The Transfer of Human Trust in Robot Capabilities across Tasks

Trust is crucial in shaping human interactions with one another and with robots. This work investigates how human trust in robot capabilities transfers across tasks. We present a human-subjects study of two distinct task domains: a Fetch robot performing household tasks and a virtual reality simulation of an autonomous vehicle performing driving and parking maneuvers. Our findings lead to a functional view of trust and two novel predictive models---a recurrent neural network architecture and a Bayesian Gaussian process---that capture trust evolution and transfer via latent task representations. Experiments show that the two proposed models outperform existing approaches when predicting trust across unseen tasks and participants. These results indicate that (i) a task-dependent functional trust model captures human trust in robot capabilities more accurately, and (ii) trust transfer across tasks can be inferred to a good degree. The latter enables trust-based robot decision-making for fluent human-robot interaction. In particular, our models can be used to derive robot policies that mitigate under-trust or over-trust by human teammates in collaborative multi-task settings.

[1]  Siddhartha S. Srinivasa,et al.  Human-Robot Mutual Adaptation in Shared Autonomy , 2017, 2017 12th ACM/IEEE International Conference on Human-Robot Interaction (HRI.

[2]  Jeffrey Dean,et al.  Efficient Estimation of Word Representations in Vector Space , 2013, ICLR.

[3]  John D. Lee,et al.  Trust, self-confidence, and operators' adaptation to automation , 1994, Int. J. Hum. Comput. Stud..

[4]  Ning Wang,et al.  Trust calibration within a human-robot team: Comparing automatically generated explanations , 2016, 2016 11th ACM/IEEE International Conference on Human-Robot Interaction (HRI).

[5]  Yiannis Demiris,et al.  Spatio-Temporal Learning With the Online Finite and Infinite Echo-State Gaussian Processes , 2015, IEEE Transactions on Neural Networks and Learning Systems.

[6]  Holly A. Yanco,et al.  Impact of robot failures and feedback on real-time trust , 2013, 2013 8th ACM/IEEE International Conference on Human-Robot Interaction (HRI).

[7]  Jessie Y. C. Chen,et al.  Human-robot interaction: Developing trust in robots , 2012, 2012 7th ACM/IEEE International Conference on Human-Robot Interaction (HRI).

[8]  Siddhartha S. Srinivasa,et al.  Game-Theoretic Modeling of Human Adaptation in Human-Robot Collaboration , 2017, 2017 12th ACM/IEEE International Conference on Human-Robot Interaction (HRI.

[9]  Yiannis Demiris,et al.  When and how to help: An iterative probabilistic model for learning assistance by demonstration , 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[10]  Gregory Dudek,et al.  OPTIMo: Online Probabilistic Trust Inference Model for Asymmetric Human-Robot Collaborations , 2015, 2015 10th ACM/IEEE International Conference on Human-Robot Interaction (HRI).

[11]  Siddhartha S. Srinivasa,et al.  Planning with Trust for Human-Robot Collaboration , 2018, 2018 13th ACM/IEEE International Conference on Human-Robot Interaction (HRI).

[12]  Jessie Y. C. Chen,et al.  A Meta-Analysis of Factors Affecting Trust in Human-Robot Interaction , 2011, Hum. Factors.

[13]  Kevin Li,et al.  Evaluating Effects of User Experience and System Transparency on Trust in Automation , 2017, 2017 12th ACM/IEEE International Conference on Human-Robot Interaction (HRI.

[14]  Anca D. Dragan,et al.  Establishing Appropriate Trust via Critical States , 2018, 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[15]  Gregory Dudek,et al.  Towards Modeling Real-Time Trust in Asymmetric Human-Robot Collaborations , 2013, ISRR.

[16]  Alan R. Wagner,et al.  Overtrust of robots in emergency evacuation scenarios , 2016, 2016 11th ACM/IEEE International Conference on Human-Robot Interaction (HRI).

[17]  Lydia E. Kavraki,et al.  The Open Motion Planning Library , 2012, IEEE Robotics & Automation Magazine.

[18]  Scott Sanner,et al.  Deep Sequential Recommendation for Personalized Adaptive User Interfaces , 2017, IUI.

[19]  N. Moray,et al.  Trust in automation. Part II. Experimental studies of trust and human intervention in a process control simulation. , 1996, Ergonomics.

[20]  Rino Falcone,et al.  Trust Theory: A Socio-Cognitive and Computational Model , 2010 .

[21]  Lehel Csató,et al.  Sparse On-Line Gaussian Processes , 2002, Neural Computation.

[22]  Jürgen Schmidhuber,et al.  Long Short-Term Memory , 1997, Neural Computation.

[23]  Luca Antiga,et al.  Automatic differentiation in PyTorch , 2017 .

[24]  Yoshua Bengio,et al.  Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation , 2014, EMNLP.

[25]  Raja Parasuraman,et al.  Automation- Induced "Complacency": Development of the Complacency-Potential Rating Scale , 1993 .

[26]  N Moray,et al.  Trust, control strategies and allocation of function in human-machine systems. , 1992, Ergonomics.

[27]  Jeffrey Pennington,et al.  GloVe: Global Vectors for Word Representation , 2014, EMNLP.

[28]  Jimmy Ba,et al.  Adam: A Method for Stochastic Optimization , 2014, ICLR.

[29]  Radford M. Neal Monte Carlo Implementation of Gaussian Process Models for Bayesian Regression and Classification , 1997, physics/9701026.

[30]  Yiannis Demiris,et al.  Learning assistance by demonstration , 2015, J. Hum. Robot Interact..

[31]  Thomas B Sheridan,et al.  Research and Modeling of Supervisory Control Behavior. Report of a Workshop , 1984 .

[32]  Carl E. Rasmussen,et al.  Gaussian processes for machine learning , 2005, Adaptive computation and machine learning.

[33]  Thomas L. Griffiths,et al.  Modeling human function learning with Gaussian processes , 2008, NIPS.

[34]  Siddhartha Srinivasa,et al.  The Role of Trust in Decision-Making for Human Robot Collaboration , 2017 .

[35]  Sebastian Thrun,et al.  Path Planning for Autonomous Vehicles in Unknown Semi-structured Environments , 2010, Int. J. Robotics Res..

[36]  Indu P. Bodala,et al.  Human Trust in Robot Capabilities across Tasks , 2018, HRI.

[37]  John D. Lee,et al.  Trust in Automation: Designing for Appropriate Reliance , 2004, Hum. Factors.

[38]  Wojciech Zaremba,et al.  An Empirical Exploration of Recurrent Network Architectures , 2015, ICML.

[39]  Bonnie M. Muir,et al.  Trust in automation. I: Theoretical issues in the study of trust and human intervention in automated systems , 1994 .