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Learning to see: you are what you see

Published:28 July 2019Publication History

ABSTRACT

The authors present a visual instrument developed as part of the creation of the artwork Learning to See. The artwork explores bias in artificial neural networks and provides mechanisms for the manipulation of specifically trained-for real-world representations. The exploration of these representations acts as a metaphor for the process of developing a visual understanding and/or visual vocabulary of the world. These representations can be explored and manipulated in real time, and have been produced in such a way so as to reflect specific creative perspectives that call into question the relationship between how both artificial neural networks and humans may construct meaning.

References

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    • Published in

      cover image ACM Conferences
      SIGGRAPH '19: ACM SIGGRAPH 2019 Art Gallery
      July 2019
      126 pages
      ISBN:9781450363112
      DOI:10.1145/3306211

      Copyright © 2019 Owner/Author

      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 28 July 2019

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      Overall Acceptance Rate1,822of8,601submissions,21%

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