AI and Human Intelligence Series
AI and Human Intelligence: A Series of Conversations
Sponsored by the Vanderbilt Center for Digital Humanities and the Vanderbilt Data Science Institute
Deep Learning, Ethics, and Human Culture
April 6, 2021 11:00 am – 12:30 pm Central Time
Dr. Jesse Spencer-Smith from the Vanderbilt Data Science Institute will present the current state of the field and new developments in deep learning and artificial intelligence technology, followed by responses and discussion from an interdisciplinary panel of humanities scholars: Dr. Michael Bess, History; Dr. Diana Heney, Philosophy, and Dr. Haerin Shin, Media and Literature.
Join the virtual event here:
About the Panel:
Jesse Spencer-Smith, PhD, is Chief Data Scientist for the Data Science Institute at Vanderbilt University. He leads a team of data scientists who collaborate with researchers across the university and medical center and with industry partners, and is also an Adjunct Professor in Computer Science.
Michael Bess, Chancellor’s Professor of History at Vanderbilt University, is a specialist in 20th- and 21st-century Europe, with a particular interest in the interactions between social and cultural processes and technological change. His current book project is “What makes us human? From neurons to the Sistine Chapel.”
Diana B. Heney is an Assistant Professor of Philosophy at Vanderbilt University. Her research fits into two broad categories: ethics and history of philosophy. She writes and teaches on both theoretical and applied topics, including normative ethics, metaethics, ethics and mental health, death and dying, and freedom and responsibility. In the history of philosophy, her research emphasizes American pragmatism and the history of ethical theory.
Haerin Shin is an assistant professor of Media Studies at Korea University. Shin’s research fields include Asian American literature, science fiction, and digital media with emphasis on artificial intelligence. She has written on cyberbullying, posthuman spirituality, techno-Orientalism, and surveillance technologies, and is now working on books on Asian American science fiction and the ethics of artificial intelligence.
Digital Technologies and Creative Practice
April 9, 2021 1:00 – 2:30 pm Central Time
Media artists alejandro t. acierto and Sahar Sajadieh will present some of their recent work and discuss the role of digital technologies, computational methods, and artificial intelligence in their artistic practice.
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About the Artists:
alejandro t. acierto, Andrew W. Mellon Assistant Professor of Digital Art and New Media and a Mellon Faculty Fellow in Digital Humanities at Vanderbilt University, is an artist, musician, and curator whose work is largely informed by human relationships to technology. His recent work investigates situations and events that challenge the chronological sequencing of time; he seeks out other manifestations where time can either feel suspended or frozen, but not entirely obliterated, dwelling on the systems and mechanisms that allow for an unruly sense of time, a queer time, a timeless time. He is the co-author of CQDE: A Feminist Manifestx of Code-ing published by Sybil Press with KT Duffy.
Sahar Sajadieh is a digital performance & media artivist (artist/activist) and scholar and software developer, who was born and raised in Tehran, Iran. She is currently an ACLS postdoctoral fellow in Comparative Media Analysis and Practice (CMAP) at Vanderbilt University. She designs and develops technologies that support emergent human rituals and interactions, and simultaneously studies the human experience in different applications of new media. She believes art practice to be a powerful means for conducting research in Human-Machine Interaction and Performance & Media Studies.
Deep Learning for Humanities Research
April 13, 2021 11:00 am – 12:00 pm Central Time
Explore Deep Learning for yourself!
In this hands-on workshop, offered by the Vanderbilt Data Science Institute and geared to humanities scholars, participants will learn to use AI, machine learning, and cutting-edge deep learning methods for academic research. No prior experience necessary.
Join the virtual workshop here: