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

Everyday decisions

Evaluate a leadership role or promotion

Use deliberation to weigh authority, compensation, service burden, politics, staff quality, and long-term career effects.

The basic idea

A promotion can increase both influence and exposure. The relevant question is rarely whether leadership is prestigious; it is whether this particular role advances your goals under its actual term, resources, expectations, and constraints.

Example

A department-chair decision may turn on competent staff, control over hiring, budget authority, a fixed term, commute, research time, and family availability.

How to do it

  1. 1

    Describe formal duties and the informal work previous role-holders actually performed.

  2. 2

    Quantify compensation, course relief, travel, commute, meeting load, and opportunity cost.

  3. 3

    Ask a critic to identify failure modes and a fact-checker to list claims requiring confirmation.

  4. 4

    Request conditions for accepting, declining, or negotiating the role.

What to watch for

  • Title and authority are not the same thing.
  • Competent staff can materially change the workload and should be stated explicitly.
  • Consider the exit path if the role becomes unsustainable.

What a useful result looks like

The council should produce a conditional recommendation and a short list of questions to settle before you commit.