Uber and Safer Cities

For some reason I have always liked talking to taxi drivers about their business.  Maybe it’s because my dad was a NYC taxi driver back in the 70s, or maybe it’s because driving a taxi is such a classic immigrant path to building a life here.  And it’s certainly because of the amount of tech and business model innovation in the transportation space.  

Last night I took an Uber home from the airport, and was talking to the driver about his experience with it.  He loves Uber — in the past 2 years, he switched from being a Boston city cab driver to being an Uber driver — and in the process traded $4000 / month in cab lease fees (what you pay a garage as a base rate to drive the cab — regardless of how much you earn) for a $700 / month car payment and $400 / month in insurance.  And he gets to have a vastly improved quality of work (managing his own business & time, driving in a nicer car, etc).

Of course there are tradeoffs — if the Uber business slows down, he’s still on the hook for that car payment.  And it’s possible that the number of Uber drivers will continue to increase (unconstrained by medallion restrictions, which in NYC cap taxis at 13,000), increasing competition and bringing down his margins.

But overall, he said that Uber changed his life (for the better).  Not everyone feels this way, but it’s one story.

Anyway, the most interesting thing he said was not about the business, but the impact on neighborhoods.  He said that Uber has radically increased the taxi / car service business in the city’s tough neighborhoods.  This comes across as sounding counter-intuitive since most tech-driven transportation platforms (like Uber, Lyft and Sidecar — but especially Uber) are derided as “For Yuppies By Yuppies”.  But the reason makes perfect sense: with Uber, you know your passenger.

So whereas a traditional taxi would hesitate to pick up fares in tough parts of town, because you never know who’s going to get in, Uber drivers can do this with much more confidence, since there is personal identity (and therefore accountability) built into the system.

This makes perfect sense in theory, and I’d be really interested to explore data that could test this out.  Especially as NYC gears up to offer mobile payments in traditional taxis.

This is a perfect example of Regulation 2.0 — using real-time / mobile accessible data to build trust and safety into a networked system.  And it points out the limitations of “1.0” regulation schemes (in this case taxi licensing), that don’t have access to such data and can hence only solve for part of the problem (in this case, protecting passengers from bad drivers).  And it’s a really great example of some of the unexpected benefits of allowing new, networked models to emerge.

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