An investigation on strategies for optimizing consumer trust in chatbots

The advancement of artificial intelligence (AI) gave rise to chatbots, which is a type of AI-powered software that communicates via natural language. Chatbots have been used in diverse contexts, delivering significant convenience to the consumers. Nonetheless, this technology encounters ambivalent attitudes from consumers. Some aspects of the chatbot technology are evoking distrustful attitudes among consumers, while the others are cultivating a sense of trust. Thus, the objective of the current paper is to outline and analyze key factors that affect consumer trust and elucidate strategies that firms can adopt to optimize trust. According to recent studies, consumer distrust primarily stems from algorithmic bias, privacy and security concerns, and the lack of algorithmic transparency; on the other hand, consumer trust is formed due to anthropomorphic attributes of chatbots, particularly warmth and competence. To reduce consumer distrust, companies are advised to first identify and minimize existing real risks in their products, then deliver transparency to the public to establish a trustworthy image. To increase trust, companies are suggested to improve upon the anthropomorphic attributes of chatbots. Contributions and limitations of the paper are also discussed to highlight areas that require further investigation in the field of chatbots as well as AI in general.