AI could help cut voter fraud – but it’s far more likely to disenfranchise you
By Dr Deepak Padmanabhan, Prof Muiris MacCarthaigh and Stanley Simoes. Article originally appeared in The Conversation.
Imagine the year is 2029. You have been living at the same address for a decade. The postman, who knows you well, smiles as he walks to your door and hands you a bunch of letters. As you sift through them, one card grabs your attention. It says: “Let us know if you are still here.”
It’s an election year and the card from the electoral office is asking you to confirm you are still a resident at the same address. It has a deadline, and you may be purged from the voter list if you don’t respond to it.
You had read about the government using AI to detect and eliminate electoral fraud through selective querying. Is it the AI pointing fingers at you? A quick check reveals your neighbours haven’t received any such cards. You feel singled out and insecure. Why have you been asked to prove that you live where you’ve lived for so long?
Let’s look under the hood. You received the card because election officials had deployed an AI system that can triangulate evidence to estimate why some voters should be contacted to check whether they are still a resident at their address. It profiles voters based on whether they display the behaviour of a “typical” resident.
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Article originally appeared in The Conversation.
About the Authors
Dr Deepak Padmanabhan is a Senior Lecturer in the School of Electronics, Electrical Engineering and Computer Science and the Institute of Electronics, Communications & Information Technology at Queen’s University Belfast, Deepak specializes in AI ethics, with a particular interest in the political economy of AI.
Prof Muiris MacCarthaigh is Professor of Politics and Public Policy and Head of Politics and International Relations at Queen’s University Belfast. His research engages with a variety of debates within and between political science, public sector governance and public policy.
Stanley Simoes is a Marie Skłodowska-Curie Early Stage Researcher and PhD student at the School of Electronics, Electrical Engineering, and Computer Science at Queen’s University Belfast. His research interests currently lie in the field of fair AI, particularly in unsupervised learning.
The featured image has been used courtesy of a Creative Commons license.
