A Unified Evaluation of Two-Candidate Ballot-Polling Election Auditing Methods
Counting votes is complex and error-prone. Several statistical methods have been developed to assess election accuracy by manually inspecting randomly selected physical ballots. Two ‘principled’ methods are risk-limiting audits (RLAs) and Bayesian audits (BAs). RLAs use frequentist statistical infer...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Book |
| Language: | English |
| Published: |
Springer International Publishing
2021
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| Online Access: | https://hdl.handle.net/1721.1/129969 |
| _version_ | 1826197326628126720 |
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| author | Huang, Zhuoqun Rivest, Ronald L Stark, Philip B. Teague, Vanessa J. Vukcevic, Damjan |
| author2 | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory |
| author_facet | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Huang, Zhuoqun Rivest, Ronald L Stark, Philip B. Teague, Vanessa J. Vukcevic, Damjan |
| author_sort | Huang, Zhuoqun |
| collection | MIT |
| description | Counting votes is complex and error-prone. Several statistical methods have been developed to assess election accuracy by manually inspecting randomly selected physical ballots. Two ‘principled’ methods are risk-limiting audits (RLAs) and Bayesian audits (BAs). RLAs use frequentist statistical inference while BAs are based on Bayesian inference. Until recently, the two have been thought of as fundamentally different. We present results that unify and shed light upon ‘ballot-polling’ RLAs and BAs (which only require the ability to sample uniformly at random from all cast ballot cards) for two-candidate plurality contests, that are building blocks for auditing more complex social choice functions, including some preferential voting systems. We highlight the connections between the methods and explore their performance. First, building on a previous demonstration of the mathematical equivalence of classical and Bayesian approaches, we show that BAs, suitably calibrated, are risk-limiting. Second, we compare the efficiency of the methods across a wide range of contest sizes and margins, focusing on the distribution of sample sizes required to attain a given risk limit. Third, we outline several ways to improve performance and show how the mathematical equivalence explains the improvements. |
| first_indexed | 2024-09-23T10:45:58Z |
| format | Book |
| id | mit-1721.1/129969 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T10:45:58Z |
| publishDate | 2021 |
| publisher | Springer International Publishing |
| record_format | dspace |
| spelling | mit-1721.1/1299692022-09-27T14:49:02Z A Unified Evaluation of Two-Candidate Ballot-Polling Election Auditing Methods Huang, Zhuoqun Rivest, Ronald L Stark, Philip B. Teague, Vanessa J. Vukcevic, Damjan Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Counting votes is complex and error-prone. Several statistical methods have been developed to assess election accuracy by manually inspecting randomly selected physical ballots. Two ‘principled’ methods are risk-limiting audits (RLAs) and Bayesian audits (BAs). RLAs use frequentist statistical inference while BAs are based on Bayesian inference. Until recently, the two have been thought of as fundamentally different. We present results that unify and shed light upon ‘ballot-polling’ RLAs and BAs (which only require the ability to sample uniformly at random from all cast ballot cards) for two-candidate plurality contests, that are building blocks for auditing more complex social choice functions, including some preferential voting systems. We highlight the connections between the methods and explore their performance. First, building on a previous demonstration of the mathematical equivalence of classical and Bayesian approaches, we show that BAs, suitably calibrated, are risk-limiting. Second, we compare the efficiency of the methods across a wide range of contest sizes and margins, focusing on the distribution of sample sizes required to attain a given risk limit. Third, we outline several ways to improve performance and show how the mathematical equivalence explains the improvements. 2021-02-22T22:59:54Z 2021-02-22T22:59:54Z 2020-09 2021-02-04T16:58:16Z Book http://purl.org/eprint/type/ConferencePaper 9783030603465 9783030603472 0302-9743 1611-3349 https://hdl.handle.net/1721.1/129969 Huang, Zhuoqun et al. "A Unified Evaluation of Two-Candidate Ballot-Polling Election Auditing Methods." E-Vote-ID: International Joint Conference on Electronic Voting, Lecture Notes in Computer Science, 12455, Springer International Publishing, 2020, 112-128. © 2020 Springer Nature en http://dx.doi.org/10.1007/978-3-030-60347-2_8 Lecture Notes in Computer Science Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Springer International Publishing arXiv |
| spellingShingle | Huang, Zhuoqun Rivest, Ronald L Stark, Philip B. Teague, Vanessa J. Vukcevic, Damjan A Unified Evaluation of Two-Candidate Ballot-Polling Election Auditing Methods |
| title | A Unified Evaluation of Two-Candidate Ballot-Polling Election Auditing Methods |
| title_full | A Unified Evaluation of Two-Candidate Ballot-Polling Election Auditing Methods |
| title_fullStr | A Unified Evaluation of Two-Candidate Ballot-Polling Election Auditing Methods |
| title_full_unstemmed | A Unified Evaluation of Two-Candidate Ballot-Polling Election Auditing Methods |
| title_short | A Unified Evaluation of Two-Candidate Ballot-Polling Election Auditing Methods |
| title_sort | unified evaluation of two candidate ballot polling election auditing methods |
| url | https://hdl.handle.net/1721.1/129969 |
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