BatchVote: Voting Rules Designed for Auditability
Name
voting17_bv.pdf
Description
Accepted version
Size
427.67 KB
Format
Adobe PDF
Checksum (MD5)
14b0a9427be2d04a49d8541cfdc71652
Author(s)
Rivest, Ronald L
Stark, Philip B.
Perumal, Zara (Zara Alexandra)
Date Issued
November 2017
Journal
International Conference on Financial Cryptography and Data Security
Publisher
Springer International Publishing
Citation
Rivest, Ronald L. et al. "BatchVote: Voting Rules Designed for Auditability." International Conference on Financial Cryptography and Data Security, April 2017, Sliema, Malta, Springer, November 2017. © 2017 International Financial Cryptography Association
Version
Author's final manuscript
Abstract
We propose a family of novel social choice functions. Our goal is to explore social choice functions for which ease of auditing is a primary design goal, instead of being ignored or left as a puzzle to solve later. Our proposal, “BatchVote,” creates a social choice function f from an arbitrary “inner” social choice function g, such as instant-runoff voting (IRV), and an integer B, the number of batches. We aim to preserve flexibility by allowing g to be arbitrary, while providing the ease of auditing of a plurality election. To compute the winner of an election of n votes, the social choice function f partitions the votes into B batches of roughly the same size, pseudorandomly. The social choice function g is applied to each batch. The election winner, according to f, is the weighted plurality winner for the B outcomes, where the weight of each batch is the number of votes it contains. The social choice function f may be viewed as an “interpolation” between plurality (which is easily auditable) and g (which need not be). Auditing is simple by design: we can view f as being a (weighted) plurality election by B “supervoters,” where the bth supervoter’s vote is determined by applying g to the votes in batch b, and the weight of her vote is the number of votes in her batch. Since plurality elections are easy to audit, the election output can be audited by checking a random sample of “supervotes” against the corresponding paper records.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.1007/978-3-319-70278-0_20
