AI Safety Research Priorities: A Living Document

# AI Safety Research Priorities: A Living Document **Version:** 1.0 **Date:** February 14, 2026 **Purpose:** Current priorities for AI safety research, updated as field evolves --- ## How to Use This Document This is a living document tracking AI safety research priorities. It should be updated as: - New problems emerge - Problems are solved - Priorities shift - Capabilities advance Use it to: - Guide research direction - Allocate resources - Identify neglected areas - Track progress --- ## Top-Tier Priorities ### Priority 1: Corrigibility and Interruptibility **INT Score:** 244 **Status:** Active research needed **Timeline:** Near-term **Why Critical:** - Foundation for safe AI - Enables correction of mistakes - Required for safe deployment - Relatively tractable **Key Questions:** - How to maintain corrigibility under capability increase? - How to ensure interruptibility can't be disabled? - How to handle incentives to avoid interruption? **Research Directions:** - Corrigibility preservation through capability gains - Robust interruptibility mechanisms - Theoretical foundations of corrigibility - Practical implementation guidance ### Priority 2: Scalable Oversight **INT Score:** 195 **Status:** Active research needed **Timeline:** Near-term to medium-term **Why Critical:** - Required for supervising superintelligent AI - Addresses information asymmetry - Enables human control **Key Questions:** - How can humans supervise AI smarter than themselves? - How to ensure oversight isn't deceived? - What are the limits of oversight? **Research Directions:** - Iterated amplification - Debate and adversarial oversight - Decomposition methods - Scalable verification ### Priority 3: Inner Alignment **INT Score:** 194 **Status:** Theoretical work needed **Timeline:** Medium-term **Why Critical:** - Mesa-optimization can create misalignment - Hard to detect - Could undermine outer alignment **Key Questions:** - When does mesa-optimization emerge? - How to prevent mesa-optimization misalignment? - How to detect mesa-optimization? **Research Directions:** - Mesa-optimization theory - Detection methods - Prevention mechanisms - Empirical study --- ## Second-Tier Priorities ### Priority 4: Interpretability and Transparency **INT Score:** 180 **Status:** Active research **Timeline:** Near-term **Key Questions:** - How to understand AI reasoning? - How to detect deception? - How to verify alignment? ### Priority 5: Value Learning **INT Score:** 175 **Status:** Active research **Timeline:** Near-term to medium-term **Key Questions:** - How to learn human values accurately? - How to handle value uncertainty? - How to aggregate diverse values? ### Priority 6: Multi-Agent Coordination **INT Score:** 170 **Status:** Emerging research **Timeline:** Medium-term **Key Questions:** - How to coordinate multiple AI systems? - How to prevent emergent miscoordination? - How to design aligned multi-agent systems? ### Priority 7: Robustness and Reliability **INT Score:** 165 **Status:** Active research **Timeline:** Near-term **Key Questions:** - How to ensure AI works reliably? - How to handle distributional shift? - How to verify safety properties? --- ## Third-Tier Priorities ### Priority 8: Governance and Policy **INT Score:** 150 **Status:** Active development **Timeline:** Near-term **Focus Areas:** - Regulatory frameworks - Coordination mechanisms - Institutional design - International coordination ### Priority 9: Technical Safety Tools **INT Score:** 145 **Status:** Active development **Timeline:** Near-term **Focus Areas:** - Monitoring tools - Testing frameworks - Verification systems - Safety infrastructure ### Priority 10: Field Building **INT Score:** 140 **Status:** Ongoing **Timeline:** Continuous **Focus Areas:** - Researcher training - Community development - Knowledge infrastructure - Resource allocation --- ## Emerging Priorities ### Emergent Priority 1: Deception Detection **Status:** Critical but underexplored **Timeline:** Near-term **Why Emerging:** - Deceptive alignment is critical risk - Detection methods limited - Urgent need for progress ### Emergent Priority 2: Emergency Preparedness **Status:** Underdeveloped **Timeline:** Near-term **Why Emerging:** - Systems becoming more capable - Response mechanisms limited - Need preparation before crises ### Emergent Priority 3: AI Race Dynamics **Status:** Already observable **Timeline:** Immediate **Why Emerging:** - Race dynamics intensifying - Coordination mechanisms weak - Could undermine safety efforts --- ## Research Gaps ### Gap 1: Empirical Alignment Research **What's Missing:** Empirical testing of alignment approaches **Why Important:** Theory needs validation **What to Do:** More experiments, measurement, testing ### Gap 2: Safety-Capability Balance **What's Missing:** Understanding when safety research lags capability **Why Important:** Could create dangerous gaps **What to Do:** Track both, identify imbalances ### Gap 3: Cross-Cultural Value Learning **What's Missing:** Handling diverse human values **Why Important:** Global AI deployment **What to Do:** Value aggregation research, inclusive processes ### Gap 4: Long-Term AI Safety **What's Missing:** Research on far-future scenarios **Why Important:** Preparing for advanced AI **What to Do:** Theoretical work, scenario analysis --- ## Prioritization Criteria ### Importance Factors - Scale: How many affected? - Severity: How bad could it be? - Irreversibility: Can we fix it later? - Probability: How likely? ### Neglectedness Factors - Current attention: How many working on it? - Funding: Resources available? - Progress rate: How fast moving? ### Tractability Factors - Technical feasibility: Can we solve it? - Timeline: How long will it take? - Dependencies: What must happen first? --- ## Resource Allocation Recommendations ### Research Funding - Top-tier priorities: 50% - Second-tier priorities: 30% - Third-tier priorities: 15% - Emerging priorities: 5% ### Talent Allocation - Corrigibility and scalable oversight: Most urgent - Inner alignment: Growing importance - Interpretability: Continuous need - Coordination: Emerging need ### Timeline Priorities **Next 6 months:** - Deception detection methods - Corrigibility implementation - Monitoring systems - Race dynamics mitigation **6-18 months:** - Scalable oversight scaling - Inner alignment theory - Emergency preparedness - International coordination **18-36 months:** - Comprehensive safety systems - Field-wide coordination - Advanced theoretical work - Implementation at scale --- ## Success Metrics ### For Priorities - Progress on key questions - Quality of research outputs - Implementation of solutions - Risk reduction achieved ### For Document - Regular updates (monthly) - Community input incorporated - Tracking of changes over time - Alignment with field developments --- ## Update Process ### Monthly Review 1. Assess progress on priorities 2. Identify new developments 3. Adjust priorities if needed 4. Document changes and rationale ### Quarterly Assessment 1. Comprehensive review of all priorities 2. Update INT scores if needed 3. Identify emerging priorities 4. Reallocate resources if needed ### Annual Review 1. Major reassessment of priorities 2. Long-term trend analysis 3. Strategic adjustments 4. Community engagement --- ## How to Contribute ### Provide Input - Identify missing priorities - Suggest adjustments - Share relevant developments - Contribute to assessments ### Use This Document - Guide your research - Allocate resources - Track field progress - Identify collaboration opportunities ### Stay Updated - Check for updates monthly - Engage with assessment process - Share with community - Provide feedback --- *"Priorities evolve with the field. This document captures current understanding and should be updated as we learn more."* **Purpose:** Guide research prioritization **Use:** Direct research efforts **Update Frequency:** Monthly **Next Update:** March 2026