This morning, Steve Henn filed a report on National Public Radio as part of NPR Cities on growing video surveillance in U.S. cities’ public spaces. Henn’s story helps demonstrate how the motivation to fight crime can drive police departments to significantly increase surveillance assets, and how these cameras, by nature of collecting massive amounts of information, demand computational techniques to make sense of all the data. Enter 3VR, a San Francisco company that provides the software to interpret all those video sources in many of the ways I describe in Robot Futures: face recognition, gesture recognition, activity reconstruction, license plate identification. When we switch from image feeds to computing power, a slippery slope of connect-the-dots is natural: Henn describes the ability to not only track someone’s actions in the city park, but to watch them enter their car, then hand off the surveillance from camera to camera until you have a complete data set on everywhere they visited that day (of course your smartphone does this too, but your local police department doesn’t have a direct smartphone location feed so far as we know). Henn interviews Law Professor Laura Donohue who points out that while we expect surveillance to watch us, we still retain a reasonable expectation that we are not tracked throughout the day- everywhere we go. Data analytics for crime prevention introduces these new boundary-changing challenges to our expectations, but the business arm of New Mediocracy is approaching quickly too. 3VR’s website markets to department stores, too, with a white paper called “Leveraging Video Analytics to Boost Total In-store Performance.” The key insight 3VR communicates is that surveillance is not just about catching shoplifters: “Retailers can use analytics to track behavior and engagement..which adds greater depth to customer profiles.” 3VR’s white paper explains that their video technology can tell if customers compare two products, pick up a specific product, browse a collection of products, and can estimate demographic information about the shoppers. Our expectations of privacy will be constantly changing, and as boundaries shift so will companies’ expectations of how our personal actions can be monetized. Our very shopping behavior in physical stores can join the Internet-based trade in on-line customer behavior, where companies swap our behavioral information for big money. Surveillance cameras, combined with sophisticated computation, are a crossover technology that will absorb the physical world into the digital realm of the Internet.