arXiv subjects

Michelle Blom

Publications and source records attributed to Michelle Blom.

27 records · Page 2Linked to original sources

arXiv2021

Auditing Hamiltonian Elections

Presidential primaries are a critical part of the United States Presidential electoral process, since they are used to select the candidates in the Presidential election. While methods differ by state and party, many primaries involve proportional delegate allocation using the so-called Hamilton method. In this paper we show how to conduct risk-limiting audits for delegate allocation elections using variants of the Hamilton method where the viability of candidates is determined either by a plurality vote or using instant runoff voting. Experiments on real-world elections show that we can audit primary elections to high confidence (small risk limits) usually at low cost.

cs.CY↗

arXiv2020

Random errors are not necessarily politically neutral

Errors are inevitable in the implementation of any complex process. Here we examine the effect of random errors on Single Transferable Vote (STV) elections, a common approach to deciding multi-seat elections. It is usually expected that random errors should have nearly equal effects on all candidates, and thus be fair. We find to the contrary that random errors can introduce systematic bias into election results. This is because, even if the errors are random, votes for different candidates occur in different patterns that are affected differently by random errors. In the STV context, the most important effect of random errors is to invalidate the ballot. This removes far more votes for those candidates whose supporters tend to list a lot of preferences, because their ballots are much more likely to be invalidated by random error. Different validity rules for different voting styles mean that errors are much more likely to penalise some types of votes than others. For close elections this systematic bias can change the result of the election.

cs.CY↗

arXiv2020

You can do RLAs for IRV

The City and County of San Francisco, CA, has used Instant Runoff Voting (IRV) for some elections since 2004. This report describes the first ever process pilot of Risk Limiting Audits for IRV, for the San Francisco District Attorney's race in November, 2019. We found that the vote-by-mail outcome could be efficiently audited to well under the 0.05 risk limit given a sample of only 200 ballots. All the software we developed for the pilot is open source.

cs.CY↗

arXiv2019

RAIRE: Risk-Limiting Audits for IRV Elections

Risk-limiting post election audits guarantee a high probability of correcting incorrect election results, independent of why the result was incorrect. Ballot-polling audits select ballots at random and interpret those ballots as evidence for and against the reported result, continuing this process until either they support the recorded result, or they fall back to a full manual recount. For elections with digitised scanning and counting of ballots, a comparison audit compares randomly selected digital ballots with their paper versions. Discrepancies are referred to as errors, and are used to build evidence against or in support of the recorded result. Risk-limiting audits for first-past-the-post elections are well understood, and used in some US elections. We define a number of approaches to ballot-polling and comparison risk-limiting audits for Instant Runoff Voting (IRV) elections. We show that for almost all real elections we found, we can perform a risk-limiting audit by looking at only a small fraction of the total ballots (assuming no errors were made in the tallying and distribution of votes).

cs.DS↗

arXiv2017

Towards Computing Victory Margins in STV Elections

The Single Transferable Vote (STV) is a system of preferential voting employed in multi-seat elections. Each vote cast by a voter is a (potentially partial) ranking over a set of candidates. No techniques currently exist for computing the margin of victory (MOV) in STV elections. The MOV is the smallest number of vote manipulations (changes, additions, and deletions) required to bring about a change in the set of elected candidates. Knowledge of the MOV of an election gives greater insight into both how much time and money should be spent on the auditing of the election, and whether uncovered mistakes (such as ballot box losses) throw the election result into doubt---requiring a costly repeat election---or can be safely ignored. In this paper, we present algorithms for computing lower and upper bounds on the MOV in STV elections. In small instances, these algorithms are able to compute exact margins.

cs.GT↗

arXiv2017

Computing the Margin of Victory in Preferential Parliamentary Elections

We show how to use automated computation of election margins to assess the number of votes that would need to change in order to alter a parliamentary outcome for single-member preferential electorates. In the context of increasing automation of Australian electoral processes, and accusations of deliberate interference in elections in Europe and the USA, this work forms the basis of a rigorous statistical audit of the parliamentary election outcome. Our example is the New South Wales Legislative Council election of 2015, but the same process could be used for any similar parliament for which data was available, such as the Australian House of Representatives given the proposed automatic scanning of ballots.

cs.DS↗

arXiv2016

An analysis of New South Wales electronic vote counting

We re-examine the 2012 local government elections in New South Wales, Australia. The count was conducted electronically using a randomised form of the Single Transferable Vote (STV). It was already well known that randomness does make a difference to outcomes in some seats. We describe how the process could be amended to include a demonstration that the randomness was chosen fairly. Second, and more significantly, we found an error in the official counting software, which caused a mistake in the count in the council of Griffith, where candidate Rina Mercuri narrowly missed out on a seat. We believe the software error incorrectly decreased Mercuri's winning probability to about 10%---according to our count she should have won with 91% probability. The NSW Electoral Commission (NSWEC) corrected their code when we pointed out the error, and made their own announcement. We have since investigated the 2016 local government election (held after correcting the error above) and found two new errors. We notified the NSWEC about these errors a few days after they posted the results.

cs.CR↗

arXiv2016

Auditing Australian Senate Ballots

We explain why the Australian Electoral Commission should perform an audit of the paper Senate ballots against the published preference data files. We suggest four different post-election audit methods appropriate for Australian Senate elections. We have developed prototype code for all of them and tested it on preference data from the 2016 election.

cs.CR↗

arXiv2015

Efficient Computation of Exact IRV Margins

The margin of victory is easy to compute for many election schemes but difficult for Instant Runoff Voting (IRV). This is important because arguments about the correctness of an election outcome usually rely on the size of the electoral margin. For example, risk-limiting audits require a knowledge of the margin of victory in order to determine how much auditing is necessary. This paper presents a practical branch-and-bound algorithm for exact IRV margin computation that substantially improves on the current best-known approach. Although exponential in the worst case, our algorithm runs efficiently in practice on all the real examples we could find. We can efficiently discover exact margins on election instances that cannot be solved by the current state-of-the-art.

cs.AI↗