An authority on creativity introduces us to AI-powered computers that are creating art, literature, and music that may well surpass the creations of humans. Today's computers are composing music that sounds “more Bach than Bach,” turning photographs into paintings in the style of Van Gogh's Starry Night, and even writing screenplays. But are computers truly creative—or are they merely tools to be used by musicians, artists, and writers? In this book, Arthur I. Miller takes us on a tour of creativity in the age of machines. Miller, an authority on creativity, identifies the key factors essential to the creative process, from “the need for introspection” to “the ability to discover the key problem.” He talks to people on the cutting edge of artificial intelligence, encountering computers that mimic the brain and machines that have defeated champions in chess, Jeopardy!, and Go. In the central part of the book, Miller explores the riches of computer-created art, introducing us to artists and computer scientists who have, among much else, unleashed an artificial neural network to create a nightmarish, multi-eyed dog-cat; taught AI to imagine; developed a robot that paints; created algorithms for poetry; and produced the world's first computer-composed musical, Beyond the Fence, staged by Android Lloyd Webber and friends. But, Miller writes, in order to be truly creative, machines will need to step into the world. He probes the nature of consciousness and speaks to researchers trying to develop emotions and consciousness in computers. Miller argues that computers can already be as creative as humans—and someday will surpass us. But this is not a dystopian account; Miller celebrates the creative possibilities of artificial intelligence in art, music, and literature.

An investigation of artists' engagement with technical systems, tracing art historical lineages that connect works of different periods. “Machine art” is neither a movement nor a genre, but encompasses diverse ways in which artists engage with technical systems. In this book, Andreas Broeckmann examines a variety of twentieth- and early twenty-first-century artworks that articulate people's relationships with machines. In the course of his investigation, Broeckmann traces historical lineages that connect art of different periods, looking for continuities that link works from the end of the century to developments in the 1950s and 1960s and to works by avant-garde artists in the 1910s and 1920s. An art historical perspective, he argues, might change our views of recent works that seem to be driven by new media technologies but that in fact continue a century-old artistic exploration. Broeckmann investigates critical aspects of machine aesthetics that characterized machine art until the 1960s and then turns to specific domains of artistic engagement with technology: algorithms and machine autonomy, looking in particular at the work of the Canadian artist David Rokeby; vision and image, and the advent of technical imaging; and the human body, using the work of the Australian artist Stelarc as an entry point to art that couples the machine to the body, mechanically or cybernetically. Finally, Broeckmann argues that systems thinking and ecology have brought about a fundamental shift in the meaning of technology, which has brought with it a rethinking of human subjectivity. He examines a range of artworks, including those by the Japanese artist Seiko Mikami, whose work exemplifies the shift.

An examination of machine learning art and its practice in new media art and music. Over the past decade, an artistic movement has emerged that draws on machine learning as both inspiration and medium. In this book, transdisciplinary artist-researcher Sofian Audry examines artistic practices at the intersection of machine learning and new media art, providing conceptual tools and historical perspectives for new media artists, musicians, composers, writers, curators, and theorists. Audry looks at works from a broad range of practices, including new media installation, robotic art, visual art, electronic music and sound, and electronic literature, connecting machine learning art to such earlier artistic practices as cybernetics art, artificial life art, and evolutionary art. Machine learning underlies computational systems that are biologically inspired, statistically driven, agent-based networked entities that program themselves. Audry explains the fundamental design of machine learning algorithmic structures in terms accessible to the nonspecialist while framing these technologies within larger historical and conceptual spaces. Audry debunks myths about machine learning art, including the ideas that machine learning can create art without artists and that machine learning will soon bring about superhuman intelligence and creativity. Audry considers learning procedures, describing how artists hijack the training process by playing with evaluative functions; discusses trainable machines and models, explaining how different types of machine learning systems enable different kinds of artistic practices; and reviews the role of data in machine learning art, showing how artists use data as a raw material to steer learning systems and arguing that machine learning allows for novel forms of algorithmic remixes.

In 1934, New York’s Museum of Modern Art staged a major exhibition of ball bearings, airplane propellers, pots and pans, cocktail tumblers, petri dishes, protractors, and other machine parts and products. The exhibition, titled Machine Art, explored these ordinary objects as works of modern art, teaching museumgoers about the nature of beauty and value in the era of mass production. Telling the story of this extraordinarily popular but controversial show, Jennifer Jane Marshall examines its history and the relationship between the museum’s director, Alfred H. Barr Jr., and its curator, Philip Johnson, who oversaw it. She situates the show within the tumultuous climate of the interwar period and the Great Depression, considering how these unadorned objects served as a response to timely debates over photography, abstract art, the end of the American gold standard, and John Dewey’s insight that how a person experiences things depends on the context in which they are encountered. An engaging investigation of interwar American modernism, Machine Art, 1934 reveals how even simple things can serve as a defense against uncertainty.

The articles collected in this volume from the two companion Arts Special Issues, "The Machine as Art (in the 20th Century)" and "The Machine as Artist (in the 21st Century)", represent a unique scholarly resource: analyses by artists, scientists, and engineers, as well as art historians, covering not only the current (and astounding) rapprochement between art and technology but also the vital post-World War II period that has led up to it; this collection is also distinguished by several of the contributors being prominent individuals within their own fields, or as artists who have actually participated in the still unfolding events with which it is concerned

Considering how culturally indispensable digital technology is today, it is ironic that computer-generated art was attacked when it burst onto the scene in the early 1960s. In fact, no other twentieth-century art form has elicited such a negative and hostile response. When the Machine Made Art examines the cultural and critical response to computer art, or what we refer to today as digital art. Tracing the heated debates between art and science, the societal anxiety over nascent computer technology, and the myths and philosophies surrounding digital computation, Taylor is able to identify the destabilizing forces that shape and eventually fragment the computer art movement.