AI-Based Technical Approach for Designing Mobile Decision Aids

Abstract

Conversational Voice User Interfaces (VUIs) help us in performing tasks in a wide range of domains these days. While there have been several efforts around designing dialogue systems and conversation flows, little information is available about technical concepts to extract critical information for addressing the users’ needs. For conversational VUIs to function appropriately as a decision aid, artificial intelligence (AI) that recognizes and supports diverse user decision strategies is a critical need. Following the design principle proposed by Kwon et al. [1] regarding the conversational flow between the user and conversational VUI, we developed an AI-based mobile-decision-aid (MODA) that predictively models and addresses users’ decision strategies to facilitate users’ in-store shopping decision process. In this paper, technical details about how MODA processes users’ natural language queries and generate the most appropriate and intelligent recommendations have been discussed. This developmental approach provides broad implications to conversational VUIs for diverse complex decision-making contexts and decision-makers with a critical need for decision assistants.