Peeking Beneath the Hood of Uber

Recently, Uber has emerged as a leader in the "sharing economy". Uber is a "ride sharing" service that matches willing drivers with customers looking for rides. However, unlike other open marketplaces (e.g., AirBnB), Uber is a black-box: they do not provide data about supply or demand, and prices are set dynamically by an opaque "surge pricing" algorithm. The lack of transparency has led to concerns about whether Uber artificially manipulate prices, and whether dynamic prices are fair to customers and drivers. In order to understand the impact of surge pricing on passengers and drivers, we present the first in-depth investigation of Uber. We gathered four weeks of data from Uber by emulating 43 copies of the Uber smartphone app and distributing them throughout downtown San Francisco (SF) and midtown Manhattan. Using our dataset, we are able to characterize the dynamics of Uber in SF and Manhattan, as well as identify key implementation details of Uber's surge price algorithm. Our observations about Uber's surge price algorithm raise important questions about the fairness and transparency of this system.

[1]  Karrie Karahalios,et al.  FeedVis: A Path for Exploring News Feed Curation Algorithms , 2015, CSCW Companion.

[2]  Roxana Geambasu,et al.  XRay: Enhancing the Web's Transparency with Differential Correlation , 2014, USENIX Security Symposium.

[3]  Vijay Erramilli,et al.  Detecting price and search discrimination on the internet , 2012, HotNets-XI.

[4]  Latanya Sweeney,et al.  Discrimination in online ad delivery , 2013, CACM.

[5]  Cecilia Mascolo,et al.  OpenStreetCab: Exploiting Taxi Mobility Patterns in New York City to Reduce Commuter Costs , 2015, ArXiv.

[6]  David Lazer,et al.  Measuring Price Discrimination and Steering on E-commerce Web Sites , 2014, Internet Measurement Conference.

[7]  Saikat Guha,et al.  Challenges in measuring online advertising systems , 2010, IMC '10.

[8]  Vijay Erramilli,et al.  Crowd-assisted search for price discrimination in e-commerce: first results , 2013, CoNEXT.

[9]  Michael Luca,et al.  Digital Discrimination: The Case of Airbnb.com , 2014 .

[10]  Karrie Karahalios,et al.  Auditing Algorithms : Research Methods for Detecting Discrimination on Internet Platforms , 2014 .

[11]  A. Krueger,et al.  An Analysis of the Labor Market for Uber’s Driver-Partners in the United States , 2016 .

[12]  Michael Luca,et al.  Digital Discrimination: The Case of Airbnb.com , 2014 .

[13]  Balachander Krishnamurthy,et al.  Measuring personalization of web search , 2013, WWW.

[14]  Laura A. Dabbish,et al.  Working with Machines: The Impact of Algorithmic and Data-Driven Management on Human Workers , 2015, CHI.

[15]  Arvind Narayanan,et al.  The Web Never Forgets: Persistent Tracking Mechanisms in the Wild , 2014, CCS.