AI Safety Research Methods: A Systematic Approach

# AI Safety Research Methods: A Systematic Approach **Version:** 1.0 **Date:** February 14, 2026 **Purpose:** Rigorous methodology for AI safety research --- ## Why Research Methods Matter AI safety is a young field with high stakes. Poor research methods lead to: - Conclusions that don't hold up - Wasted effort on unpromising approaches - Missed opportunities for real progress - Reduced credibility for the field Good methods lead to: - Reliable findings - Efficient progress - Practical insights - Field advancement --- ## Core Principles ### Principle 1: Explicit Uncertainty Always specify confidence levels and acknowledge limitations ### Principle 2: Multiple Perspectives Consider alternative explanations and steel-man opposing views ### Principle 3: Empirical Grounding Connect theoretical claims to empirical evidence where possible ### Principle 4: Practical Value Ensure research has actionable implications ### Principle 5: Reproducibility Document methods sufficiently for others to replicate --- ## Research Types ### Type 1: Conceptual Analysis **Purpose:** Clarify concepts, develop frameworks, identify principles **When to Use:** - Concept is unclear or contested - Framework needed for further work - Theoretical foundation required **Method:** ``` 1. Define scope - What concept/area? - What's included/excluded? - What's the goal? 2. Survey existing work - Literature review - Identify key positions - Map conceptual landscape 3. Analyze - Identify key distinctions - Develop framework - Test against examples 4. Synthesize - Integrate insights - Develop framework - Identify gaps 5. Validate - Test framework - Get peer review - Iterate ``` **Quality Criteria:** - Clarity: Are concepts well-defined? - Completeness: Does it cover the domain? - Usefulness: Can others apply it? - Rigor: Is reasoning sound? ### Type 2: Literature Review **Purpose:** Synthesize existing research, identify patterns and gaps **When to Use:** - Entering new area - Mapping field - Identifying research gaps **Method:** ``` 1. Define scope - Research questions - Inclusion/exclusion criteria - Time frame 2. Search - Identify databases - Define search terms - Apply filters 3. Screen - Title/abstract review - Full text review - Apply criteria 4. Extract - Key information - Methodologies - Findings 5. Analyze - Identify patterns - Compare approaches - Assess quality 6. Synthesize - Integrate findings - Identify gaps - Suggest directions ``` **Quality Criteria:** - Comprehensiveness: Did you find relevant work? - Systematic: Was process documented? - Critical: Did you assess quality? - Synthesis: Did you integrate findings? ### Type 3: Scenario Analysis **Purpose:** Explore possible futures, identify risks and opportunities **When to Use:** - High uncertainty - Multiple possible outcomes - Strategic planning **Method:** ``` 1. Define scope - What scenarios? - Time horizon? - What variables? 2. Identify drivers - Key factors - Uncertainties - Trends 3. Develop scenarios - Base case - Best case - Worst case - Alternative cases 4. Analyze - Implications - Likelihood - Impact - Intervention points 5. Validate - Expert review - Historical analogies - Internal consistency 6. Document - Scenarios - Reasoning - Implications ``` **Quality Criteria:** - Plausibility: Are scenarios realistic? - Distinctiveness: Do scenarios differ meaningfully? - Usefulness: Do they inform decisions? - Rigor: Is reasoning documented? ### Type 4: Framework Development **Purpose:** Create systematic approaches for analysis or action **When to Use:** - Need structured approach - Complex problem - Multiple factors **Method:** ``` 1. Identify need - What problem? - Why framework needed? - Who will use it? 2. Survey approaches - Existing frameworks - Related fields - Best practices 3. Design framework - Core components - Structure - Process 4. Test framework - Apply to cases - Identify weaknesses - Iterate 5. Document - Clear explanation - Examples - Guidance 6. Validate - Peer review - User testing - Refinement ``` **Quality Criteria:** - Completeness: Does it cover the domain? - Clarity: Can others understand/use it? - Usefulness: Does it solve the problem? - Rigor: Is it systematically developed? ### Type 5: Comparative Analysis **Purpose:** Compare approaches, identify strengths and weaknesses **When to Use:** - Multiple approaches exist - Need to choose between options - Understanding trade-offs **Method:** ``` 1. Define comparison - What to compare? - What criteria? - What's the goal? 2. Characterize approaches - Each approach described - Key features - Underlying assumptions 3. Evaluate - Against criteria - Strengths - Weaknesses 4. Compare - Side-by-side - Trade-offs - Context dependence 5. Recommend - When to use each - Best practices - Hybrid approaches ``` **Quality Criteria:** - Fairness: Is each approach represented fairly? - Comprehensiveness: Are criteria complete? - Objectivity: Is evaluation unbiased? - Usefulness: Does it help decisions? --- ## Analysis Methods ### Method 1: INT Prioritization **Purpose:** Prioritize problems or opportunities **Process:** ``` 1. Score Importance (0-10) - Scale: How many affected? - Severity: How bad/good? - Irreversibility: Can it be undone? 