Inequality in the Age of Pseudonymity
Aviv Yaish, Nir Chemaya, Lin William Cong, Dahlia Malkhi
TL;DR
The class of all Sybil-proof measures are characterized, and it is proved they must satisfy relaxed versions of the established properties, and it is shown that the structure imposed restricts the ability to assess inequality at a fine-grained level.
Abstract
Inequality measures such as the Gini coefficient are used to inform and motivate policymaking, and are increasingly applied to digital platforms. We analyze how measures fare in pseudonymous settings that are common in the digital age. A key challenge of such environments is the ability of actors to create fake identities under fictitious false names, also known as ``Sybils.'' While actors may do so to preserve privacy, we show that this can hamper inequality measurement: it is impossible for measures satisfying the literature's canonical set of desired properties to assess the inequality of an economy that harbors Sybils. We characterize the class of all Sybil-proof measures, and prove they must satisfy relaxed versions of the established properties. Furthermore, we show that the structure imposed restricts the ability to assess inequality at a fine-grained level. We then apply our results to prove that popular measures are not Sybil-proof, with the famous Gini coefficient being but one example out of many. Finally, we examine dynamics leading to the creation of Sybils in digital and traditional settings.