Behavioral Measurement of Trust in Automation

Stating that one trusts a system is markedly different from demonstrating that trust. To investigate trust in automation, we introduce the trust fall: a two-stage behavioral test of trust. In the trust fall paradigm, first the one learns the capabilities of the system, and in the second phase, the ‘fall,’ one’s choices demonstrate trust or distrust. Our first studies using this method suggest the value of measuring behaviors that demonstrate trust, compared with self-reports of one’s trust. Designing interfaces that encourage appropriate trust in automation will be critical for the safe and successful deployment of partially automated vehicles, and this will rely on a solid understanding of whether these interfaces actually inspire trust and encourage supervision.

[1]  Jaap Ham,et al.  Trusting a Virtual Driver That Looks, Acts, and Thinks Like You , 2015, Hum. Factors.

[2]  Wendy Ju,et al.  The Design of Implicit Interactions , 2015, Synthesis Lectures on Human-Centered Informatics.

[3]  Clifford Nass,et al.  The media equation - how people treat computers, television, and new media like real people and places , 1996 .

[4]  Daniel V. McGehee,et al.  Driver Reaction Time in Crash Avoidance Research: Validation of a Driving Simulator Study on a Test Track , 2000 .

[5]  David D. Woods,et al.  Cognitive Technologies: The Design of Joint Human-Machine Cognitive Systems , 1986, AI Mag..

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

[7]  Gavriel Salvendy,et al.  Handbook of Human Factors and Ergonomics , 2005 .

[8]  J. H. Davis,et al.  An Integrative Model Of Organizational Trust , 1995 .

[9]  Crystal L. Hoyt,et al.  Immersive Virtual Environment Technology as a Methodological Tool for Social Psychology , 2002 .

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

[11]  Wendy Ju,et al.  Joint Cognition in Automated Driving: Combining Human and Machine Intelligence to Address Novel Problems , 2015, AAAI Spring Symposia.

[12]  Donald A. Norman,et al.  Some observations on mental models , 1987 .

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

[14]  Clifford Nass,et al.  Computers are social actors , 1994, CHI '94.

[15]  Wijnand A. IJsselsteijn,et al.  Presence: concept, determinants, and measurement , 2000, Electronic Imaging.

[16]  Philip N. Johnson-Laird,et al.  Mental Models in Cognitive Science , 1980, Cogn. Sci..

[17]  Eui Park,et al.  MEASURING TRUST OF HUMAN OPERATORS IN NEW GENERATION RESCUE ROBOTS , 2008 .

[18]  Mark R. Lehto,et al.  Foundations for an Empirically Determined Scale of Trust in Automated Systems , 2000 .

[19]  Raja Parasuraman,et al.  Humans and Automation: Use, Misuse, Disuse, Abuse , 1997, Hum. Factors.

[20]  Mark S. Young,et al.  Malleable Attentional Resources Theory: A New Explanation for the Effects of Mental Underload on Performance , 2002, Hum. Factors.

[21]  C. Nass,et al.  Machines and Mindlessness , 2000 .

[22]  John D. Lee.  The Dynamics of Trust in a Supervisory Control Simulation , 1991 .

[23]  Thomas B. Sheridan,et al.  Human and Computer Control of Undersea Teleoperators , 1978 .