Flexible Representative Democracy: an Introduction with Binary Issues

Flexible Representative Democracy: an Introduction with Binary Issues

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence (IJCAI-19) Flexible Representative Democracy: An Introduction with Binary Issues Ben Abramowitz1 and Nicholas Mattei2 1Rensselaer Polytechnic Institute, Troy, NY, USA 2Tulane University, New Orleans, LA, USA [email protected], [email protected] Abstract been used in many contexts and disciplines to reduce the computation and communication burden of decision makers. We introduce Flexible Representative Democracy The Computational Social Choice (COMSOC) community (FRD), a novel hybrid of Representative Democ- [Brandt et al., 2016] has produced a large body of research racy (RD) and Direct Democracy (DD), in which on how to select and weight representatives. Indeed, using voters can alter the issue-dependent weights of a multi-winner voting [Skowron et al., 2016], we can view the set of elected representatives. In line with the liter- winners as a set of exemplars that may be used to decide some ature on Interactive Democracy, our model allows downstream application.Often it is beneficial to elect fixed the voters to actively determine the degree to which committees which meet certain axiomatic criteria. For exam- the system is direct versus representative. How- ple, committees should be proportional and have justified rep- ever, unlike Liquid Democracy, FRD uses strictly resentation of the voters [Aziz et al., 2017]. Intuitively, these non-transitive delegations, making delegation cy- difficulties in electing committees carry through to the set- cles impossible, preserving privacy and anonymity, ting of Representative Democracy (RD) where the commit- and maintaining a fixed set of accountable elected tee makes decisions in the interest of the voters/agents who representatives. We present FRD and analyze it us- elect them. This setting was studied by Skowron [2015] who ing a computational approach with issues that are proved that when we want to optimize for the sum of voters independent, binary, and symmetric; we compare who are represented on each issue the k-Median rule optimal. the outcomes of various democratic systems us- Since DD can be impractical and RD comes with inher- ing Direct Democracy with majority voting and full ent tradeoffs and limitations, hybridizations of the two have participation as an ideal baseline. We find through arisen under the umbrella of Interactive Democracy. Coupled theoretical and empirical analysis that FRD can with modern communication technologies, a large number of yield significant improvements over RD for emu- proposed democratic decision making systems have been pro- lating DD with full participation. posed, and Interactive Democracy has become an important area of research and application for AI [Brill, 2018]. Perhaps 1 Introduction the most popular version of this today is Liquid Democracy Since the Athenian Ecclesia in 595 BCE Direct Democ- (LD); which has received significant attention in the political [ ] [ et al. ] racy (DD) as an ideal collective decision making scheme has science Green-Armytage, 2015 , AI Kahng , 2018 and [ ] loomed large in the western imagination [Dunn, 1995]. While agents communities Brill and Talmon, 2018 , and has been [ ] DD may be desirable it becomes impractical at scale as it implemented in both corporate Hardt and Lopes, 2015 and [ ] places too much burden on individual decisions makers: ev- political settings Blum and Zuber, 2016 . Flexible eryone must be well-informed on every issue and available to In contrast to existing proposals, our model of Representative Democracy (FRD) vote [Green-Armytage, 2015]. In addition to the attention re- maintains a set of expert quirements, voters are also required to know and be able to ar- representatives while allowing voters to guarantee their own ticulate their preferences at the time of every vote. While pref- representation without raising the voters’ minimum required erences and preference learning are large research areas in burden. In an FRD voters elect a set of representatives to AI [Domshlak et al., 2011] every voter may not have enough serve a term during which they decide the outcomes over a knowledge, information, time, energy, or incentive to partici- set of issues. Each voter, by default, allocates a fraction of pate, particularly when issues are numerous or complex. their voting power to each member of the committee. If this Given the prohibitive costs of implementing a large-scale allocation is uniform and we stop here, we are left with the DD in both human and agent societies, we often resort to rep- traditional model of RD where each representative has equal resentation, relying upon a set of proxies to decide on the power. However, for each issue under consideration in FRD, voters’ behalf. Countries have parliaments, companies have the voters may deviate from this default by delegating their elected boards, and groups of agents select leaders to