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Random Errors Are Not Necessarily Politically Neutral

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Electronic Voting (E-Vote-ID 2020)

Abstract

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.

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Notes

  1. 1.

    https://www.aec.gov.au/Voting/counting/files/css-integrity.pdf.

  2. 2.

    https://www.aec.gov.au/Voting/counting/files/senate-count.pdf.

  3. 3.

    See the downloads section for each election at: https://vote.andrewconway.org.

  4. 4.

    https://github.com/SiliconEconometrics/PublicService.

  5. 5.

    https://www.anao.gov.au/work/performance-audit/aec-procurement-services-conduct-2016-federal-election.

  6. 6.

    For example, https://www.aec.gov.au/Voting/Informal_Voting/senate/.

  7. 7.

    There is unpublished work claiming 0.17%.

References

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  2. Richey, S.: Random and systematic error in voting in presidential elections. Polit. Res. Q. 66(3), 645–657 (2013). http://www.jstor.org/stable/23563171

  3. Toghi, B., Grover, D.: MNIST dataset classification utilizing k-NN classifier with modified sliding window metric. CoRR abs/1809.06846 (2018). http://arxiv.org/abs/1809.06846

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Acknowledgements

We would like to thank our colleagues who participated in our informal experiment during the 2019 Australian federal election. Thanks also to Philip Stark for very valuable suggestions on improving the paper.

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Correspondence to Vanessa J. Teague .

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Blom, M., Conway, A., Stuckey, P.J., Teague, V.J., Vukcevic, D. (2020). Random Errors Are Not Necessarily Politically Neutral. In: Krimmer, R., et al. Electronic Voting. E-Vote-ID 2020. Lecture Notes in Computer Science(), vol 12455. Springer, Cham. https://doi.org/10.1007/978-3-030-60347-2_2

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  • DOI: https://doi.org/10.1007/978-3-030-60347-2_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-60346-5

  • Online ISBN: 978-3-030-60347-2

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