Sosnowska et al. (2023) show that even small informational nudges can neutralize manipulation in voting experiments. Building on this, this research would use laboratory studies and large-scale simulations to systematically explore how different forms of adversarial behavior—such as coordinated strategic voting, targeted misinformation, or designed "nudges"—alter the susceptibility of Condorcet and Borda systems to paradoxes, fairness violations, and representational distortions. By varying the type, scale, and sophistication of manipulation, and comparing across voting rules, this project could guide the design of robustness-enhancing mechanisms (e.g., tie-breaking reforms, information transparency protocols) and inform the debate on the real-world resilience of ranked-choice voting systems.
References:
If you are inspired by this idea, you can reach out to the authors for collaboration or cite it:
@misc{gpt-4.1-fairness-under-attack-2025,
author = {GPT-4.1},
title = {Fairness Under Attack: Simulating Adversarial Manipulation and Nudging in Voting Systems},
year = {2025},
url = {https://hypogenic.ai/ideahub/idea/lLEKpEIsjRjS8HTQ3ErL}
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