rep- voting power to any subset of the committee. If all voters use resent them [Yu et al., 2010]. Sets of representatives have their option to delegate on each issue, as long as there is at 3 Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence (IJCAI-19) least one representative who agrees with each voter’s view, In FRD, as with RD, the voters elect a set of representa- the outcome perfectly recovers DD. Voters have both the elec- tives RE (PVC) ! D ⊆ C. However, for every issue, a divis- tion and the flexible delegation option as tools for achieving ible unit of voting power is given to each voter rather than to representation and holding representatives accountable. each representative. Automatically after the election, the vot- In an FRD, voters have great flexibility in determining how ers’ issue-specific votes are distributed among the representa- they are represented and the mandated disclosure of represen- tives according to some default distribution mechanism. Sub- tatives’ votes guarantees that an attentive voter can be fully sequently, every voter has the option to alter how their voting informed about how their voting power will be and was used. power is assigned to the representatives and may change this For example, the day after the election an inattentive voter for any subset issues at once or on an issue-by-issue basis. We might choose a few elected representatives they trust, appor- refer to this process of deviating from the default and actively tion the power of their vote to these few for all future issues allocating voting power to representatives as delegation. Del- and pay no attention until the next election. A more attentive egations are not permanent and may be altered before an issue i voter might alter their allocations on an issue-by-issue basis is decided. We let Wjl represent the voting power allocated i as issues arise, reacting to representatives’ votes. In general, by voter vj 2 V to candidate cl 2 C on issue s 2 S, yield- voters determine the granularity with which they privately ex- ing a collective matrix of weights W . In FRD, a decision rule press their preferences over issues via the representatives. In RS is then applied to the representatives’ preferences taking addition, in an FRD voters may or may not be permitted to these weights into account RS (W; PDS ) !OF RD. If voters vote directly on the issues, depending upon the application. have the option to vote directly on issues rather than having Contributions. We introduce Flexible Representative their voting power only distributed to representatives (e.g., Democracy (FRD), a new model of Interactive Democracy more similar to LD), W and PDS can be augmented to allow which transitions, at the discretion of the voters, between voters to “delegate” to themselves. RD and DD. FRD solves standing issues in the literature on Interactive Democracy including maintaining a fixed, 2.1 Model Specification elected committee to generate legislation, making delegation We restrict our attention to a simple type of FRD. Our ob- cycles impossible, and preserving voter anonymity. We jective is to compare the extent to which RD and FRD can analyze our model theoretically using independent, binary, emulate DD, which we hold as “optimal.” We consider a set- symmetric issues. We show that electing an optimal set of ting with symmetric, binary issues so each issue si 2 S has representatives is hard for any large-scale RD no matter the two possible outcomes Oi 2 f0; 1g, and there are 2r possi- voting rule, thus motivating the use of flexible delegations. ble outcome vectors over jSj = r of the form O 2 f0; 1gr. Thus, we demonstrate the theoretical ability of delegations We assume all issues are independent, this is a simplifying under FRD to overcome the limitations of RD, providing assumption that circumvents issues raised in judgment aggre- empirical results demonstrating that FRD outperforms both gation [List and Puppe, 2009], though an important direction RD and Proxy Voting for representing the majority will. for future work. Without loss of generality, we label each of the alternatives preferred by the (weak) majority of voters 1 2 Model and Preliminaries and the other 0, breaking ties randomly (when N is even). r We primarily consider three democratic decision systems: Di- Thus, the ideal majoritarian outcome over the issues is f1g . Each voter in the set of voters V = fv1; : : : ; vN g has a rect Democracy (DD), Representative Democracy (RD), and i i our model: Flexible Representative Democracy (FRD). Given preferred alternative vj 2 f0; 1g for every issue s in the set 1 r 1 r a set of voters V with preferences over the alternatives for of issues S = fs ; : : : ; s g. We let vector ~vj = fvj ; : : : ; vj g each issue in a set of issues S, we represent their collective represent the preferred outcome of voter vj over the issues, preferences by a preference profile PVS . In DD, a decision resulting in the collective profile PVS = f~vj : vj 2 Vg.

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