Super-Big Market-Data: A Case Study, Walkthrough Approach to Amazon Go Cashierless Convenience Stores

Traditional communication theory assumes that all communicators are people and all machines are tools. However, artificial intelligence (AI) challenges traditional communication theory now that machines automate decision-making and author information independent of human coders. Human-machine communication (HMC) represents a radical departure from traditional comm theory by recognizing that machines are legitimate communicators that we communicate with, not just thru (Guzman, 2018). In this study, I use Amazon Go cashierless convenience store as a case of HMC to explore the imagined affordances of sensor fusion techniques. Marketed as “the future of shopping” Amazon Go is the first smart retail environment to deploy sensor fusion AI techniques. Here’s how the stores work: Customers download the Amazon Go mobile app and scan their unique QR code upon entering the store. Like scanning a commuter pass at a subway station, the mobile app functions as a digital passport that opens a turnstile and as a method of payment, thereby collapsing the space between access and the ability to pay. Instead of waiting in a checkout queue or scanning items, shoppers just walk out. Within the context of Amazon Go, shoppers’ mobile smartphone devices, weighted shelves, and computer vision cameras infer what shoppers buy through human action recognition (HAR). In this case study, I adapt and expand on existing methods to overcome the challenges of traditional communication theory. Using (1) semi-structured interviews, (2) the walkthrough method (Light, Burgess & Duguay, 2018), and (3) an ethnographic smart infrastructure walkthrough, I explore the imagined affordances of cashierless environments using three key constructs–affect, materiality, and mediation–to guide my research questions: 1. How are material affordances of commercial smart environments imagined among stakeholders? 2. How are the affective signatures of commercial smart environments imagined among stakeholders? 3. How are the mediated affordances of commercial smart environments imagined among stakeholders?