Earlier this month, news outlets were buzzing about Amazon Go, Amazon’s latest foray into brick and mortar shopping. Using the Amazon Go app, shoppers log in, pull goods from the shelves, and using a combination of “computer vision, sensor fusion, and deep learning,” the shopper’s account is charged for the items they select. The official video demonstrates how the “smart” shelves can detect when an item is returned to the shelf, so shoppers are only charged for what they take.
According to the Wall Street Journal, this is part of “Project Como, Amazon’s plan to capture more food sales, opening the door to a key driver of consumer spending that would broaden the online retailer’s increasing dominance in the retail market.” Amazon is following in the footsteps of big box stores like Target and Wal-Mart that use grocery sales to drive traffic, in the hopes of turning a profit from the higher-margin products in shoppers’ carts like home goods and clothing.
Vanity Fair identified a bigger strategic picture for Amazon. As Amazon Go matches purchases to an individual user account, “The company can collect loads of data… based on their purchase history and the items they browse in-store, which in turn allows the company to serve more personalized recommendations online.”
“It’s not that retail tech companies haven’t already been hard at work tracking people as they explore physical stores and shop. A host of companies with names like RetailNext, Euclid, and Nomi, among others, are all part of this trend,” Wired reports. “It’s in a store’s interest to track people, after all, not just because they can target and upsell customers on more products and in-store promotions. Aggregate data on how customers move within a store and what they buy can help stores project purchasing trends, decide how to rearrange a layout, and create better reports for their shareholders, among other benefits.”
The implication for retail is obvious — in a world where self-checkout counters cause almost as much hassle as they are meant to relieve, and still require humans to fix human errors, Amazon Go has eliminated the cause of the bottleneck. That same article predicts a further move toward replacing workers with automation. Amazon has added more than 30,000 robots to its warehouses since 2014, causing a hiring slowdown.
This move is mirrored by Uber’s launch of driverless cars in San Francisco. “Uber doesn’t expect to deploy fully autonomous, completely empty vehicles to pick up passengers anytime soon. The technology isn’t there yet, nor is the public ready to accept a vision of ghost vehicles roaming the streets at all hours.” However, Uber C.E.O. Travis Kalanick has a far-reaching driverless vision of the future saying, “The reason Uber could be expensive is because you’re not just paying for the car—you’re paying for the other dude in the car. When there’s no other dude in the car, the cost of taking an Uber anywhere becomes cheaper than owning a vehicle.”
In light of these developments, tech leaders like Y Combinator’s Sam Altman are advocating for a universal basic income, “a guaranteed minimum stipend that the government would pay to everyone, ensuring some cushion as technological change roils the labor market, and allowing workers to develop new skills. In the end, it won’t be globalization, but automation, that will transform the U.S. economic landscape.”
What are your thoughts about the implications for data collection, the economy and jobs? Let us know in the comments or contact us.