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Machine, Unlearning was created by a computer program that constructs “litanies” of questions by searching an automatically learned space for word clusters and contexts that are “near” a provided seed concept according to the machine-learned model. Ranging from obvious to awkward, natural to uncanny, these generated streams of inquiry work to frame the assumptions embedded within the model in a (somewhat) human-interpretable way. In the end, machine learning relies on data analysis and pattern recognition to achieve its goals. Machine, Unlearning, however, asks for a different type of analysis: examining, questioning, unlearning.

Part of the series Using Electricity.

Li Zilles is a language hacker and programmer based in Seattle, WA. They hold an MS in computer science from the University of Washington, where they researched machine learning and natural language processing. In addition to writing two previous computer-generated books, The Seeker and Our Story, Li is also known for creating over thirty Twitter bots under the internet handle @thricedotted.

Machine, Unlearning
September, 2018
Li Zilles
$21.00; 6″ x 8.25″
112 pgs.
ISBN 978-1-93-399667-7

 

 
 

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