iNNk: A Multi-Player Game to Deceive a Neural Network

Jennifer Villareale, Ana V. Acosta-Ruiz, Samuel Adam Arcaro, Thomas Fox, Evan Freed, Robert C. Gray, Mathias Löwe, Panote Nuchprayoon, Aleksanteri Sladek, Rush Weigelt, Yifu Li, Sebastian Risi, Jichen Zhu

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review


This paper presents iNNK, a multiplayer drawing game where human players team up against an NN. The players need to successfully communicate a secret code word to each other through drawings, without being deciphered by the NN. With this game, we aim to foster a playful environment where players can, in a small way,
go from passive consumers of NN applications to creative thinkers and critical challengers.
Original languageEnglish
Title of host publicationCHI PLAY '20: Extended Abstracts of the 2020 Annual Symposium on Computer-Human Interaction in Play
Number of pages4
Publication date1 Nov 2020
ISBN (Electronic)9781450375870
Publication statusPublished - 1 Nov 2020


  • Multiplayer drawing game
  • Human-NN interaction
  • Secret code communication
  • Creative engagement
  • Critical thinking


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