Michelle Blom

Michelle Blom, Alexander Ek, Peter J. Stuckey et al.

Constructing efficient risk-limiting audits (RLAs) for multiwinner single transferable vote (STV) elections is a challenging problem. An STV RLA is designed to statistically verify that the reported winners of an election did indeed win according to the voters' expressed preferences and not due to mistabulation or interference, while limiting the risk of accepting an incorrect outcome to a desired threshold (the risk limit). Existing methods have shown that it is possible to form RLAs for two-seat STV elections in the context where the first seat has been awarded to a candidate in the first round of tabulation. This is called the first winner criterion. We present an assertion-based approach to conducting full or partial RLAs for STV elections with three or more seats, in which the first winner criterion is satisfied. Although the chance of forming a full audit that verifies all winners drops substantially as the number of seats increases, we show that we can quite often form partial audits that verify most, and sometimes all, of the reported winners. We evaluate our method on a dataset of over 500 three- and four-seat STV elections from the 2017 and 2022 local council elections in Scotland.

Alexander Ek, Michelle Blom, Philip B. Stark et al.

One approach to risk-limiting audits (RLAs) compares randomly selected cast vote records (CVRs) to votes read by human auditors from the corresponding ballot cards. Historically, such methods reduce audit sample sizes by considering how each sampled CVR differs from the corresponding true vote, not merely whether they differ. Here we investigate the latter approach, auditing by testing whether the total number of mismatches in the full set of CVRs exceeds the minimum number of CVR errors required for the reported outcome to be wrong (the "CVR margin"). This strategy makes it possible to audit more social choice functions and simplifies RLAs conceptually, which makes it easier to explain than some other RLA approaches. The cost is larger sample sizes. "Mismatch-based RLAs" only require a lower bound on the CVR margin, which for some social choice functions is easier to calculate than the effect of particular errors. When the population rate of mismatches is low and the lower bound on the CVR margin is close to the true CVR margin, the increase in sample size is small. However, the increase may be very large when errors include errors that, if corrected, would widen the CVR margin rather than narrow it; errors affect the margin between candidates other than the reported winner with the fewest votes and the reported loser with the most votes; or errors that affect different margins.

Michelle Blom, Andrew Conway, Dan King et al.

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.

Archana Vadakattu, Michelle Blom, Adrian R. Pearce

The ability to continuously learn and adapt to new situations is one where humans are far superior compared to AI agents. We propose an approach to knowledge transfer using behavioural strategies as a form of transferable knowledge influenced by the human cognitive ability to develop strategies. A strategy is defined as a partial sequence of events - where an event is both the result of an agent's action and changes in state - to reach some predefined event of interest. This information acts as guidance or a partial solution that an agent can generalise and use to make predictions about how to handle unknown observed phenomena. As a first step toward this goal, we develop a method for extracting strategies from an agent's existing knowledge that can be applied in multiple contexts. Our method combines observed event frequency information with local sequence alignment techniques to find patterns of significance that form a strategy. We show that our method can identify plausible strategies in three environments: Pacman, Bank Heist and a dungeon-crawling video game. Our evaluation serves as a promising first step toward extracting knowledge for generalisation and, ultimately, transfer learning.

Michelle Blom, Peter J. Stuckey, Vanessa Teague et al.

Risk-limiting audits (RLAs) are an increasingly important method for checking that the reported outcome of an election is, in fact, correct. Indeed, their use is increasingly being legislated. While effective methods for RLAs have been developed for many forms of election -- for example: first-past-the-post, instant-runoff voting, and D'Hondt elections -- auditing methods for single transferable vote (STV) elections have yet to be developed. STV elections are notoriously hard to reason about since there is a complex interaction of votes that change their value throughout the process. In this paper we present the first approach to risk-limiting audits for STV elections, restricted to the case of 2-seat STV elections.

Michelle Blom, Jurlind Budurushi, Ronald L. Rivest et al.

Risk-limiting audits (RLAs), an ingredient in evidence-based elections, are increasingly common. They are a rigorous statistical means of ensuring that electoral results are correct, usually without having to perform an expensive full recount -- at the cost of some controlled probability of error. A recently developed approach for conducting RLAs, SHANGRLA, provides a flexible framework that can encompass a wide variety of social choice functions and audit strategies. Its flexibility comes from reducing sufficient conditions for outcomes to be correct to canonical `assertions' that have a simple mathematical form. Assertions have been developed for auditing various social choice functions including plurality, multi-winner plurality, super-majority, Hamiltonian methods, and instant runoff voting. However, there is no systematic approach to building assertions. Here, we show that assertions with linear dependence on transformations of the votes can easily be transformed to canonical form for SHANGRLA. We illustrate the approach by constructing assertions for party-list elections such as Hamiltonian free list elections and elections using the D'Hondt method, expanding the set of social choice functions to which SHANGRLA applies directly.

Michelle Blom, Philip B. Stark, Peter J. Stuckey et al.

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.

Andrew Conway, Michelle Blom, Lee Naish et al.

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.

Berj Chilingirian, Zara Perumal, Ronald L. Rivest et al.

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.

Michelle Blom, Peter J. Stuckey, Vanessa J. Teague et al.

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.