Art Machine Learning
This presentation is best thought of as an ongoing set of experiments that seek to combine computer science with media. These experiments are collectively called The Machine is Learning, and consist of images generated by training computers to watch and analyze print, television, film, and social media. Works created from The Machine is Learning incorporate many mediums and cross multiple disciplines, embrace the failures of machine seeing, the proven weaknesses of human perception, and the racial and gender biases encoded in mass media.
MFA Candidate
California College of the Arts
Benjamin De Kosnik is an artist working with hybrid media in multiple disciplines: one to three channel video art, animated GIF, new media, installations, experimental writing and publishing, documentation systems, legal instruments, horticulture, and works on paper. He has participated in juried group shows in Tokyo, Hong Kong, California, and Texas.
He was formerly a Principal Software Engineer at Red Hat specializing in developer tools, libraries, and runtimes. He is a member of the GNU project, and has served as a technical expert for the International Standards Organization working groups on the C and C++ languages, The Austin Group, and Linux Standard Base. He incorporates this technical background and his free software aesthetic of computation into his art experiments. His current interests are visual forms of metadata augmentation for computer vision, media remix and fan production, horticulture, and mapping global media piracy flows.
Benjamin earned his BA in Mathematics at the University of Texas at Austin, and is currently an MFA candidate in Fine Arts at California College of the Arts. He currently lives and works as an artist and engineer in San Francisco, California.
