We introduce Flexible Representative Democracy (FRD), a novel hybrid of Representative Democracy and Direct Democracy in which voters can alter the issue-dependent weights of a set of elected representatives. In line with the literature on Interactive Democracy, our model allows the voters to actively determine the degree to which the system is direct versus representative. However, unlike Liquid Democracy, Flexible Representative Democracy uses strictly non-transitive delegations, making delegation cycles impossible, and maintains a fixed set of accountable, elected representatives. We present Flexible Representative Democracy and analyze it using a computational approach with issues that are binary and symmetric. We compare the outcomes of various voting systems using Direct Democracy with majority voting as an ideal baseline. First, we demonstrate the shortcomings of Representative Democracy in our model. We provide NP-Hardness results for electing an ideal set of representatives, discuss pathologies, and demonstrate empirically that common multi-winner election rules for selecting representatives do not perform well in expectation. To analyze the effects of adding delegation to representative voting systems, we begin by providing theoretical results on how issue-specific delegations determine outcomes. Finally, we provide empirical results comparing the outcomes of various voting systems: Representative Democracy, Proxy Voting, and FRD with issue-specific delegations. Our results show that variants of Proxy Voting yield no discernible benefit over unweighted representatives and reveal the potential for Flexible Representative Democracy to improve outcomes as voter participation increases.
Pandering in a (flexible) representative democracy
In representative democracies, regular election cycles are supposed to prevent misbehavior by elected officials, hold them accountable, and subject them to the “will of the people." Pandering, or dishonest preference reporting by candidates campaigning for election, undermines this democratic idea. Much of the work on Computational Social Choice to date has investigated strategic actions in only a single election. We introduce a novel formal model of pandering and examine the resilience of two voting systems, Representative Democracy (RD) and Flexible Representative Democracy (FRD), to pandering within a single election and across multiple rounds of elections. For both voting systems, our analysis centers on the types of strategies candidates employ and how voters update their views of candidates based on how the candidates have pandered in the past. We provide theoretical results on the complexity of pandering in our setting for a single election, formulate our problem for multiple cycles as a Markov Decision Process, and use reinforcement learning to study the effects of pandering by single candidates and groups of candidates over many rounds.
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- Award ID(s):
- 2007955
- NSF-PAR ID:
- 10480841
- Publisher / Repository:
- Proceedings of Machine Learning Research
- Date Published:
- Journal Name:
- Proceedings of the 39th Conference on Uncertainty in Artificial Intelligence
- Format(s):
- Medium: X
- Location:
- Pittsburgh, PA, USA
- Sponsoring Org:
- National Science Foundation
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Oh, A ; Naumann, T ; Globerson, A ; Saenko, K ; Hardt, M ; Levine, S (Ed.)Liquid democracy with ranked delegations is a novel voting scheme that unites the practicability of representative democracy with the idealistic appeal of direct democracy: Every voter decides between casting their vote on a question at hand or delegating their voting weight to some other, trusted agent. Delegations are transitive, and since voters may end up in a delegation cycle, they are encouraged to indicate not only a single delegate, but a set of potential delegates and a ranking among them. Based on the delegation preferences of all voters, a delegation rule selects one representative per voter. Previous work has revealed a trade-off between two properties of delegation rules called anonymity and copy-robustness. To overcome this issue we study two fractional delegation rules: Mixed Borda branching, which generalizes a rule satisfying copy-robustness, and the random walk rule, which satisfies anonymity. Using the Markov chain tree theorem, we show that the two rules are in fact equivalent, and simultaneously satisfy generalized versions of the two properties. Combining the same theorem with Fulkerson's algorithm, we develop a polynomial-time algorithm for computing the outcome of the studied delegation rule. This algorithm is of independent interest, having applications in semi-supervised learning and graph theory.more » « less
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Abstract Two of the most significant concerns about the contemporary United States are the erosion of democratic institutions and the high rate of depression. We provide evidence connecting these phenomena. We use a survey (N = 11,517) to show a relationship between misperceptions (about COVID-19 vaccines) and voting, in 2022, for gubernatorial candidates who denied or cast doubt on the legitimacy of the 2020 election results. We further predict and find that the presence of moderately severe-to-severe depressive symptoms exacerbates the relationship between misperceptions and voting for election deniers or doubters. The results offer insight into the links between misperceptions, depression, and democratic backsliding (i.e., supporting candidates who challenge election results). We also contribute to a growing line of research on how mental health affects democratic functioning, potentially worldwide.
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