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Investigations of sex differences in the human brain take place on politically sensitive terrain. While some scholars express concern that gendered biases and stereotypes remain embedded in scientific research, others are alarmed about the politicization of science. This talk sets out three kinds of conflicts that can arise in the neuroscience of sex differences: academic freedom versus gender equality; frameworks, background assumptions, and dominant methodologies; and inductive risk and social values. The boundaries between fair criticism and politicization are explored for each kind of conflict, pointing to ways in which the academic community can facilitate fair criticism while protecting against politicization.

Registration is free but required. A registration link will be shared via email with our department mailing lists a few weeks before the event. Please contact Jack Mikuszewski at jhm378@nyu.edu if you did not receive a registration link.

Generative art made with algorithms has existed since the early days of computing in the 1960s. In recent years, a new strand of generative art has emerged: AI-generated art, which leverages the recent progress of artificial intelligence to create artworks. Unlike old-fashioned generative art, AI-generated art is not produced with an explicit set of programming instructions provided by human artists; instead, it involves training an algorithm on a dataset so that it can later produce artworks (images, music, or video clips) using its own internal parameters that have not been explicitly defined by a human. This process raises fascinating questions at the intersection of computer science, art history, and the philosophy of art. At a superficial level of analysis, AI-generated art seems to offload much of the creative impetus of art production to the machine, requiring minimal intervention from the artist. On closer inspection, however, it involves a novel process of curation at two key stages: upstream in the selection of the dataset on which the algorithm is trained, and downstream in the selection of the outputs that should qualify as artworks. Instead of replacing human artists with computers, AI-generated art can be understood as a new kind of collaboration between mind and machine, both of which contribute to the aesthetic value of the final artwork.

This seminar will bring together AI artists and philosophers to explore the significance of this new mode of art production. It will discuss the implications of AI-generated art for the definition of art, the nature of the relationship between artists and tools, the process of digital curation, and whether AI systems can be as creative as humans.

Event Speakers

• Sougwen Chung, artist and researcher
• Helena Sarin, visual artist
• Anne Spalter, digital mixed-media artist
• Katherine Thomson-Jones, Professor of Philosophy at Oberlin College
• Moderated by Raphaël Millière, Presidential Scholar in Society and Neuroscience at Columbia University

Event Information

Free and open to the public. Registration is required via Eventbrite. Registered attendees will receive an event link shortly before the seminar begins.

This event is hosted by the Presidential Scholars in Society and Neuroscience as part of the Seminars in Society and Neuroscience series.

The Center for Science and Society makes every reasonable effort to accommodate individuals with disabilities. If you require disability accommodations to attend a Center for Science and Society event, please contact us at scienceandsociety@columbia.edu or (212) 853-1612 at least 10 days in advance of the event. For more information, please visit the campus accessibility webpage.