An Immersive Investment Game to Study Human-Robot Trust

Sebastian Zörner , Emy Arts , Brenda Vasiljevic , Ankit Srivastava , Florian Schmalzl , Glareh Mir , Kavish Bhatia , Erik Strahl , Annika Peters , Tayfun Alpay , Stefan Wermter
Frontiers in Robotics and AI Volume 8, pages 139, doi: 10.3389/frobt.2021.644529 - Jun 2021 Open Access
Associated documents :  
As robots become more advanced and capable, developing trust is an important factor of human-robot interaction and cooperation. However, as multiple environmental and social factors can influence trust, it is important to develop more elaborate scenarios and methods to measure human-robot trust. A widely used measurement of trust in social science is the investment game. In this study, we propose a scaled-up, immersive, science fiction Human-Robot Interaction (HRI) scenario for intrinsic motivation on human-robot collaboration, built upon the investment game and aimed at adapting the investment game for human-robot trust. For this purpose, we utilize two Neuro-Inspired COmpanion (NICO) - robots and a projected scenery. We investigate the applicability of our space mission experiment design to measure trust and the impact of non-verbal communication. We observe a correlation of 0.43 (p  0.02) between self-assessed trust and trust measured from the game, and a positive impact of non-verbal communication on trust (p  0.0008) and robot perception for anthropomorphism (p  0.007) and animacy (p  0.00002). We conclude that our scenario is an appropriate method to measure trust in human-robot interaction and also to study how non-verbal communication influences a human’s trust in robots.


 	 author =  {Zörner, Sebastian and Arts, Emy and Vasiljevic, Brenda and Srivastava, Ankit and Schmalzl, Florian and Mir, Glareh and Bhatia, Kavish and Strahl, Erik and Peters, Annika and Alpay, Tayfun and Wermter, Stefan},  
 	 title = {An Immersive Investment Game to Study Human-Robot Trust}, 
 	 journal = {Frontiers in Robotics and AI},
 	 number = {},
 	 volume = {8},
 	 pages = {139},
 	 year = {2021},
 	 month = {Jun},
 	 publisher = {Frontiers},
 	 doi = {10.3389/frobt.2021.644529},