When the Machine Made Art
Title | When the Machine Made Art PDF eBook |
Author | Grant D. Taylor |
Publisher | Bloomsbury Publishing USA |
Pages | 353 |
Release | 2014-04-10 |
Genre | Social Science |
ISBN | 1623565618 |
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.
When the Machine Made Art
Title | When the Machine Made Art PDF eBook |
Author | Grant D. Taylor |
Publisher | Bloomsbury Publishing USA |
Pages | 353 |
Release | 2014-04-10 |
Genre | Social Science |
ISBN | 1623568846 |
"When the Machine Made Art covers the reception and criticism of computer art from its emergence in 1963 to its crisis in 1989, when ideological differences fragment the art movement. The text begins by identifying the various divisions between the humanistic and scientific cultures that inform early criticism. The fact that the first computer art has military origins and is imbued with various techno-science mythologies, places the movement at odds with artworld orthodoxy. Yet, while mainstream art critics reproach computerized art, a comparison between similar art forms of the era, such as conceptual art, reveals that the criticism of computer art was motivated more by the fear of the machine than by aesthetics. Dr. Grant Taylor shows that social anxiety, often fueled by Cold War dystopianism, posited the computer as a powerful instrument in the overall subordination of the individual to the emerging technocracy. But even though anti-computer sentiment abated in the late 1970s, computer art did not find acceptance. The book illustrates how computer art's exponents, desiring artworld legitimacy, traced its lineage back to modernism. Conversely, in the 1980s, art theorists, employing the latest critical theory, began critiquing the assumptions of modernism, and thus viewed computer art's modernist history as hopelessly outdated. And yet other critics reconciled computer technology with the critical insights of postmodernism, viewing the computer as a pluralistic agent that could challenge modernist conventions. Nonetheless, while postmodernist criticism enabled the formation of new discourses for emerging digital arts, it left computer art, which was committed to modernist and techno-science philosophies, in a state of crisis"--
The Artist in the Machine
Title | The Artist in the Machine PDF eBook |
Author | Arthur I. Miller |
Publisher | MIT Press |
Pages | 429 |
Release | 2019-10-01 |
Genre | Computers |
ISBN | 0262042851 |
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.
Beyond the Creative Species
Title | Beyond the Creative Species PDF eBook |
Author | Oliver Bown |
Publisher | MIT Press |
Pages | 417 |
Release | 2021-02-23 |
Genre | Computers |
ISBN | 026204501X |
A multidisciplinary introduction to the field of computational creativity, analyzing the impact of advanced generative technologies on art and music. As algorithms get smarter, what role will computers play in the creation of music, art, and other cultural artifacts? Will they be able to create such things from the ground up, and will such creations be meaningful? In Beyond the Creative Species, Oliver Bown offers a multidisciplinary examination of computational creativity, analyzing the impact of advanced generative technologies on art and music. Drawing on a wide range of disciplines, including artificial intelligence and machine learning, design, social theory, the psychology of creativity, and creative practice research, Bown argues that to understand computational creativity, we must not only consider what computationally creative algorithms actually do, but also examine creative artistic activity itself.
Painting Machine
Title | Painting Machine PDF eBook |
Author | Guy Shoham |
Publisher | |
Pages | 176 |
Release | 2019-04 |
Genre | |
ISBN | 9781527237414 |
Machine Art, March 6 to April 30, 1934
Title | Machine Art, March 6 to April 30, 1934 PDF eBook |
Author | Museum of Modern Art (New York, N.Y.) |
Publisher | |
Pages | 128 |
Release | 1969 |
Genre | Art |
ISBN |
Art in the Age of Machine Learning
Title | Art in the Age of Machine Learning PDF eBook |
Author | Sofian Audry |
Publisher | MIT Press |
Pages | 215 |
Release | 2021-11-23 |
Genre | Art |
ISBN | 0262367106 |
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.