[Colloq] [phds] Thesis Proposal - Measuring the Impact of Algorithms in Online Marketplaces - Le Chen - Monday, April 25th, 2-3 pm WVH 366

[lechen]

Title:Measuring the Impact of Algorithms in Online Marketplaces
Speaker: Le Chen
Date: Monday, April 25th
Time: 2:00pm-3:00pm

Location: 366WVH

Abstract:

The integration of Big Data and algorithms have revolutionized many aspects of modern life. One of the revolutions is happening in markets, where data-centric algorithms are gradually automating services that used to require manual operations. For example, Real-Time Bidding (RTB) algorithms are are widely adopted in the online advertising network, and are expected to grow from generating 31% of the revenue of the entire digital ads market in 2015 to 48% in 2020. Mortgage and credit lenders in the loan markets use algorithms to make lending decisions based on Big Data rather than traditional credit reports. Outside of advertising and financial markets, ride sharing companies like Uber and Lyft use surge pricing algorithms to dynamically balance the gaps between car supply and user demand. Sellers in e-commerce markets use dynamic pricing tools to adjust product prices and manage inventories in real-time. Surveys show that as of 2013, 13% of retailers had deployed dynamic pricing algorithms.

Algorithms are powerful tools that have the potential to improve the efficiency of markets, but come at a cost of possible harms. On one hand, algorithms can be beneficial: RTB maps billions of Internet users to customized advertisements based on their interests in real time, and thus increases the effectiveness for both advertisers and publishers in terms of advertising inventory sold. Similarly, ride sharing has redefined the transportation market by matching millions of drivers and riders around the globe in real-time. On the other hand, evidence shows that problems may be caused by algorithms, such as racial discrimination on Google's advertisement services, or unpredictable prices shown to users in online marketplaces.

Unfortunately, we currently lack measurement tools or methodologies to audit the behavior of these algorithms. As a result, we are unable to measure the impact of these algorithms on people. For example, the general public is unable to access the details about how credit scores and prices are calculated on online marketplaces, since algorithms are typically proprietary trade secrets. Similarly, for Machine Learning algorithms, the data for training the predicative models may also be unavailable. The lack of transparency surrounding algorithms and the data that powers them has led to concerns about whether they are being manipulated by companies to increase their own profit, and whether they are fair and unbiased to users.

In this proposal, my goal is to develop methodologies and build measurement tools to audit and understand the impact of algorithms in online marketplaces. We focus on three types of marketplaces: the ride sharing marketplace Uber, the e-commerce marketplace Amazon, and human labor marketplaces like Monster and Indeed. Algorithms play a crucial role in all three platforms, and potential fairness and manipulation issues caused by the algorithms may be present in these systems. First, I examine Uber's surge pricing algorithm to answer questions such as whether ride prices are true reflections of supply and demand dynamics, and whether surge prices can be manipulated by the company or passengers. Next, I investigate Amazon Marketplace and inspect two major and correlated algorithmic components that determine the product prices consumers need to pay: the Buy Box and dynamic pricing by third-party sellers. Finally, as a current ongoing project, we are exploring the ranking algorithms that power candidate search on hiring markets like Monster and Indeed. Unfortunately, if the ranking algorithms are poorly designed, they may cause recruiters to discriminate against job hunters based on their demographics.

Committee:

Prof. Alan Mislove
Prof. Christoph Riedl
Prof. Christo Wilson (advisor)
Prof. Ben Zhao (external examiner, UCSB)

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