"Location is dead, the world is flat, and where you live no longer affects how effectively I can work with you." This is a mantra in Silicon Valley where working with someone from across the pond or the planet is common. Julia Grace explains that her team analyzed 20.000 meetings at IBM and found that 60% were global meetings, that time zone is no longer an indicator of location, and that thanks to social media, news no longer depends on the place where they happen to immediately spread around the globe. She says that the irrelevance of location is also true for online retail. It doesn't matter which warehouse the item was in or if it crossed the globe to get to you as long as it gets to your doorstep the next morning.
On the other hand, this is an increasingly location-aware world where 380 million people checked in on Foursquare last year, and Groupon, a website of local deals is growing faster than ever. Location is becoming simultaneously more and less relevant; this is the inspiration behind the title of Grace's talk: "Location is Dead! Long Live Location!"
In an ethnographic study, Julia Grace's team studied why people buy some things online and other things offline and concluded that there is a mix-and-match phenomenon of online search and buying with offline search and buying. She concluded that offline purchases happen because sometimes buying is a sensory experience as people want to feel and touch what they are about to buy. Buying can also be a social experience.
All the location-based services - Foursquare, Google Latitude, Facebook Places - know a lot about us and we know very little about them. Safeway knows what cereal you buy and what you normally buy in conjunction with that cereal. So does your credit card company. All this data has augmented our reality and location is the proxy to experience that reality, so we should use all that data and take advantage of it. She claims that big data is like a puzzle: the more data you get, the better picture you get of the whole. So she proposes that if we had all that data and buying history and fed it into an AI system like Watson (the IBM super-computer that answers questions posed in natural language and that went on Jeopardy to compete against human participants) we could have a better life, not fighting the crowds to figure out what product is best for you. We would have buying recommendations based on our past purchases and item use.
Julia H. Grace is a social computing researcher at the IBM Almaden Research Center in the User Sciences & Experience Research (USER) Group in San Jose, California. Her research is focused on how to use social networks and other social computing technologies in large enterprises to better facilitate communication and team cohesion. She received her Master of Science in Computer Science from the University of North Carolina at Chapel Hill; her thesis focused on fostering communication and collaboration in online communities. Julia is active in the SIGCHI (Computer Human Interaction) and CSCW (Computer Supported Collaborative Work) communities.
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Photo: Julia Grace