoMa PS1, the Contemporary Museum of Montreal and film festivals such as Sundance, SXSW, and New York Film Festival. 

Kerry Doran
Kerry Doran is a writer and curator based in New York and Buenos Aires. The writing and shows she produces center around time-based media and performance because of their particular engagement with new technologies. Her research looks at the critical applications of such tools by artists to better understand their cultural implications—economically, politically, and socially. Doran contributes to exhibition catalogs, artist books, and independent publications, including BOMB, Flash Art, Foam, Rhizome, Terremoto, and SFMOMA’s Open Space. Her curatorial projects have been featured in Artforum, ARTnews, Modern Painters, The New York Times, Página/12, Rhizome, and The Village Voice, among others. She has presented her research at the British Computer Society, Harvard, the ICP Museum, Goldsmiths, M+ Museum, MIT, and Virginia Tech. Previously, Doran was the director of bitforms and Postmasters, respectively, and a member of the inaugural team at the New Museum’s NEW INC. She holds a master’s with distinction from the Courtauld Institute of Art, where she was an Associate Scholar at the Research Forum.

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