Steve Pepple

Big Smart, Small Smart, smartest

October 10, 2019 by Ted Cuzzillo

No sooner had I posted the story in 2017 about Steve Pepple’s real-time visualization of a San Francisco parade’s data than a reader lodged an objection. “Building displays that show where the parties are,” wrote that reader, “could also show a gunman what sites to shoot up.”

True, Pepple’s LCD display, hanging in a neighborhood art project’s entryway for any passerby to see, posed that familiar risk. But let’s not all run away screaming in terror just yet. Pepple’s project — a bit player in the “smart cities” super-genre — deserves a long look at what it and others on the same scale may offer.

How much additional risk did his project pose? Slight. Pepple points out that scouting for targets is easy enough even without his guide. If the would-be shooter wants a small event, he looks for crowds and noise. If he thinks his gun rates a big event, he looks for police.

What benefit did Pepple’s LCD screen offer? Again, slight. At least its immediate benefit. The LCD was up and down in a day — a confection that went down like a piece of good chocolate.

A comparable balance arose a century ago. Electricity let people read at night at last and powered motors where steam or muscular effort had been required. Those features had to balance out with the danger of electrocution and fire. We opted for opportunity. Electricity has since become such a pivotal technology that now we say that data is “the new electricity” (as we discard the tired “new oil” metaphor).

Electricity became pivotal partly because it’s easy enough for most people can learn to work with it. Courses and books are easy to find and are very inexpensive. Clever people holed up to invent electrical machines and circuitry in your own garages as long as there have been light bulbs to work under. For equipment, supplies, and free expertise, there’s plentiful retail and even your next door neighbor.

It didn’t become useful solely on the backs of AT&T Labs and other enterprise-scale outfits. The many unknown, everyday bit players had a hand in it too.

Though Pepple’s screen was up and down in a day, Pepple himself is still in the civic tech game — along with the growing ranks of others like him. Community know-how, especially with the help of Code for America and perhaps similar organizations, continues to build.

Those volunteers — coders, UX designers, project managers, and others — constitute Small Smart. Meanwhile, Big Smart vendors are the colonizers usually associated with “smart cities.” That’s where the city-wide projects happen: millions of dollars spent, hundreds of city planning staff hours spent poring over plans, months with vendors hammering out data rights, then more months of public inconvenience with torn up intersections — all to embed cutting-edge sensors and other tech that may or may not work.

Each, Small Smart and Big Smart both, bring along a risk-versus-benefit tradeoff.

Look at each type closely, though, and you begin to suspect, as I do, that Small Smart may just offer something more — something that gets woven into the community instead of becoming obsolete with every upgrade.

The volunteer, small scale projects, widely known as “civic tech” build a city’s culture of smart. That’s what makes cities truly smart.

My theory is based on the Cities and the Wealth of Nations by Jane Jacobs, specifically her theory of import replacement.

A fun, lively path to smarter cities

May 2, 2017 by Ted Cuzzillo

San Francisco-area designer Steve Pepple wondered whether data could help him explore neighborhoods — on the way to helping city planners build better, perhaps “smarter” cities.

He describes in a fun post on Medium, a genuine “data story,” how he set out to help people find “pockets of activity, vibrance, and new things.”

First, he joined a do-it-yourself project called Sense Your City. Sensors around the world reaped “hyper-local data about environmental conditions, such as noise, dust, light, and pollutants.” That data led to “pockets of activity, vibrance, and new things.” In San Francisco, he writes, “you could see when the fog rolls in.”

That sounds like fun, but could he find a key insights about mobility, housing, or neighborhood change? He had frustrating moments. “I had a bunch of data to work with,” he writes. His many sources included DataSF, San Francisco Planning, SPUR, and the City of Oakland. But he didn’t know what he was doing. Perhaps worse, “I was stymied by trying to find a significant, cumulative insight by cobbling together and analyzing all the data.”

He had been inspired by one man’s discovery who famously found such an insight in San Francisco rental data. Eric Fischer had pored over newspaper ads back to 1948 and surprised urbanists with his conclusion: the usual levers for regulating demand wouldn’t solve the city’s housing crisis.

Smaller experiments

With no big discoveries in sight, Pepple turned to shorter experiments. Apparently as part of a fellowship with Stamen Design and Gray Area Foundation for the Arts, he looked at Instagram photos to track street movement, such as some taken during the 2015 Pride Parade. Data from those photos showed events like parade formation and, in the afternoon, a drift into block parties.

His Medium post includes a short series of visualizations that are more fun and vibrant than you might think any “smart city” has a right to be. With “color quantization,” he created a “spatial database of color” that showed parks and murals in the Mission District. In another map, colors expressed “density of people and establishments,” with brighter and more colorful buildings showing the most active.

Tangible, street-level meaning came in large, street-level screens…that showed passersby how they could “interact with data about their neighborhood and arrive at their own discoveries.”

Clues

It was his work with the urban designers and architects Perkins + Will that his approach had what I find the most interesting and possibly the most meaningful clue. Pepple and team could see and hear neighborhoods with the most activity. Could that be found with data? Indeed, data tracked activity and what people said about the places where it occurred; social media helped characterize those places; mapping tools connected hotspots.

A look at the maps Pepple and team produced shows that transit, living space, restaurants, and other amenities fail to anchor social hotspots. Fine, but why? If the data can reveal this, perhaps it can go the rest of the way.

Keep your eye on Pepple. His playful and often fun analysis puts a bright, even inspiring face on urban data.

Thanks to Stephanie Langenfeld McReynolds, vice president of marketing at Alation, for alerting me to Pepple’s work.