Predictability in Human-Robot Interactions for Autistic Children

A commonly used argument for using robots in interventions for autistic children is that robots can be very predictable. Even though robot behaviour can be designed to be perceived as predictable, a degree of perceived unpredictability is unavoidable and may sometimes be desirable to some extent. To balance the robot's predictability for autistic children, we will need to gain a better understanding of what factors influence the perceived (un)predictability of the robot, how those factors can be taken into account through the design of the interaction, and how they influence the autistic child-robot interaction. In our work, we look at a specific type of predictability and define it as “the ability to quickly and accurately predict the robot's future actions”. Initial results show that seeing the cause of a robot's responsive actions influences to what extent it is perceived as being unpredictable and its competence. In future work, we will investigate the effects of the variability of the robot's behaviour on the perceived predictability of a robot for both typically developing and autistic individuals.

[1]  V. Manera,et al.  Grasping intentions: from thought experiments to empirical evidence , 2012, Front. Hum. Neurosci..

[2]  Stefan Kopp,et al.  To Err is Human(-like): Effects of Robot Gesture on Perceived Anthropomorphism and Likability , 2013, International Journal of Social Robotics.

[3]  B. Scassellati,et al.  Robots for use in autism research. , 2012, Annual review of biomedical engineering.

[4]  U. Castiello,et al.  The case of Dr. Jekyll and Mr. Hyde: A kinematic study on social intention , 2008, Consciousness and Cognition.

[5]  G. Csibra,et al.  'Obsessed with goals': functions and mechanisms of teleological interpretation of actions in humans. , 2007, Acta psychologica.

[6]  Kerstin Dautenhahn,et al.  ROBOTS AS SOCIAL ACTORS: AURORA AND THE CASE OF AUTISM , 1999 .

[7]  D. Sarko,et al.  Improving therapeutic outcomes in autism spectrum disorders: Enhancing social communication and sensory processing through the use of interactive robots. , 2017, Journal of psychiatric research.

[8]  Tom Ziemke,et al.  Robot-assisted therapy for autism spectrum disorders with (partially) autonomous control: Challenges and outlook , 2012, Paladyn J. Behav. Robotics.

[9]  P. Leseman,et al.  Unraveling the nature of autism: finding order amid change , 2015, Front. Psychol..

[10]  U. Castiello,et al.  Cues to intention: The role of movement information , 2011, Cognition.

[11]  J. Wagemans,et al.  Precise minds in uncertain worlds: predictive coding in autism. , 2014, Psychological review.

[12]  R. Held,et al.  Autism as a disorder of prediction , 2014, Proceedings of the National Academy of Sciences.

[13]  Karl J. Friston,et al.  An aberrant precision account of autism , 2014, Front. Hum. Neurosci..

[14]  Ruzena Bajcsy,et al.  Communicating intent on the road through human-inspired control schemes , 2016, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[15]  Andrea Lockerd Thomaz,et al.  Generating anticipation in robot motion , 2011, 2011 RO-MAN.

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

[17]  D. Burr,et al.  When the world becomes ‘too real’: a Bayesian explanation of autistic perception , 2012, Trends in Cognitive Sciences.

[18]  Christoph Bartneck,et al.  Do as I say: exploring human response to a predictable and unpredictable robot , 2015, BCS HCI.