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Pictorial

Reinterpreted Spaces, an AI Printmaking Collaboration

Hannen Wolfe, Charlotte Rogerson, Amanda Lilleston

Nine of the flag books created by the artists interpreting a chosen space through photography, AI generated imagery and printmaking.
A flag book and the 4 images that were used to create it: the photograph, the segmented image, the AI generated image and the print.
A flag book created by an artist interpreting a chosen space through photography, AI generated imagery and printmaking.
A flag book created by an artist interpreting a chosen space through photography, AI generated imagery and printmaking.
A flag book created by an artist interpreting a chosen space through photography, AI generated imagery and printmaking.
A flag book displayed in four different ways: opened like a book, opened to the full spread, the back of the book and the top of the book.
A flag book created by an artist interpreting a chosen space through photography, AI generated imagery and printmaking.
A flag book created by an artist interpreting a chosen space through photography, AI generated imagery and printmaking.
A flag book created by an artist interpreting a chosen space through photography, AI generated imagery and printmaking.
A flag book created by an artist interpreting a chosen space through photography, AI generated imagery and printmaking.

We present an examination of organic spaces through print, book making, data, and machine learning. Artists created a book that explored the idea of organic and machine-made interpretations of a place that were generate using 3 different processes: a generative adversarial network, traditional printmaking and a camera. The artists found the results unexpected, discussing how the AI-generated image changed and complicated their understanding and constructed narrative about the original image and space. This caused them to think outside the box with over half of the students changing their print matrix and/or ink choices after seeing their AI-generated image. This supported the learning objective for students to collaborate with technology that is uninhibited by perspective or expectation, adapting and responding productively and creatively within a new framework. With the newfound accessibility to AI-generated images we encourage art teachers to explore how it fits into their curriculum.

Artists bio
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Hannen Wolfe

Hannen Wolfe (PhD, Media Arts and Technology; MS, Computer Science) is an artist and Assistant Professor at Colby College. Their research is at the intersection of art and computation, building interactive art installations and staging robot performances that uplift underrepresented voices, question how we use technology, and dismantle systemic and structural inequalities. Their work has been shown at SIGGRAPH Art Gallery, New Technological Art Award, ISEA, Contemporary Istanbul and others. Their research has been published in Leonardo and IEEE Transactions on Affective Computing.

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Charlotte Rogerson

Charlotte Rogerson is a software engineer living in San Fransisco and working at Google. In 2022, Charlotte graduated from Colby College with a Bachelor of Arts in computer science and studio art, concentrating in print and digital media. She currently works on the YouTube trust and safety team using machine learning to fight hate, harassment, and impersonation.

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Amanda Lilleston

Amanda Lilleston is an Assistant Professor of studio art at Colby College in Waterville, ME. Using printmaking techniques and paper joining, her work depicts a long and evolving relationship with human anatomy, physiology and ecology. Most of her creative ideas stem from experience working as a Wilderness EMT and as a lab technician in Anatomical Sciences at University of Michigan. She received her MFA from University of Michigan Stamps School of Art and Design and a BA in biology from Colorado College in Colorado Springs, CO. Amanda shows her print collages nationally and internationally.

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