Qualitative and quantitative Analysis of consumers perception regarding anthropomorphic AI designs

Abstract Business intelligence and analytics are nowadays being integrated into diverse industries, from healthcare to customer relationship management and behavioral profiling, due to the competitive advantages that they offer. Nevertheless, most companies try to integrate as many forms of business intelligence systems as possible into different internal processes. This overall digitization applied to more and more business departments is being analyzed with both curiosity and reluctance. The decision regarding the implementation of innovative forms of automation is taken in an attempt to discover and solve business challenges. However, there are several issues involved, which need to be addressed. One of the risks that are being discussed in the research environment refers to the level of acceptance of artificial intelligence systems. The tolerance and overall readiness of the consumers towards innovation and technology is one of the critical factors which need to be determined before implementing disruptive business intelligence systems. Moreover, in an effort to make devices friendlier to consumers, some developers chose to assign anthropomorphic appearances and even create individual identities for each artificial intelligence system. In this context, it is important for most companies investing in intelligent automation systems to determine to which extend the use of anthropomorphic designs impacts the customer’s perception. The objective of this research paper is to analyze the unconscious reaction of consumers towards two opposite designs of artificial intelligence systems: a robotic-like form and a human-like design. Based on this difference, a photo collage was created figuring two pictures: one with a metallic robot having a conversation with a human being and one with a robot with a strong anthropomorphic figure found in the same situation. For the analysis, an eye tracking device was used, in order to measure the point of gaze, the unconscious motion of the eyes, along with the time spent on each fixation and the order in which different elements were fixated upon by the respondents. As the eye-tracking device can generate data in various forms, this research includes both qualitative and quantitative analyses of the results, which confirm the same hypothesis, regarding the consumer’s preference towards artificial intelligence systems with robotic designs.