Model Style Guide

This guide covers core purpose, summary requirements, format requirements, diagram types, methodological principles, and rating criteria for analytical models in this knowledge base.

Executive Summary Requirement

The Summary Formula

A good model summary follows this pattern:

"This model [methodology/approach]. It [key finding - trajectory, critical variables, or uncertainty assessment]."

Types of Valid Findings

Summaries should emphasize where things are going and what matters most:

Examples

Good summaries:

Bad summaries:

Frontmatter Format

---
title: "Racing Dynamics Impact Model"
description: "This model analyzes competitive pressures among frontier labs. It estimates a 60-80% probability that racing dynamics reduce safety investment by 30-50% compared to non-competitive scenarios."
quality: 3
lastEdited: "2025-12-26"
ratings:
  novelty: 4
  rigor: 3
  actionability: 4
  completeness: 3
---

The description field:

• Must state what the model does (methodology/approach)
• Must include key conclusions with quantified estimates where possible
• Should be 1-3 sentences (max ~250 characters for good preview display)
• Is shown in entity cards, backlinks, and search results

Displaying the Summary on the Page

Add a ## Summary section at the top of every model page that references the frontmatter:

{/* Replace with actual entity ID from entities.yaml */}
<DataInfoBox entityId="E43" ratings={frontmatter.ratings} />

## Summary

{frontmatter.description}

## Overview

[Detailed context and background...]

This way the summary text lives only in frontmatter and is rendered on the page via {frontmatter.description}.

Core Purpose: Strategic Prioritization

The Goal

The knowledge base serves people making strategic decisions about AI safety:

• Researchers deciding what to work on
• Funders deciding where to allocate resources
• Policymakers deciding what to regulate
• Organizations deciding their focus areas

Models should help them decide what matters most and what to do about it.

Required Strategic Content

Every model must include:

Common Mistake: Mechanism Without Magnitude

Bad example (from a hypothetical sycophancy model):

"The feedback loop operates through 4 phases over 10 years, with differential equations governing each variable..."

(300 lines on mechanism, 0 lines on strategic importance)

What's missing:

• Is sycophancy a top-5 AI risk or a minor concern?
• Should safety orgs prioritize this over alignment research?
• How does this compare to racing dynamics or concentration risks?
• What beliefs would change whether this matters?

Better approach:

"Sycophancy represents approximately 5-15% of near-term AI risk, ranking below core alignment but above most misuse risks. For most safety organizations, this is a secondary priority unless they have specific comparative advantage. The key crux is whether market competition makes sycophancy inevitable—if so, regulatory intervention becomes critical."

Strategic Importance Section Template

Include a section like this in every model:

## Strategic Importance

### Magnitude
- **Share of total AI risk:** [X-Y%]
- **Affected population:** [scope]
- **Timeline:** [when effects materialize]

### Comparative Ranking
| Risk Category | Relative Importance | Reasoning |
|---------------|--------------------:|-----------|
| Core alignment | Higher | [why] |
| This risk | Baseline | - |
| [Other risk] | Lower | [why] |

### Resource Implications
- **Who should work on this:** [actor types]
- **Suggested allocation:** [% of resources]
- **Comparative advantage:** [who is best positioned]

### Key Cruxes
1. If [X], this becomes more important because [Y]
2. If [A], this becomes less important because [B]

Part 1: Structure Requirements

Overview Section

Write 2-3 paragraphs of flowing prose (no bullet points). The overview should:

• Explain the model's central insight in the first paragraph
• Describe why understanding this matters in the second paragraph
• Preview key findings or framework structure in the third paragraph

Required Sections

Tables

Include tables with 3+ columns and 4+ rows. Tables should add structured information beyond what prose conveys.

Good table characteristics:

• Uncertainty ranges (low/central/high estimates)
• Comparison across multiple dimensions
• Clear headers that explain what each column means
• Sources or confidence levels where relevant

Part 2: Diagram Types

Models should include at least one diagram. Choose the type that best represents your model's structure.

Flowcharts (Process/Causation)

Use for: Showing how things lead to other things, causal chains, decision processes.

flowchart TD
    A[Initial Condition] --> B[Intermediate State]
    B --> C[Outcome 1]
    B --> D[Outcome 2]

Network Diagrams (Relationships)

Use for: Showing how multiple factors influence each other, feedback loops, complex interdependencies.

State Diagrams (Transitions)

Use for: Showing how systems move between discrete states, regime changes, phase transitions.

