Taxonomy / Deliberative aggregation / Putting the model in the facilitator's seat

Putting the model in the facilitator's seat

A model takes over jobs a human facilitator, chair or annotator would do around a group's disagreement. It drafts a candidate group statement from everyone's opinions and critiques and redrafts it as participants rank the versions, picks slates of statements that represent the whole spread of opinion under formal fairness guarantees, chairs a live session by managing the speaking queue and intervening on incivility, voices stakeholders who are not in the room, and rates each contribution for justification, novelty and openness in place of the human coders who used to. Some of this runs live inside a session and some works offline from a collected set of opinions; what the family shares is that the model occupies a role in the deliberation rather than consuming its output afterward.

The method, against Deliberative aggregation

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Concept Analysis: Theoretical Foundations

Each concept is read twice: whether the approach carries it, and whether the approach's own sources claim it. A concept that is absent and was never claimed is a gap in the field rather than a failure of the work, and is marked out of scope.

Deliberation, Not Tallying

PartialClaimed · partial

Definition · Jürgen Habermas, Between Facts and Norms (1992)

This concept locates legitimacy in the exchange of reasons among equals: participants justify their views to each other, free of coercion, and remain able to change their minds. Counting votes or averaging preferences does not produce it, because the reasoning is what does the work.

Analysis

One mechanism in the family genuinely exchanges reasons: in the Habermas machine participants file critiques of a draft and the model rewrites in light of them, and participants demonstrably moved position, which no tally can produce; the Stanford moderator adds the speech conditions Habermas cares about, allocating speaking time and intervening on incivility. But every member settles the matter by counting rather than by the better argument — the winning statement is fixed by a preference ranking, the veto-core and token-level-MDP papers work entirely from per-participant preference models so no participant reasons with anyone, and the two quality graders score contributions one at a time, so a discussion in which one party dominates and nobody is moved can score well throughout. Reasons enter as inputs to an aggregation rather than as what does the work.

General Will vs. Sum of Preferences

PartialClaimed · partial

Definition · Jean-Jacques Rousseau, The Social Contract (1762)

This distinction separates what is good for a public in common from the sum of what its members privately want. Aggregating private wants, however fairly, does not produce the former, since the two can and often do diverge.

Analysis

What is carried is the form of the output: most of these systems emit a single statement written in the group's voice rather than a numeric average, and Tessler et al. show the winning statements incorporate dissenting views instead of tracking the majority, which is the divergence Rousseau points at. What is not carried is the distinction itself — every rule that picks the statement is a function of what members privately want (social welfare functions in Bakker, the proportional veto core, per-participant token rewards, proportional slates), and the Overton benchmark literally scores how much of the spread of private views one answer covers. In Bakker the choice between summing the group and protecting its worst-off is a dial the researchers turn, so the one place the question arises it is settled off-stage rather than by the public whose common good is at issue.

Veil of Ignorance

AbsentNot claimed · out of scope

Definition · John Rawls, A Theory of Justice (1971)

This device requires that rules be chosen without knowledge of which position the chooser will occupy under them, e.g., rich or poor, majority or minority. Not knowing generally pushes the chooser to protect the worst-off position, since it may turn out to be their own.

Analysis

Nothing anywhere in the family screens a chooser from their own position: participants opine and critique as themselves, the citizens'-assembly replication matches demographics precisely so that known positions are present, annotators rate from their own standpoint, and the Empty Chair supplies absent perspectives by naming and voicing them rather than by veiling anyone. The maximin outcome the veil is meant to generate does surface — Bakker selects statements under egalitarian as well as utilitarian welfare functions, and the proportional veto core shields minorities from being overruled — but it arrives as a researcher's choice of objective, which is the conclusion without the device. No source engages the veil; using Rawlsian vocabulary for a welfare function imports the outcome principle, not the construction procedure.

Reasonable Rejection

PartialClaimed · partial

Definition · T. M. Scanlon, What We Owe to Each Other (1998)

This test holds a principle justified only if no individual could reasonably reject it, and it is applied person by person rather than in aggregate. One sufficiently strong objection therefore outweighs many mild preferences, which is the case averaging handles wrongly.

Analysis

Rejection power exists here in quantitative form: the proportional veto core lets a coalition block any statement in proportion to its size, generative social choice guarantees a cohesive group of sufficient size a statement of its own, and in the mediation loop a critique must be answered in the next draft or the statement loses ground. Both halves of Scanlon's test are missing, though — it is applied person by person and is indifferent to how many share the objection, and it turns on the grounds offered rather than on strength of feeling. In these systems an objection is registered as a preference score or a rating, so a reasoned rejection and a mild dislike are the same datum and many mild approvals outweigh one strong objection; Bakker's own exclusion experiment makes the failure concrete, with a statement assembled from a subset still standing over the member left out.

Concept Analysis: Newly Introduced

Dissent kept inside the winning statement

Added

Deliberative theory asks that the outcome be one everybody could accept; it does not say the outcome should contain the objections. The embedding analysis here finds that the statements which succeed are the ones that incorporate dissenting voices while respecting the majority — a property of the artifact rather than of the procedure, and one the tradition has no name for.

A computable measure of deliberative quality

Added

Habermas supplies a standard for deliberation and no way of telling whether a given discussion met it, because his participants were assumed present to one another. These instruments make the standard computable for every post: AQuA runs adapter models for 20 deliberative indices and produces a score from pre-trained adapters alone, and the Stanford model rates on four criteria at a scale the paper says human annotation cannot reach, being time-consuming and costly. Whether the number measures what the standard asks for is a separate question, but the tradition offers no number at all.

Papers

Generative Social Choice

Sara Fish et al., Sep 2023

arXiv:2309.01291MethodPartial

AI can help humans find common ground in democratic deliberation

Michael Henry Tessler et al., Oct 2024

doi:10.1126/science.adq2852172 citationsMethodBuilt

Trains an AI mediator that takes a group's individual opinions and critiques, writes a candidate group statement, and refines it round after round; participants (N=5,734) preferred its statements to those of human mediators and moved toward a shared position, and the result replicated in a demographically representative UK citizens' assembly.

Finding Common Ground in a Sea of Alternatives

Jay Chooi et al., Mar 2026

arXiv:2603.16751MethodBuilt

Gives a formal account of finding common ground when the candidate statements are effectively infinite, based on the proportional veto core, and supplies a sampling algorithm that returns an alternative in the approximate core with high probability, with matching lower bounds.

Generating Fair Consensus Statements with Social Choice on Token-Level MDPs

Carter Blair & Kate Larson, Oct 2025

arXiv:2510.14106MethodBuilt

Models consensus-statement generation as a token-level Markov decision process with one objective per participant, deriving each participant's token rewards from their own personalized model, so fairness guarantees attach to the generation itself.

Generative Social Choice: The Next Generation

Niclas Boehmer et al., May 2025

arXiv:2505.22939MethodBuilt

Extends generative social choice to produce a slate of statements that proportionally represents the whole spectrum of opinion, with theoretical guarantees that hold under the queries an LLM can actually answer.

Fine-tuning language models to find agreement among humans with diverse preferences

Michiel A. Bakker et al., Nov 2022

arXiv:2211.15006MethodBuilt

Fine-tunes a 70-billion-parameter model to write statements that maximize a group's expected approval and ranks the candidates with a reward model trained to predict individual preferences, with the group's appeal defined according to different social welfare functions; its statements were preferred to those of prompted models more than 70% of the time and to the best human-written opinions more than 65%, and when a consensus was built silently from only a subset of the group the excluded members were more likely to dissent.