It is widely acknowledged that ubiquitous computing, artificial intelligence, and data-driven media are rapidly reshaping how people think and act in unprecedented ways. As these technologies become incorporated into more aspects of our daily lives, we need new forms of critical awareness and analysis to address the emerging challenges they pose. Working under the conviction that these challenges exceed the reach of individual disciplines and expertise, the Data Science & Humanities Initiative seeks to bring together humanistic researchers with technical practitioners and data scientists to examine our technological milieu in real time.
In addition to informal reading groups and daily interaction, activities of the initiative during the 2019–2020 academic year largely center on collaborative symposia. During the spring 2020 semester, the Center for Data Science is hosting a semi-weekly colloquium that will place historians, philosophers, literary scholars, and artists in conversation with computer scientists, engineers, and data scientists for cross-disciplinary engagement and exchange. Events aim to gather researchers from across the New York University community, leveraging its unique strengths in AI, data science, and the critical & analytical humanities. Topics that will be highlighted include conceptual histories of themes that underlie contemporary computational research, philosophical issues surrounding synthetic minds, human-AI interaction in the arts, and applications of data science in the digital humanities.
Tuesday October 1, 4–5:30pm
Center for Data Science (60 Fifth Avenue)
7th Floor Open Space
Mercedes Bunz (Digital Humanities, King’s College, London)
On the Misunderstandings of AI
A wide range of different AI systems based on the promising technology of machine learning are rapidly being integrated into everyday life, variously supplanting and delivering institutional decisions. The emerging ubiquity of these systems alternately provokes consternation and enthusiastic acceptance. Taking inspiration from French technology theorist Gilbert Simondon, this lecture considers the boundaries between the meaning-making capacities of technical objects, such as AI systems, and aesthetic objects. It asks what it means that AI systems are ‘integrated’ into the world, and whether this integration could be understood differently. Might existing responses to integration be based on a misunderstanding?
David Bering-Porter (Culture and Media, The New School)
Alt.Intelligence: Generative Media and Deformations of Intelligence
In 2014, the computer scientist Ian Goodfellow and his colleagues developed the idea of Generative Adversarial Networks (GANs), ushering in a new age of generative media. Ranging from Google’s “deep dream” to “deepfakes,” these new forms of media show off a starkly alien style in which neural networks reveal a view on the world that is radically different from our own. This talk looks to examples of generative media produced by GANs to consider how AI functions as both an alternative to and a deformation of traditional views of intelligence. It uses generative media as a touchstone to consider why it is both interesting and important to attempt to articulate the experiential view of artificial intelligence, and how doing so is worthwhile as machine learning continues to pervade our everyday lives.
Co-sponsored by NYU’s Digital Theory Lab and the Dean for Humanities