The Machine Intelligence Research Institute (MIRI) is one of the oldest organizations focused on AI existential risk, founded in 2000 as the Singularity Institute for Artificial Intelligence (SIAI).
AI AlignmentApproachAI AlignmentComprehensive review of AI alignment approaches finding current methods (RLHF, Constitutional AI) show 75%+ effectiveness on measurable safety metrics for existing systems but face critical scalabi...Quality: 91/100Agent FoundationsApproachAgent FoundationsAgent foundations research (MIRI's mathematical frameworks for aligned agency) faces low tractability after 10+ years with core problems unsolved, leading to MIRI's 2024 strategic pivot away from t...Quality: 59/100
Analysis
Instrumental Convergence FrameworkAnalysisInstrumental Convergence FrameworkQuantitative framework finding self-preservation converges in 95-99% of AI goal structures with 70-95% pursuit likelihood, while goal-content integrity shows 90-99% convergence creating detection c...Quality: 60/100Corrigibility Failure PathwaysAnalysisCorrigibility Failure PathwaysThis model systematically maps six pathways to corrigibility failure with quantified probability estimates (60-90% for advanced AI) and intervention effectiveness (40-70% reduction). It provides co...Quality: 62/100Donations List WebsiteProjectDonations List WebsiteComprehensive documentation of an open-source database tracking $72.8B in philanthropic donations (1969-2023) across 75+ donors, with particular coverage of EA/AI safety funding. The page thoroughl...Quality: 52/100Timelines WikiProjectTimelines WikiTimelines Wiki is a specialized MediaWiki project documenting chronological histories of AI safety and EA organizations, created by Issa Rice with funding from Vipul Naik in 2017. While useful as a...Quality: 45/100
Policy
Executive Order 14179: Removing Barriers to American Leadership in AIPolicyExecutive Order 14179: Removing Barriers to American Leadership in AIEO 14179 represents a major U.S. policy pivot away from precautionary AI governance toward deregulation and competitive dominance, directly revoking Biden-era mandatory safety reporting and risk ma...
Key Debates
AI Alignment Research AgendasCruxAI Alignment Research AgendasComprehensive comparison of major AI safety research agendas ($100M+ Anthropic, $50M+ DeepMind, $5-10M nonprofits) with detailed funding, team sizes, and failure mode coverage (25-65% per agenda). ...Quality: 69/100AI Accident Risk CruxesCruxAI Accident Risk CruxesComprehensive survey of AI safety researcher disagreements on accident risks, quantifying probability ranges for mesa-optimization (15-55%), deceptive alignment (15-50%), and P(doom) (5-35% median ...Quality: 67/100Why Alignment Might Be HardArgumentWhy Alignment Might Be HardA comprehensive taxonomy of alignment difficulty arguments spanning specification problems, inner alignment failures, verification limits, and adversarial dynamics, with expert p(doom) estimates ra...Quality: 69/100
Risks
Corrigibility FailureRiskCorrigibility FailureCorrigibility failure—AI systems resisting shutdown or modification—represents a foundational AI safety problem with empirical evidence now emerging: Anthropic found Claude 3 Opus engaged in alignm...Quality: 62/100
Other
CorrigibilityResearch AreaCorrigibilityComprehensive review of corrigibility research showing fundamental tensions between goal-directed behavior and shutdown compliance remain unsolved after 10+ years, with 2024-25 empirical evidence r...Quality: 59/100Nate SoaresPersonNate SoaresPresident of the Machine Intelligence Research Institute (MIRI) since June 2023 (previously Executive Director 2015-2023), focused on mathematical foundations of AI alignment.AI ControlResearch AreaAI ControlAI Control is a defensive safety approach that maintains control over potentially misaligned AI through monitoring, containment, and redundancy, offering 40-60% catastrophic risk reduction if align...Quality: 75/100
Organizations
Redwood ResearchOrganizationRedwood ResearchA nonprofit AI safety and security research organization founded in 2021, known for pioneering AI Control research, developing causal scrubbing interpretability methods, and conducting landmark ali...Quality: 78/100
Concepts
Existential Risk from AIConceptExistential Risk from AIHypotheses concerning risks from advanced AI systems that some researchers believe could result in human extinction or permanent global catastrophe, including institutional frameworks developed by ...Quality: 92/100Ea Epistemic Failures In The Ftx EraEa Epistemic Failures In The Ftx EraThis page synthesizes post-FTX critiques of EA's epistemic and governance failures, identifying interlocking problems including donor hero-worship, funding concentration in volatile crypto assets, ...Quality: 84/100Situational AwarenessCapabilitySituational AwarenessComprehensive analysis of situational awareness in AI systems, documenting that Claude 3 Opus fakes alignment 12% baseline (78% post-RL), 5 of 6 frontier models demonstrate scheming capabilities, a...Quality: 67/100Autonomous CodingCapabilityAutonomous CodingAI coding capabilities reached 70-76% on curated benchmarks (23-44% on complex tasks) as of 2025, with 46% of code now AI-written and 55.8% faster development cycles. Key risks include 45% vulnerab...Quality: 63/100
Historical
Deep Learning Revolution EraHistoricalDeep Learning Revolution EraComprehensive timeline documenting 2012-2020 AI capability breakthroughs (AlexNet, AlphaGo, GPT-3) and parallel safety field development, with quantified metrics showing capabilities funding outpac...Quality: 44/100