“Feedback is a method of controlling a system by reinserting into it the results of its past performance. If these results are merely used as numerical data for the criticism of the system and its regulation, we have the simple feedback of the control engineers. If, however, the information which proceeds backward from the performance is able to change the general method and pattern of performance, we have a process which may well be called learning.
Norbert Wiener. The Human Use of Human Beings: Cybernetics and Society (1950)
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Machine Learning probes the interface between human perception and artificial intelligence by applying post‑industrial image‑making techniques to industrial and rural landscapes. Instead of relying on textual prompts, the project fed photographs into DALL·E’s first‑generation deep‑learning model—trained on some 400 million image‑text pairs— and challenged it to hallucinate entirely new interpretations of those scenes. These algorithm‑generated visions prompt critical reflection on emerging visual economies and the shifting locus of authorship: to what extent will creative agency reside with the human operator versus computational processes? What unforeseen visual realities might such synthetic re-imaginings disclose—realities beyond the reach of unaided human observation?
Machine Learning stages this inquiry, unsettling traditional notions of artistic production in an era increasingly defined by algorithmic vision.
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Phillip Kalantzis Cope is a Greek-born photographer, author, and cultural theorist based in Champaign, Illinois, USA. He bridges visual art and critical theory, exploring how digital media, property, and technology shape social life. His photography and scholarship are internationally published and exhibited, emphasizing human environments and the unseen narratives of everyday experience.
www.phillipkalantziscope.com
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Edition: 100
Page Count: 48
Dimensions: 5.8” x 8.3”
Format: Saddle Stitch
ISBN: 978-1-7355008-6-7
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PRESS / LINKS:
“Feedback is a method of controlling a system by reinserting into it the results of its past performance. If these results are merely used as numerical data for the criticism of the system and its regulation, we have the simple feedback of the control engineers. If, however, the information which proceeds backward from the performance is able to change the general method and pattern of performance, we have a process which may well be called learning.
Norbert Wiener. The Human Use of Human Beings: Cybernetics and Society (1950)
****
Machine Learning probes the interface between human perception and artificial intelligence by applying post‑industrial image‑making techniques to industrial and rural landscapes. Instead of relying on textual prompts, the project fed photographs into DALL·E’s first‑generation deep‑learning model—trained on some 400 million image‑text pairs— and challenged it to hallucinate entirely new interpretations of those scenes. These algorithm‑generated visions prompt critical reflection on emerging visual economies and the shifting locus of authorship: to what extent will creative agency reside with the human operator versus computational processes? What unforeseen visual realities might such synthetic re-imaginings disclose—realities beyond the reach of unaided human observation?
Machine Learning stages this inquiry, unsettling traditional notions of artistic production in an era increasingly defined by algorithmic vision.
——————
Phillip Kalantzis Cope is a Greek-born photographer, author, and cultural theorist based in Champaign, Illinois, USA. He bridges visual art and critical theory, exploring how digital media, property, and technology shape social life. His photography and scholarship are internationally published and exhibited, emphasizing human environments and the unseen narratives of everyday experience.
www.phillipkalantziscope.com
——————
Edition: 100
Page Count: 48
Dimensions: 5.8” x 8.3”
Format: Saddle Stitch
ISBN: 978-1-7355008-6-7
——————
PRESS / LINKS:
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