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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
  • Drexel University

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

Abstract

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
Pages33-37
ISBN (Electronic)9781450375870
DOIs
Publication statusPublished - 1 Nov 2020
EventAnnual Symposium on Computer-Human Interaction in Play - Virtual event , VIRTUAL
Duration: 2 Nov 20205 Nov 2020

Conference

ConferenceAnnual Symposium on Computer-Human Interaction in Play
LocationVirtual event
CityVIRTUAL
Period02/11/202005/11/2020

Keywords

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

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