In this two-part presentation, art historian Emily L. Spratt and computer scientist Ahmed Elgammal explore the uses of vision technology for the analysis of art and its philosophical implications for both aesthetic theory and artificial intelligence. Through an investigation of the most fundamental questions computer scientists are confronted with in giving a machine the capacity to see, we demonstrate the value in utilizing methodologies from art history as the field of computer vision has already, in fact, predicted certain categories of interpretation that aid in the analysis of art. Returning to the aesthetic debates inspired by Kant and renewing focus to the art historical theories of iconography and iconology that were prominent in the first half of the twentieth century, basic issues of object classification are examined in relation to vision technology. In this presentation, we hope to demonstrate the merit of bridging the fields of art history and computer science, and to underscore the new challenges aesthetics, in the age of artificial intelligence, face.

This event is hosted by the Computer Science Colloquium, and co-sponsored by GC Digital Initiatives.