CDSS and Cal Performances present
Place and Displacement: Bias in Our Algorithms and Society
Date: Thursday, October 28, 2021
Time: 4:00-5:30 PM Pacific
Location: Watch the video recording (available to watch on demand through June 30, 2022). This free event was presented live at UC Berkeley's Zellerbach Hall and virtually via livestream video.
As part of Angélique Kidjo’s artist residency with Cal Performances during the 2021-2022 season, the UC Berkeley Division of Computing, Data Science, and Society (CDSS) is collaborating with Cal Performances to host a discussion on “Place and displacement: Bias in our algorithms and society.” The event will feature Kidjo in conversation with CDSS Associate Provost Jennifer Chayes, EECS Assistant Professor Nika Haghtalab, Computer Science PhD Student Devin Guillory, and EECS Professor Michael I. Jordan. The group will discuss the intersection of artificial intelligence and art, and explore how algorithms and machine learning tools reflect the biases of the people and data used to train them. The discussion will also touch on current research and promising interventions that aim to make algorithms more just.
This event is co-hosted by CDSS and Cal Performances as part of the 2021-22 Illuminations: “Place and Displacement series, which examines the fraught and often devastating effects of migration, exile, dislocations, and separation, on both hyper-local and international scales, through five main stage performances and related online and in-person programs with artists, creators, scholars, activists, and thinkers who are part of the UC Berkeley community.
Speaker(s)
Jennifer Chayes
Jennifer Chayes is the Associate Provost of the Division of Computing, Data Science, and Society, and the Dean of the School of Information at UC Berkeley. She is a professor in the departments of EECS, Mathematics, Statistics, and the School of Information. Before joining Berkeley, she was a Technical Fellow at Microsoft, where she was the founder and managing director of interdisciplinary Microsoft Research labs in New England, New York City, and Montreal. Chayes has received numerous awards for both leadership and scientific contributions, including the Anita Borg Institute Women of Vision Leadership Award, the John von Neumann Award of the Society for Industrial and Applied Mathematics, and an honorary doctorate from Leiden University. She is a member of the American Academy of Arts and Sciences and the National Academy of Sciences. Chayes’ research areas include phase transitions in computer science and structural and dynamical properties of networks including modeling and graph algorithms. Chayes is one of the inventors of the field of graphons, which are widely used for the machine learning of large-scale networks. Her recent work focuses on machine learning, including both theory and applications in cancer immunotherapy, ethical decision making, and climate change.
Angélique Kidjo
Cal Performances is thrilled to welcome singer, composer, activist, and humanitarian Angélique Kidjo as our first season-long artist-in-residence for 2021-2022. Kidjo, an international star and four-time Grammy Award winner, visits the UC Berkeley campus twice this season, performing her unique take on the Talking Heads’ seminal Remain in Light album in the fall, and returning in the spring with Yemandja, a new music-theater production co-commissioned by Cal Performances.
Kidjo is a genre- and border-crossing artist fluent in multiple languages and cultures, who has been honored for her activist work by the World Economic Forum and Amnesty International, and has been recognized by the BBC as “one of the greatest artists in international music today.” In all her work, the French-Beninese singer makes connections between contemporary issues and African musical traditions, and probes the past for lessons on improving the future.
During her campus visits, Kidjo will work closely with students, faculty, and a host of campus partners as part of a series of academic encounters and public programs that engage topics close to her heart, including the issue of equity in the fields of technology and data.
Nika Haghtalab
Nika Haghtalab is Assistant Professor in the Department of Electrical Engineering and Computer Sciences at UC Berkeley. She works broadly on AI and Theory and more specifically on learning in presence of social and strategic interactions. Her work focuses on creating a mathematical foundation that can both be used for guaranteeing that AI systems and algorithms will continue to perform well even when their environment is impacted by changing realities of our social and economic life, and for ensuring the integrity and equitability of social and economic forces that are born out of the use of AI systems in practice. Examples of application domains supported by this mathematical foundation include understanding belief polarization and biased beliefs in media, supporting platforms that enable collaboration in machine learning, and quality and equitability of AI methods that are used for making consequential decisions that impact humans. Haghtalab has won several awards for her work, including CMU School of Computer Science Dissertation Award and SIGecom dissertation honorable mention. She is a co-founder of Learning Theory Alliance.
Devin Guillory
Devin Guillory is a PhD student in computer science at UC Berkeley where he works in the fields of computer vision and machine learning. Prior to Berkeley, he obtained bachelor’s and master’s degrees in electrical engineering from Stanford and went on to serve as a Staff Data Scientist and technical lead of Search Ranking and Computational Advertising teams at Etsy. A founding engineer of Blackbird Technologies, Devin joined Etsy by way of acquistion. Throughout his career, he’s worked on a variety of machine learning problems in industrial and academic settings (e.g., computer vision, robotics, natural language processing, information retrieval, computational advertising, etc.) and has grown passionate about exploring areas where the theory and practice of machine learning systems diverge. His current work focuses on designing AI systems that perform reliably as environments change and that learn with limited supervision. Devin’s service as a director of Black in AI and publication of “Combating Anti-Blackness in the AI Community” illustrate his interest in the critical examination of systems that produce AI technology. Devin strives to participate in a technical community whose values center equity and positive impact.
Michael I. Jordan
Michael I. Jordan is the Pehong Chen Distinguished Professor in the Department of Electrical Engineering and Computer Sciences. His research interests bridge the computational, statistical, cognitive and biological sciences, and have focused in recent years on Bayesian nonparametric analysis, probabilistic graphical models, spectral methods, kernel machines and applications to problems in distributed computing systems, natural language processing, signal processing and statistical genetics. Jordan is a member of the National Academy of Sciences, a member of the National Academy of Engineering and a member of the American Academy of Arts and Sciences. He is a Fellow of the American Association for the Advancement of Science and has been named a Neyman Lecturer and a Medallion Lecturer by the Institute of Mathematical Statistics. He received the IJCAI Research Excellence Award in 2016, the David E. Rumelhart Prize in 2015, and the ACM/AAAI Allen Newell Award in 2009. He is a Fellow of the AAAI, ACM, ASA, CSS, IEEE, IMS, ISBA and SIAM.