A governance perspective on user acceptance of autonomous systems in Singapore

Abstract

Autonomous systems that operate without human intervention by utilising artificial intelligence are a significant feature of the fourth industrial revolution. Various autonomous systems, such as driverless cars, unmanned drones and robots, are being tested in ongoing trials and have even been adopted in some countries. While there has been a discussion of the benefits and risks of specific autonomous systems, more needs to be known about user acceptance of these systems. The reactions of the public, especially regarding novel technologies, can help policymakers better understand people's perspectives and needs, and involve them in decision-making for governance and regulation of autonomous systems. This study has examined the factors that influence the acceptance of autonomous systems by the public in Singapore, which is a forerunner in the adoption of autonomous systems. The Unified Technology Adoption and Use Theory (UTAUT) is modified by introducing the role of government and perceived risk in using the systems. Using structural equation modelling to analyse data from an online survey (n = 500) in Singapore, we find that performance expectancy, effort expectancy, social influence, and trust in government to govern autonomous systems significantly and positively impact the behavioural intention to use autonomous systems. Perceived risk has a negative relationship with user acceptance of autonomous systems. This study contributes to the literature by identifying latent variables that affect behavioural intention to use autonomous systems, especially by introducing the factor of trust in government to manage risks from the use of these systems and filling the gap by studying the entire domain of autonomous systems instead of a narrow focus on one application. The findings will enable policymakers to understand the perceptions of the public in regard to adoption and regulation, and designers and manufacturers to improve user experience.