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

Decide whether to move to a new city

Compare work, housing, commute, community, family, climate, schools, and reversibility in a relocation decision.

The basic idea

Relocation decisions fail when a vivid benefit is compared with an incomplete picture of daily life. Give the council consistent facts for both locations and separate one-time moving friction from durable differences.

Example

Compare a higher salary in Atlanta with commute time and housing, or a smaller market with lower costs, closer family, and fewer career options.

How to do it

  1. 1

    Build a side-by-side baseline for income, taxes, housing, transport, childcare, and travel to family.

  2. 2

    Describe the daily routine in each location, not just annual totals.

  3. 3

    Ask for best-case, base-case, and worst-case scenarios over two time horizons.

  4. 4

    Identify low-cost tests such as an extended visit, commute trial, or temporary lease.

What to watch for

  • Online cost-of-living averages may not match your neighborhood or household.
  • Do not overlook partner careers, caregiving, schools, and social support.
  • Check current local facts independently before committing money.

What a useful result looks like

A good run reveals whether the move remains attractive after lifestyle and uncertainty are priced into the comparison.