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Data, the city and the public object

Adam Greenfield is the principal designer of Urbanscale, a design firm that focuses on design for networked cities and citizens. He’s interested in the challenge of building spaces that support civic life, public debates, and the use of public space.

The networked city isn’t a proximate future, it’s now. We’ve got a pervasively, comprehensively instrumented population through mobile phones. We have widespread adoption of locative and declarative media through tools like Fourquare and systems of sentiment analysis. And we’re starting to see “declarative objects”, items in public spaces like the London Bridge, which now tweets in its own voice using data scraped from a website. Objets start having informational shadows, like a building in Tokyo, literally clad in a QR code – you can “click” on the building and read more about it.

We’re starting to see cities that have objects, buildings and spaces that are gathering, processing, displaying, transmitting, and taking action on information. We’re subject to new modes of surveillance which aren’t always visual. Tens of millions of people are
already exposed to this, which suggests we may need a new theory and jurisprudence around public objects.

Offering a taxonomy of public objects, Adam starts with the example of the Välkky traffic sensor. This detects the movement of people and bikes in a crosswalk and triggers a bright LED light to warn motorists. This is very important in Finland, which is very dark 20 hours a day, 10 months of the year. He describes this as “prima facie unobjectionable, because the data is not uploaded, not archived, and because there’s a clear public good.

Another example is an ad in the subway system in Seoul. There’s a red carpet in front of a billboard. Walk on it, and the paparazzi in an animated billboard will swivel and photograph you. It’s mildly disruptive and disrespectful, and there’s no consensus public good. On the plus side, it’s purely commercial – there’s no red herring of benefit. And it probably doesn’t rise to the threshold of harm.

And then there’s the soda machine. Adam shows us the Accure touch screen beverage machine in Tokyo, which uses a high resolution display to show you what beverages are available. Each customer is offered different consumables – an embedded camera guesses at age and gender and delivers beverage options to you based on that model. It’s prescriptive and insidiously normative. And it compares information with other vending machines. If you’re a bit abnormal – a man who likes beverages common in the female model, for instance – these systems leave you out of luck. And while they’re commercially viable, there’s no public good associated with this information gathering. We might put this into the same category as interactive billboards with analytics packages, like the Quividi VidiReports, which detects age, gender, and even gaze. There is no opt out – you’re a data point even if you turn away from the ad.

How do we think about these systems when power resides in a network? Adam gives the example of an access control bollard in Barcelona, a metal pile that rises out of the ground to block access to a street unless you present an RFID that gives you permission to pass. This system relies on an embedded sensor grid, RFID system, signage, and traffic law all interacting together. It’s a complex, network system that we largely interact with through that bollard. It’s even easier to understand these systems when they exist solely through code.

There’s a class of public objects that we need to define and have a conversation about. Adam proposes that they include any discrete object in the common spatial domain intended for general use, located on public right of way, or that have de facto shared access to the public. When we build these systems, Adam says, we should design in ways that the data is open and available. That means offering an API, and making data accessible in a way that’s nonrivalrous and nonexcludable.

An open city necessarily has an more open attack surface. It’s more open to griefing and hacking. We need a great deal of affirmative value to run this risk. And we need to develop protocols and procedures to establish precedence and deconfliction around these objects. We’re roughly a century into the motor car in cities and we still don’t handle cars well, never mind these public objects.

Adam advocates a move against the capture of public space by private interest and towards a fabric of freely discoverable, addressable, queryable and scriptable resources. We need to head towards a place where “right to the city” is underwritten by the technology of the space.

Jeffrey Huang of the Berkman Center and EPFL Media x Design Laboratory has been involved with the design of a “hyperpublic” campus in the deserts of Ras Al Khaimah, one of the seven Emirates of the UAE. The Sheik of the state has agreed to fund the joint development of the campus with Huang’s institution in Switzerland, and his design students have been focused on building a university campus that’s deeply public, both in terms of physical and architectural space.

One of the major constraints for the design is lowering water and energy usage. The goal is to make buildings make environmental sense using data. They’ve mapped the building site and located natural low points where water accumulates. The design makes use of these points as “micro-oasises”. The design for the building is large, open spaces around these points, an echo of the EPFL learning center in Laussane, Switzerland.

Within the building, a network of sensors can greet people by name and offer personal services to them. You can interact with people through data shadows, which physically track people through the building, a shadow cast on the wall that shows someone’s name, identity and interests.

He acknowledges the dangers of this system, making reference to Mark Shepard’s Sentient City Survival Kit and an umbrella whose visual pattern scrubs your data from surveillance. But he notes that there’s less need to design the private if hyperpublicness is adequately designed. We should build systems where everyone and no one owns the data, which are fully transparent.

Betsy Masiello from Google works on public policy issues and offers us a practicioner perspective on the topic of the hyperpublic. She tells us she originally misread the title of our session – “The risks and beauty of the Hyper-public life” and skipped over the risk part. She worried we might be celebrating a “Paris Hilton-like existence of life streaming,” making your identifiable behavior available to anyone who chooses to watch.

There’s a better way of thinking about data-driven lives and existences. Systems like Google Flu trends uses lots of discrete points of information to make predictions about health issues – this gets quite important when this helps us target outbreaks of diseases like dengue fever. Unlike the pure performance of a public life, we get public good that comes from big data analysis.

She offers a frame for analysis: predictive analytics based on your behavior, which use your data and make it clear how it’s used veruss systems that are predictive based on other people’s behaviors, like Google’s search, flu trends, and perhaps the soda machine Adam talks about. Both systems can be very valuable. But the risk is the collapse of contexts that happens in a hyperpublic life – the idea that data can be reidentified and attached to your identity.

She recalls Jonathan Franzen’s essay, “The Imperial Bedroom”, from 1998 about the Monica Lewinsky scandal. Franzen suggests that without shame, there’s no distinction between public and private. The more identifiable you are, the more likely you are to feel that shame.

The current challenge we face is contructing and managing multiple identities. Ideally, we’d have ways to manage an identity that includes a form of anonymity. It’s becoming trivial to reidentify people within sets of data. We may need to have policy interventions that put requirements on the data holders, punishing people who release information that allows people to be reidentified.

There’s an interesting argument that arises around privacy and transparency. Adam offers his frustration that Amazon continues recommending Harry Potter to him despite having 15 years of purchasing behavior data, none of which should indicate his desire to read fantasy. Jef sees this as a problem of too little data, not too much. Jeff Jarvis, moderating, criticizes Adam for asking for too much privacy and tells us he doesn’t want a world in which we can’t customize, and where we’re forced away from targeted data when it’s useful.

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