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The 411 on the new 311 app

A new iPhone application that reports civic disturbances like potholes and graffiti to the city is underwhelming at best.

The app, called 311 Universal [iTunes link], allows iPhone users to photograph instances of broken streetlights (and the like) and reports those directly to 311Toronto in an email containing the photo and coordinates of the problem.

It’s been touted as a positive step toward citizen engagement and improving city services.

But it doesn’t do either. Here’s why not:

311Universal is not exactly location-based, hence the “universal.” It’s uses a standard template that works in any number of cities, and relies on various other services to work.

The app uses Google to pinpoint the location of the problem, and the built-in Apple camera to take the photo. Both come free with the iPhone.

311 Toronto also is free to use (well, paid for in taxes).

So, essentially, 311 Universal collects a bunch of free, already-convenient services, loosely organizes them, and charges for it.

Its 99-cent cost in iTunes seems like a nominal enough fee. But, since it’s a generic, one-size-fits-all template for every city its present in, it was a one-time production cost.

There is no partnership – either in the creation or usage – with Toronto, or any of the cities it aims to serve. The profits are not shared, even though the legwork is performed by Toronto 311.

And speaking of legwork!

Toronto’s 311 could, ostensibly, be flooded with mistaken reports from broken street lights from Guelph or jurisdictions outside its purview. The app can’t tell the difference. The responsibility for sorting through all these iPhoned-in reports falls on Toronto.

This is not the sort of civic engagement Toronto needs.

The better organized city services app is Pittsburgh’s impressive iBurgh. It works with the municipality to manage all the reports it lets citizens file – Pittsburgh city employees can reject reports using the program. It’s also free, and made in Pittsburgh.

With the recent opening up of city data, a much better model is surely on its way.

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