2. Score Neglectedness (0-10) - Current attention (inverse) - Funding (inverse) - Awareness (inverse) 3. Score Tractability (0-10) - Technical feasibility - Clarity of path - Timeline 4. Calculate Priority Priority = I × N × T ``` ### Method 2: COMPLEX Problem Analysis **Purpose:** Understand and address complex problems **Components:** ``` C - Context (historical, systems, stakeholders) O - Objectives (primary, stakeholder, hierarchy) M - Mechanisms (causal chains, drivers, variables) P - Patterns (empirical, comparative, anomalies) L - Leverage Points (types, assessment, intervention) E - Evidence (types, quality, uncertainty) X - eXecute (strategy, implementation, learning) ``` ### Method 3: Scenario Planning **Purpose:** Explore possible futures **Process:** ``` 1. Identify driving forces 2. Identify critical uncertainties 3. Develop scenario matrix 4. Flesh out scenarios 5. Analyze implications 6. Identify indicators ``` ### Method 4: Root Cause Analysis **Purpose:** Identify underlying causes **Process:** ``` 1. Define problem 2. Ask "why" 5 times 3. Map causal chain 4. Identify root causes 5. Design interventions ``` ### Method 5: Stakeholder Analysis **Purpose:** Understand who's affected and their interests **Process:** ``` 1. Identify stakeholders 2. Map interests/concerns 3. Assess power/influence 4. Identify conflicts/alignments 5. Design engagement strategy ``` --- ## Quality Assurance ### Quality Checklist **For All Research:** ``` ☐ Clear research question ☐ Documented methodology ☐ Multiple perspectives ☐ Confidence levels specified ☐ Limitations acknowledged ☐ Practical implications ☐ Reproducible documentation ``` **For Theoretical Work:** ``` ☐ Concepts clearly defined ☐ Assumptions explicit ☐ Reasoning sound ☐ Counterarguments addressed ☐ Examples provided ☐ Scope defined ``` **For Empirical Work:** ``` ☐ Data sources documented ☐ Methods reproducible ☐ Limitations acknowledged ☐ Alternative explanations ☐ Statistical rigor ☐ Peer review ``` ### Peer Review Process **Submission:** ``` 1. Self-review against checklist 2. Identify specific feedback needs 3. Provide context 4. Submit to reviewer ``` **Review:** ``` 1. Overall assessment 2. Specific feedback on: - Methodology - Reasoning - Conclusions - Presentation 3. Constructive suggestions 4. Quality rating ``` **Revision:** ``` 1. Address critical issues 2. Consider all feedback 3. Document changes 4. Resubmit if needed ``` --- ## Common Pitfalls ### Pitfall 1: Insufficient Literature Review **Problem:** Reinventing the wheel, missing key insights **Solution:** Systematic literature review before starting ### Pitfall 2: Overclaiming **Problem:** Conclusions exceed evidence **Solution:** Specify confidence levels, acknowledge limitations ### Pitfall 3: Single Perspective **Problem:** Only considering one viewpoint **Solution:** Actively seek alternative perspectives ### Pitfall 4: Missing Practical Value **Problem:** Theoretical work with no application **Solution:** Always include practical implications ### Pitfall 5: Poor Documentation **Problem:** Methods unclear, not reproducible **Solution:** Document everything thoroughly --- ## Research Workflow ### Phase 1: Planning **Activities:** - Define research question - Determine type and scope - Plan methodology - Identify resources **Output:** Research plan ### Phase 2: Execution **Activities:** - Literature review - Data collection - Analysis - Documentation **Output:** Draft findings ### Phase 3: Review **Activities:** - Self-review - Peer review - Revision - Quality check **Output:** Revised draft ### Phase 4: Publication **Activities:** - Final formatting - Publication decision - Dissemination - Feedback collection **Output:** Published work --- ## Tools and Resources ### Literature Management - Reference managers (Zotero, Mendeley) - Search databases (arXiv, Google Scholar) - Note-taking systems ### Analysis Tools - Frameworks (INT, COMPLEX) - Visualization tools - Statistical software ### Collaboration - Version control (Git) - Communication tools - Shared documents ### Quality Assurance - Checklists - Peer review systems - Quality standards --- *"Rigorous methods are the foundation of reliable knowledge. In AI safety, where stakes are high and uncertainty is common, methodological rigor is essential."* **Purpose:** Systematic, rigorous research **Use:** Guide for all AI safety research **Outcome:** Reliable, valuable findings