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PROTOTYPING IN SOCIAL VR: ANTICIPATE THE UNANTICIPATED OUTCOMES OF INTERACTIONS BETWEEN AI-POWERED SOLUTIONS AND USERS

Published online by Cambridge University Press:  27 July 2021

Elena Mariani ,
Finn Søren Casper Kooijman ,
Priyanka Shah  and
Niya Stoimenova
Elena Mariani
Affiliation:
Politecnico di Milano
Finn Søren Casper Kooijman*
Affiliation:
Delft University of Technology;
Priyanka Shah
Affiliation:
Delft University of Technology;
Niya Stoimenova
Affiliation:
Delft University of Technology;
*
Kooijman, Finn Søren Casper, Delft University of Technology, Industrial Design Engineering, Netherlands, The kooijmanfinn@gmail.com

Abstract

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Interactions of users with AI powered solutions (AIPS) have the potential to affect collective behaviours and amplify unanticipated outcomes. Product developers, organisations, and companies are increasingly being expected to take responsibility for the unanticipated outcomes of their products. In this paper we explore a proactive approach to prototyping AIPS-user interactions using Social Virtual Reality (SVR) environments that allows for the anticipation of potential outcomes. We contend that doing so would limit the detrimental effect outcomes could have on product developers' resources and reputation

Keywords

Virtual realityVirtual PrototypingArtificial intelligenceDesign processUnanticipated outcomes

Information

Type
Article
Information
Proceedings of the Design Society , Volume 1: ICED21 , August 2021 , pp. 2491 - 2500
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2021. Published by Cambridge University Press

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