The Waze Effect: AI & The Public Commons

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A couple of weeks ago my wife and I were heading across the San Rafael bridge to downtown Oakland for a show at the Fox Theatre. As all Bay area drivers know, there’s a historically awful stretch of Interstate 80 along that route — a permanent traffic sh*t show.

I considered taking San Pablo Ave., a major thoroughfare which parallels the freeway. But my wife fired up Waze instead, and we proceeded to follow an intricate set of instructions which took us onto frontage roads, side streets, and counter-intuitive detours. Despite our shared unease (unfamiliar streets through some blighted neighborhoods), we trusted the Waze algorithms — and we weren’t alone. In fact, a continuous stream of automobiles snaked along the very same improbable route — and inside the cars ahead and behind me, I saw glowing blue screens delivering similar instructions to the drivers within.


About a year or so ago I started regularly using the Waze app — which is to say, I started using it on familiar routes: to and from work, going to the ballpark, maneuvering across San Francisco for a meeting. Prior to that I only used Waze as an occasional replacement for Google Maps — when I wasn’t sure how to get from point A to point B.

Of course, Waze is a revelation for the uninitiated. It essentially turns your car into an autonomous vehicle, with you as a simple robot executing the commands of an extraordinarily sophisticated and crowd-sourced AI.

But as I’m sure you’ve noticed if you’re a regular “Wazer,” the app is driving a tangible “flocking” behavior in a significant percentage of drivers on the road. In essence, Waze has built a real time layer of data and commands over our current traffic infrastructure. This new layer is owned and operated by a for-profit company (Google, which owns Waze), its algorithms necessarily protected as intellectual property. And because it’s so much better than what we had before, nearly everyone is thrilled with the deal (there are some upset homeowners tired of those new traffic flows, for instance).

Since the rise of the automobile, we’ve managed traffic flows through a public commons — a slow moving but accountable ecosystem of local and national ordinances (speed limits, stop signs, traffic lights, etc) that were more or less consistent across all publicly owned road ways.

Information-first tech platforms like Waze, Uber, and Airbnb are delivering innovative solutions to real world problems that were simply impossible for governments to address (or even imagine).

At what point will Waze or something like it integrate with the traffic grid, and start to control the lights?

I’ve written before about how we’re slowly replacing our public commons with corporate, for-profit solutions — but I sense a quickening afoot. There’s an inevitable collision between the public’s right to know, and a corporation’s need for profit (predicated on establishing competitive moats and protecting core intellectual property). How exactly do these algorithms choose how best to guide us around? Is it fair to route traffic past people’s homes and/or away from roadside businesses? Should we just throw up our hands and “trust the tech?”

We’ve already been practicing solutions to these questions, first with the Web, then with Google search and the Facebook Newsfeed, and now with Waze. But absent a more robust dialog addressing these issues, we run a real risk of creating a new kind of regulatory capture — not in the classic sense, where corrupt public officials preference one company over another, but rather a more private kind, where a for-profit corporation literally becomes the regulatory framework itself — not through malicious intent or greed, but simply by offering a better way.

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