Digital dilemmas: The unintended consequences of election technology
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Digital technologies are increasingly used in elections around the world. Where the resources and capacity of the state are limited, some have argued that such technologies make it possible to rapidly “leapfrog” to cleaner and more credible elections. This article argues that the growing use of these technologies has been driven by the fetishization of technology rather than by rigorous assessment of their effectiveness; that they may create significant opportunities for corruption that (among other things) vitiate their potential impact; and that they carry significant opportunity costs. Indeed, precisely because new technology tends to deflect attention away from more “traditional” strategies, the failure of digital checks and balances often renders an electoral process even more vulnerable to rigging than it was before. These observations are not intended as a manifesto against the digitization of elections; apart from anything else, we argue that the drivers of the adoption of these new methods are too powerful to resist. But the analysis draws attention to the importance of more careful assessments of the problems, as well as the benefits, of such technologies – and to the need for more careful planning in their deployment.
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The greatest gains from digitization come in countries where the quality of democracy is higher and the electoral commission more independent.
“We can extend to identification systems generally t he conclusion that 'the greatest gains from digitization come in countries where the quality of democracy is higher and the electoral commission more independent' (Cheeseman et al., 2018, p. 3; see also Piccolino, 2016).”
From The Sustainable Development Goals and 'legal identity for all': 'First, do no harm' (2021) · cites this paper as Cheeseman et al., 2018
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- Authors
- Cheeseman, N., Lynch, G., & Willis, J.
- Affiliations
- University of Birmingham (GB)
- University of Warwick (GB)
- Durham University (GB)
- Corresponding author
- Cheeseman, Nic
- Venue
- Democratization
- Publisher
- Informa UK Limited
- Published
- 2018-06-08
- Volume
- 25
- Issue
- 8
- Pages
- 1397-1418
- ISSN
- 1351-0347 (ISSN-L)
- 1743-890X
- OpenAlex
- W2799844154
- Cited by
- 140
- References
- 40
- Citations by year
- 2026: 6 · 2025: 17 · 2024: 31 · 2023: 12 · 2022: 16 · 2021: 30 · 2020: 17 · 2019: 8 · 2018: 3
- FWCI
- 63.10
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Democratization (publishedVersion, cc-by)
- Durham Research Online (Durham University) (acceptedVersion, other-oa)
- Durham Research Online (Durham University) (submittedVersion, cc-by)
- Warwick Research Archive Portal (University of Warwick) (submittedVersion)
- Funders
- Economic and Social Research Council (ES/L002108/1, ES/L002345/1)
- Topics
- Social Sciences › Political Science and International Relations › Electoral Systems and Political Participation
- Social Sciences › Political Science and International Relations › E-Government and Public Services
- Physical Sciences › Computer Science › Artificial Intelligence › Internet Traffic Analysis and Secure E-voting
- Keywords
- electoral technology, digitalization of elections, electoral integrity, election rigging, corruption, leapfrogging, technology fetishism, checks and balances, electoral process, opportunity cost
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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