Andreas Broeckmann
- Published in print:
- 2017
- Published Online:
- September 2017
- ISBN:
- 9780262035064
- eISBN:
- 9780262336109
- Item type:
- book
- Publisher:
- The MIT Press
- DOI:
- 10.7551/mitpress/9780262035064.001.0001
- Subject:
- Art, Art History
This book deals with the ways in which visual artists have reflected on the cultural meaning of technology, and the particular aesthetic of machines, throughout the twentieth century. It is the first ...
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This book deals with the ways in which visual artists have reflected on the cultural meaning of technology, and the particular aesthetic of machines, throughout the twentieth century. It is the first comprehensive treatment of Machine Art and covers the most important historical developments as well as the key concepts of machine aesthetics. The book examines a variety of twentieth- and early twenty-first-century artworks that articulate people’s changing relationship with technical devices and infrastructures. It traces historical lineages that connect art of different periods, looking for continuities that link works from the end of the twentieth century to developments in the 1950s and 1960s and to works from the avant-gardes of the 1910s and 1920s. The investigation focuses on four specific domains of artistic engagement with technology: algorithms and machine autonomy; image, vision, and the advent of technical imaging; the human body in its relation to machines; and ecology. The book argues that systems thinking and ecological theories have brought about a fundamental shift in the cultural meaning of technology, which has also caused a change in the way technology impacts the formation of human subjectivity. This changing relationship between technology and subjectivity has been articulated by the different types of "machine art" throughout the twentieth century.Less
This book deals with the ways in which visual artists have reflected on the cultural meaning of technology, and the particular aesthetic of machines, throughout the twentieth century. It is the first comprehensive treatment of Machine Art and covers the most important historical developments as well as the key concepts of machine aesthetics. The book examines a variety of twentieth- and early twenty-first-century artworks that articulate people’s changing relationship with technical devices and infrastructures. It traces historical lineages that connect art of different periods, looking for continuities that link works from the end of the twentieth century to developments in the 1950s and 1960s and to works from the avant-gardes of the 1910s and 1920s. The investigation focuses on four specific domains of artistic engagement with technology: algorithms and machine autonomy; image, vision, and the advent of technical imaging; the human body in its relation to machines; and ecology. The book argues that systems thinking and ecological theories have brought about a fundamental shift in the cultural meaning of technology, which has also caused a change in the way technology impacts the formation of human subjectivity. This changing relationship between technology and subjectivity has been articulated by the different types of "machine art" throughout the twentieth century.
Antonio Torralba and Adolfo Plasencia
- Published in print:
- 2017
- Published Online:
- January 2018
- ISBN:
- 9780262036016
- eISBN:
- 9780262339308
- Item type:
- chapter
- Publisher:
- The MIT Press
- DOI:
- 10.7551/mitpress/9780262036016.003.0027
- Subject:
- Society and Culture, Technology and Society
Antonio Torralba, member of MIT CSAIL, opens the dialogue by describing the research he performs in the field of computer vision and related artificial intelligence (AI). He also compares the ...
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Antonio Torralba, member of MIT CSAIL, opens the dialogue by describing the research he performs in the field of computer vision and related artificial intelligence (AI). He also compares the conceptual differences and the context of the early days of artificial intelligence—where hardly any image recording devices existed—with the present situation, in which an enormous amount of data is available. Next, through the use of examples, he talks about the huge complexity faced by research in computer vision to get computers and machines to understand the meanings of what they “see” in the scenes, and the objects they contain, by means of digital cameras. As he explains afterward, the challenge of this complexity for computer vision processing is particularly noticeable in settings involving robots, or driverless cars, where it makes no sense to develop vision systems that can see if they cannot learn. Later he argues why today’s computer systems have to learn “to see” because if there is no learning process, for example machine learning, they will never be able to make autonomous decisions.Less
Antonio Torralba, member of MIT CSAIL, opens the dialogue by describing the research he performs in the field of computer vision and related artificial intelligence (AI). He also compares the conceptual differences and the context of the early days of artificial intelligence—where hardly any image recording devices existed—with the present situation, in which an enormous amount of data is available. Next, through the use of examples, he talks about the huge complexity faced by research in computer vision to get computers and machines to understand the meanings of what they “see” in the scenes, and the objects they contain, by means of digital cameras. As he explains afterward, the challenge of this complexity for computer vision processing is particularly noticeable in settings involving robots, or driverless cars, where it makes no sense to develop vision systems that can see if they cannot learn. Later he argues why today’s computer systems have to learn “to see” because if there is no learning process, for example machine learning, they will never be able to make autonomous decisions.
