The growing popularity of tools like DALL-E & MidJourney illustrates how artificial intelligence (AI) is quickly transforming image-making. Digital culture theorist & artist Lev Manovich will be in conversation with media scholar & writer Natasha Chuk to share examples & discuss these developments. They will address the emerging aesthetics & creative practices of AI photography & what these changes mean for the future of photography & the lens-based arts. This event is the first of a series of events & discussions exploring the relationship between AI & the lens & screen arts hosted by the MFA Photography, Video & Related Media Department at the School of Visual Arts. Stay tuned for future events in early 2023.

Deluge became a metaphor to describe the amount of information to which we are subjected, and very often we feel we are drowning while our access to information is rising. Devising mechanisms for exploring massive image sets according to perceptual attributes is still a challenge, even more when dealing with user-generated social media content. Such images tend to be heterogenous, and using metadata-only can be misleading. This paper describes a set of tools designed to analyze large sets of user-created art related images using image features describing color, texture, composition and orientation. The proposed pipeline permits to discriminate Flickr groups in terms of feature vectors and clustering parameters. The algorithms are general enough to be applied to other domains in which the main question is about the variability of the images.