Computers and art in the age of machine learning

investment in the use of the latest technologies in the arts and announce the symposium “Searching Through Seeing: Optimizing Computer Vision Technology for the Arts” that will take place at The Frick on April 12-13. This pioneering symposium is evidence that the field of art history is responding to advances in computer science. Also emphasizing the history of technology and the arts, Molly Wright Steenson, associate professor in the School of Design at Carnegie Mellon, underscores the role of designers and architects in computing practices and presents here an overview of her new book, Architectural Intelligence: How Designers and Architects Created the Digital Landscape. This issue also spotlights the role of artists and curators in the use and development of machine-learning techniques. In my conversation with artist and Google Arts and Culture resident Mario Klingemann, we explore the increased curatorial role of the artist in generative adversarial networks (GAN)-produced imagery and the philosophical implications of machine-generated art, including its relationship to music. At the center of our discussion are the seemingly inextinguishable human elements in computer art and W hen M a r v i n M i n sk y w a s i n t e r v i e w e d by computerimag ing specialist David Stork in the mid-nineties, the cognitive scientist and co-founder of the AI Laboratory at the Massachusetts Institute of Technology stated that the effective representation of knowledge would be key to the development of artificial intelligence [1]. More than two decades later, interest in the use of machine learning, a subset of AI, to perform analytical, organizational, and even generative tasks has extended far beyond the realm of basic images and sounds to the complex domain of art and music. Recent applications of computer vision and music technologies to knowledge-based and creative-use projects in the arts have received widespread acclaim in the media, and the rapid developments in this area outpace both their philosophical digestion and their interpretative positioning within academia [2, 3]. In this issue of XRDS, a range of approaches to this burgeoning area of creative research and development are showcased in order to bring attention to the everincreasing need for a more complex understanding of what exactly comprises the domain of computers and art as this hybrid and ill-defined area in applied machine learning takes root. To date, the fields of computer science, psychology, art history, music, art and architecture, and even the museum industry and business world all have expanded their engagement with the arts through an array of digitally based projects. In this issue, we take an in-depth look at some of the most exciting developments in these fields, which have led to inspiring scientific and artistic advancements. The work of Benoit Seguin, doctoral candidate in the Digital Humanities Laboratory at the École polytechnique fédérale de Lausanne (EPFL), has led to the development of a visual search engine that has the potential to augment pre-existing methodologies in art history, especially in relation to research in the imitation, replication, and emulation of works of art. In the Department of Computer Science at the University of California, Berkeley, doctoral candidate Shiry Ginosar and others have explored the repetition of objects in paintings, and the way computer models make generalizations about visual abstractions in comparison to humans. Her research improves the way computer vision technology is able to compliment human sight in regard to aesthetic subjects. How some of the developments in computer vision science have direct application for art historical research and to museums is made clear in the history of the Photoarchive at The Frick Collection in New York. Samantha Deutch, assistant director of the Center for the History of Collecting, and Louisa Wood Ruby, head of research at the museum, discuss the need for continued Computers and Art in the Age of Machine Learning