scholarly journals The best task allocation process is to decide on one’s own: effects of the allocation agent in human–robot interaction on perceived work characteristics and satisfaction

Author(s):  
Alina Tausch ◽  
Annette Kluge

AbstractNew technologies are ever evolving and have the power to change human work for the better or the worse depending on the implementation. For human–robot interaction (HRI), it is decisive how humans and robots will share tasks and who will be in charge for decisions on task allocation. The aim of this online experiment was to examine the influence of different decision agents on the perception of a task allocation process in HRI. We assume that inclusion of the worker in the allocation will create more perceived work resources and will lead to more satisfaction with the allocation and the work results than a decision made by another agent. To test these hypotheses, we used a fictional production scenario where tasks were allocated to the participant and a robot. The allocation decision was either made by the robot, by an organizational unit, or by the participants themselves. We then looked for differences between those conditions. Our sample consisted of 151 people. In multiple ANOVAs, we could show that satisfaction with the allocation process, the solution, and with the result of the work process was higher in the condition where participants themselves were given agency in the allocation process compared to the other two. Those participants also experienced more task identity and autonomy. This has implications for the design of allocation processes: The inclusion of workers in task allocation can play a crucial role in leveraging the acceptance of HRI and in designing humane work systems in Industry 4.0.

Procedia CIRP ◽  
2016 ◽  
Vol 44 ◽  
pp. 216-221 ◽  
Author(s):  
D. Schröter ◽  
P. Kuhlang ◽  
T. Finsterbusch ◽  
B. Kuhrke ◽  
A. Verl

Kybernetes ◽  
2016 ◽  
Vol 45 (8) ◽  
pp. 1257-1272 ◽  
Author(s):  
Hooman Samani

Purpose The purpose of this paper is to propose a novel method for evaluation of human-robot affection. The model is inspired by the scientific methods of human-human love evaluation. This paper would benefit the researchers in the field of developing new technologies where emotional interaction is involved. Design/methodology/approach Among the two available options of Functional Magnetic Resonance Imaging (fMRI) and user study, the latter is adopted and the conventional method of Love Attitude Scale is transformed for human-robot interaction as Lovotics (love + robotics) Love Attitude Scale. A user study is conducted to evaluate the emotional effect of interaction with the robot. Findings The proposed method is employed in order to evaluate the performance of Lovotics robot. In total, 20 users experienced interaction with Lovotics robot and answered questionnaires which were designed based on the psychology of love, especially to measure love scales between the participants and the robot. Data from the user study are analyzed statistically to evaluate the overall performance of the designed robot. Research limitations/implications Various aspects including human to robot love styles, robot to human love styles, overall love values and gender study are investigated during the data analysis. The concept of human-robot affection is still in initial stage of development. Personal and social robots are increasing and much limitation from artificial intelligence, mechanical development and integration still exist. Practical implications This is a multidisciplinary research field utilizing fundamentals concepts from robotics, artificial intelligence, philosophy, psychology, biology, anthropology, neuroscience, social science, computer science and engineering. Social implications Considering the recent technical advancement in robotics which is brining robots closer to home, this paper aims to bridge the gap between human and robot affection measurement. The final goal is to introduce robots to the society which are useful and can be especially used to take care of those in need such as elderly. Originality/value This paper is one of the first kind to get inspired from scientific human love evaluation methods and apply that to human-robot application.


2009 ◽  
Author(s):  
Matthew S. Prewett ◽  
Kristin N. Saboe ◽  
Ryan C. Johnson ◽  
Michael D. Coovert ◽  
Linda R. Elliott

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