I recently finished my Ph.D. As a present, a friend of mine gave me a hand. Not help, which he had done during the process, but rather a battery-powered automated hand, cut off at the wrist, similar to that of Thing, the Addams Family’s servant from TV and film. In part of my thesis, and my research on automation, I’ve looked to Thing as a metaphor for IoT software automation. Thing, on TV, is a trusted friend who builds relationships with family members and can negotiate with others on their behalf. In fiction, and the representation of fiction, Thing works beautifully and embodies what a smart agent could be. It is aware of its surroundings, it builds trust. It connects people. Thing is a keeper of local knowledge. The Applin and Fischer (2013) Thing agent, is a software construct using deontic logic to encourage and support human agency, building trust in a relationship based context. The hand my friend gave me moved on a fixed path for several seconds, and then stopped until its button was pushed again. It looked like Thing, but it was only a physical representation, a simulation of physical form. In automation, data collection is not the same as building relationships, and community knowledge cannot easily be derived from quantitative Big Data. This is one of the more serious problems with Amazon Go.
Amazon Go is a grocery store concept that allows people who have activated the Amazon Go app on their mobile phone, to walk through an “authentication” turnstile into an Amazon Go supermarket. Once inside, people can “grab” what groceries they want or need, and walk out the door, without needing to check out, because Amazon’s “computer vision, sensor fusion, and deep learning” will calculate what people take, and charge them accordingly via the app. Amazon Go has a video on their website that explains all of this, and shows people “grabbing and going” with their groceries, stuffing them into bags or just holding onto them, and walking out. In the Amazon Go video, no one is shown talking to each other.
On the surface, Amazon Go may seem ideal to people who need food and lack time. Supermarkets are a mess. The current market I go to has long checkout lines as well as a huge navigation problem. Mostly the navigation problems are due to online shopping service workers, who are tracked and clocked and thus rush carts around the store to fulfill orders amidst others operating at a different pace (similar to what we will start to see as more autonomous vehicles join us in more numbers on the roads). This may not be any different for Amazon Go. People might prefer a store with no check out, but might take their time shopping and browsing and block progress for those harder core grabbers and goers. Amazon Go seems to be turning shoppers into mini versions of the Amazon order picking robots, clearly trying to leverage their warehouse technology to apply to grocery shopping. However, Amazon doesn’t seem interested in building trusted relationships with shoppers as Thing—if Thing were real. In Amazon’s world, shoppers are tracked, and measured and their data is reported back to Amazon, who isn’t sharing it for anyone’s benefit but Amazon’s. People’s bodily motion, response rate, etc. will be tracked as well, which is a huge forfeiture of privacy.
Amazon Go’s focus on “grab and go” seems to be about time savings. This is not unexpected, as Amazon has demonstrated more than a little Quantitative focus (bias). Amazon’s rush to quantify and automate has seemingly depleted its ability to examine both its impact on society, and its own limitations. Amazon does not demonstrate prioritizing people, or the personal side of automation and agency. The main metric that Amazon has focused on is saving people time, which has somehow evolved to be the thing to save, based on early manufacturing models of assembly line efficiency. It isn’t clear if Amazon Go is considering what the “grab and go” action does—does it train behavior on an aggregate scale? Does it have the potential to create long term damage to communities, as sociability is removed from the shopping experience?
Grabbing and going seems to be a revisited human theme in current society. It’s popular with toddlers, and has a history for adults as well. Through the ages, humans have plundered and looted as a “reward” of war; to make ends meet; and/or to enrich their own situation at the expense of those who are deemed to have more than enough. What is new is how it has resurged. A current trend in burglary is “grab and go.” Certain stores are targeted over others, and Apple stores are particularly vulnerable. The Burlingame, CA Apple store was recently robbed three times in this way, twice within four days. In about 10 seconds, 3 to 5 robbers entered an Apple store, untethered and grabbed devices on the tables closest to the front door, and ran out. In New York, a man “grabbed” an 86 pound bucket of gold flakes worth $1.6 million dollars off the back of a truck, and walked down 48th Street with it. “Grab and Go” is clearly a time saving strategy.
What robbers are doing with “Grab and Go” in each case is exploiting a vulnerability in a system—preying on predictable social interaction, or finding a loophole where there is no local surveillance. (We’ve seen other exploits of the same type , such as what happened on 9/11.) Exploiting vulnerabilities in a system allows for certain types of innovation, as well as exploitation. In innovation, Amazon Go is enabling human agency for ease of product procurement, while saving time for individuals, however this may be coming at the expense of the community group in a broader way, as it simultaneously exploits individuals for their behavior patterns.
Marketplaces throughout human history have been a vehicle for trading commodities, and one of their main functions has been to create a venue for people to exchange information and ideas, and to socialize. This social exchange is what enables us to cooperate with each other in broader ways outside of the marketplace. Additionally, because vendors interact with so many people in the community, those working in the marketplace are the keepers of community knowledge—the understanding in a holistic (or close to) way of the health of the community writ large.
In moving the marketplace to a commodified and quantified framework, Amazon has removed the sociability of the marketplace, which is a vehicle for both community cooperation, and the qualitative data of a community’s well-being, replacing it with its sole ownership of the aggregate of individual quantitative data. Amazon Go will be activated without any consideration of its impact to the community it will be deployed upon. Furthermore, the community knowledge that comes from trusted human relationships will now be seemingly “created” by analyzing Big Data algorithms, which will not produce anywhere near the same result—without broader contextual knowledge. Community knowledge is local and specific. It is also critical to the way that people cooperate and survive in their communities.
The power of Amazon Go is that it is creating a marketplace for people with time constraints and mobile phones, which is just about everyone. The problem is that in doing so, Amazon Go will be contributing to changing community structure even further than the advent and broad usage of mobile phones, and soon to be other autonomous based services. As we’ve migrated away from our local locales, relying more and more on our networks for community knowledge, we too, “grab and go” information and data, applying it only to ourselves and our lives. The problems arise when we need to communicate and cooperate in our local locale, but have a network that is distant and distributed, or based solely on quantitative data.
 Sally A. Applin earned her Ph.D. in Anthropology at the University of Kent at Canterbury, UK, working with the Centre for Social Anthropology and Computing (CSAC) where she researches the changing relationship between humans and algorithms, the impact of technology on culture, Maker culture, leading technologies, and the outcomes of network complexities as modeled by PolySocial Reality (PoSR). Sally holds a Masters degree from the graduate Interactive Telecommunications Program at NYU (ITP), and a BA in Conceptual Design from SFSU. Sally has had a career in the science museum design, computer software, telecommunications, innovation, insight, and product design/definition industries working as a Senior Researcher, and Senior Consultant. Sally is an Associate Editor of the IEEE Technology and Society Magazine, and Associate Editor of the IEEE Consumer Electronics Magazine (Societal Impacts Section), a member of IoT Council (a think tank for the Internet of Things (IoT)), and a board member of the Edward H. and Rosamond B. Spicer Foundation.