Interactions Over Time

For showing how different actors or systems interact in sequence, attack chains, or response protocols, use a table rather than a sequence diagram (which has rendering issues):

For simple flows, a basic flowchart works well:

Entity Relationship Diagrams (Schemas)

Use for: Showing structural relationships between concepts, taxonomies, classification systems.

Quadrant Diagrams (2x2 Matrices)

Use for: Classifying items along two dimensions, prioritization frameworks, strategic positioning.

Timeline Diagrams

Use for: Showing progression over time, milestone projections, historical development.

Subgraph Groupings

Use for: Showing categories of related items, system boundaries, domain separation.

Part 3: Schema Structures

For models describing structural relationships, use schema-style representations.

When to Use Schemas

• Defining taxonomy of related concepts
• Showing how entities relate to each other
• Describing data structures or classification systems
• Mapping stakeholder relationships

Schema Example: Risk Factor Taxonomy

Schema Example: Actor Relationships

Part 4: Methodological Principles

Distinguish Stocks vs. Flows

Identify Feedback Loops

Many risks involve feedback loops where effects become causes. Make these explicit.

Positive feedback loops (amplifying): The effect reinforces the cause. Negative feedback loops (stabilizing): The effect counteracts the cause.

Consider Base Rates

Before modeling specific mechanisms, consider: what's the base rate for this type of event?

Distinguish Correlation vs. Causation

When factors co-occur, be explicit about the causal structure:

Avoid False Binary Thresholds

Better approach:

• Use gradient language: "largely past," "degrading," "limited risk"
• Acknowledge that most systems degrade continuously
• If using threshold framing, add explicit caveats

Avoid Naive Multiplicative Formulas

Better approach:

1. Acknowledge correlations explicitly in a table
2. Use influence diagrams instead of formulas
3. If using formulas, add caveats about correlation assumptions

Consider Counterfactuals

Good models should address: "Compared to what?"

Part 5: Rating System

Each model is rated on four dimensions (1-5 scale). These ratings appear in the model's info box.

Novelty (1-5)

How much does this model add beyond existing frameworks?

Rigor (1-5)

How well-supported and internally consistent is the model?

Actionability (1-5)

How useful is this model for decision-making?

Completeness (1-5)

How thoroughly does the model cover its domain?

How to Assign Ratings

When reviewing a model, ask:

1. Novelty: "Have I seen this idea before? Does it change how I think?"
2. Rigor: "Would I bet money on these claims? What's the evidence quality?"
3. Actionability: "Could I make a decision based on this? What would I do differently?"
4. Completeness: "What's missing? Would adding more change the conclusions?"

Part 6: Advanced Visualization Ideas

Sensitivity Analysis Tables

Show how conclusions change with different assumptions:

Comparison Matrices

Compare interventions, scenarios, or approaches:

Before/After Comparisons

Show how a change affects multiple dimensions:

Decision Trees

For models with sequential choices:

Part 7: Review Checklist

Format

• Overview is 2-3 paragraphs of flowing prose (no bullets)
• At least one Mermaid diagram with caption
• Quantitative tables with 3+ columns and uncertainty ranges
• Scenario analysis with probability weights
• Limitations section in prose format
• Related models linked

Diagrams

• Diagram type matches content (flowchart for causation, network for relationships, etc.)
• Diagram has explanatory caption
• Complex diagrams use subgraphs for grouping
• Color coding is meaningful and explained

Methodology

• No false binary thresholds (or explicitly caveated)
• Multiplicative formulas acknowledge correlations
• Feedback loops identified where relevant
• Stocks vs. flows distinguished
• Base rates considered
• Counterfactual comparisons made

Ratings

• All four ratings assigned (novelty, rigor, actionability, completeness)
• Ratings are justified by content quality
• Ratings are consistent with similar models

Content Consistency

• Every simplifying assumption is explicitly flagged as such (with a pointer to Limitations), never asserted as fact
• Every [0, 1] or other numeric scale has grounded anchors defining what the endpoints mean — write anchors before writing estimates that use the scale
• Rankings with overlapping ranges say "roughly ordered by median" or "suggestive, not definitive" — no definitive ordinal rankings when ranges overlap
• Option value of delay is addressed (additional time lets us learn whether alignment is hard or easy)
• Racing/coordination effects are addressed (does unilateral action just shift activity elsewhere?)
• Recursive dynamics are addressed where relevant (e.g. AI accelerating safety research) — goes beyond the structural feedback loops in Methodology to check for domain-specific self-referential dynamics
• Effects are distinguished as qualitatively different where appropriate, not just quantitatively shifted

Common Issues to Fix