AI Deliberator
Guides
How to use AI DeliberatorView all 58 guides

Getting started

Evaluate and export a Council runHow to ask a better decision questionHow to choose models for an AI councilRun your first AI councilUse the Consideration MapContinue a decision with follow-up questionsEstimate and control LLM costs

Everyday decisions

Use an AI council for a career changeEvaluate a leadership role or promotionThink through a relationship decisionDecide whether to move to a new cityCompare degrees, certificates, and education optionsAnalyze a major purchaseUse live evidence mode

Work and teams

Use deliberation for a business strategy decisionSupport a hiring decision responsiblyPrioritize a product roadmapRun a decision pre-mortemMap a stakeholder disagreementAnalyze a policy proposal

Research design

Duplicate and pilot an experimentDesign an LLM deliberation experimentDefine outcomes and dependent variablesConfigure experimental conditions and independent variablesCompare deliberation with homogeneous reconsiderationBuild an independent model ensembleUse randomization, replications, and compute matching

Participant studies

Build a participant interaction studyDesign pre- and post-interaction questionnairesChoose Likert, slider, and questionnaire formatsAdd attention, manipulation, and exposure checksAnalyze and export participant-study resultsBuild a composable experiment timelineMeasure human–AI advice relianceAdd process tracing and cognitive tasksRun a human deliberation conditionBuild a human–AI hybrid deliberation chainRun a text, image, or video stimulus experimentRun a learning and tutoring experimentPlan a powered participant studyMonitor recruitment, cost, and attrition

Behavioral games

Design a behavioral economics gameRun a Dictator GameRun an Ultimatum GameRun a Trust or Investment GameRun a Prisoner’s DilemmaRun a Public Goods GameRun a Stag Hunt GameConfigure game payoffs, incentives, and feedbackManage private game links, consent, and completion

Benchmarks and results

Select benchmark questions and subsetsRun MMLU-Pro in AI DeliberatorRun PolicyBench for public-policy reasoningRun CogToM for social cognitionCreate and read 95% confidence-interval plotsCollaborate and preserve a reproducible experiment recordAnalyze sentiment and quantitative text metricsCompare two Council runs
Workspace

Work and teams

Analyze a policy proposal

Examine policy goals, mechanisms, affected groups, implementation, evidence, unintended effects, and alternatives.

The basic idea

Policy analysis is stronger when objectives, causal mechanisms, distributional effects, administrative feasibility, and uncertainty are evaluated separately. A council can widen the analysis but cannot replace jurisdiction-specific legal or empirical expertise.

Example

Evaluate a housing, transportation, education, or workplace policy by asking how the rule is expected to work and who bears its costs and benefits.

How to do it

  1. 1

    State the policy text or proposal accurately and identify the jurisdiction.

  2. 2

    Define the intended outcome and plausible mechanism connecting the policy to that outcome.

  3. 3

    Assign roles for implementation, equity, fiscal effects, evidence quality, and unintended consequences.

  4. 4

    Request alternative designs and measurable indicators for evaluation.

What to watch for

  • Verify current statutes, regulations, budgets, and empirical citations.
  • Distinguish disagreement about values from disagreement about predicted effects.
  • Do not present model output as an official legal interpretation.

What a useful result looks like

The result should be an inspectable policy argument with explicit beneficiaries, burdens, assumptions, and evaluation criteria.