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302With Importance

67.0Avg Importance

307With Quality

Columns: Imp = Importance (0-100)Qual = Quality (0-100)Struct = Structural score (tables, diagrams, sections)Words = Word countLinks = Backlinks from other pagesGap = Priority score (high importance + low quality)Age = Days since last editRefs = Resource references with hover tooltipsUnconv = Unconverted links (could have hover tooltips)Dup = Max similarity to other pages (hover for list)

351 of 351 results


95	88	12/15	Scheming & Deception Detection	Responses	1.9k	0	7	10d	—	—	21%
92	88	11/15	Solution Cruxes	Cruxes	3.5k	0	4	10d	62	—	20%
92	88	15/15	AI Risk Portfolio Analysis	Models	2.2k	2	4	10d	19	10	16%
92	88	15/15	Intervention Effectiveness Matrix	Models	4.3k	1	4	10d	55	10	19%
92	88	15/15	Instrumental Convergence	Risks	4.2k	10	4	10d	63	7	24%
90	4	13/15	Carlsmith's Six-Premise Argument	Models	1.9k	0	86	5d	7	—	17%
90	91	12/15	Safety-Capability Gap	Parameters	2.6k	10	-1	9d	44	—	19%
88	92	10/15	AI Control	Responses	2.6k	8	-4	11d	15	—	20%
88	91	15/15	Alignment Robustness	Parameters	2.9k	12	-3	9d	24	4	21%
87	88	11/15	Warning Signs Model	Models	3.5k	2	-1	12d	60	—	18%
87	88	9/15	Safety Research Allocation Model	Models	1.8k	0	-1	11d	26	—	15%
87	89	15/15	Intervention Timing Windows	Models	4.4k	0	-2	10d	41	7	18%
87	88	9/15	AI Governance and Policy	Responses	2.6k	1	-1	11d	71	—	21%
85	87	10/15	Large Language Models	Capabilities	1.5k	2	-2	14d	22	—	16%
85	82	10/15	Long-Horizon Autonomous Tasks	Capabilities	1.6k	0	3	14d	39	—	16%
85	82	12/15	Self-Improvement and Recursive Enhancement	Capabilities	4.0k	5	3	10d	27	—	22%
85	88	10/15	AI Capabilities Metrics	Metrics	3.0k	1	-3	—	52	—	17%
85	88	12/15	AI Proliferation Risk Model	Models	1.9k	1	-3	12d	23	—	16%
85	88	14/15	AI Uplift Assessment Model	Models	4.5k	1	-3	10d	12	4	21%
85	82	11/15	Capability Threshold Model	Models	2.9k	2	3	10d	78	—	20%
85	88	11/15	Corrigibility Failure Pathways	Models	2.0k	2	-3	—	25	—	20%
85	88	9/15	Power-Seeking Emergence Conditions Model	Models	2.3k	1	-3	—	23	—	20%
85	89	11/15	AI-Assisted Alignment	Responses	1.4k	0	-4	10d	29	—	16%
85	88	11/15	AI Alignment	Responses	2.6k	0	-3	10d	47	—	19%
85	88	11/15	Corrigibility Research	Responses	2.0k	4	-3	10d	14	—	21%
85	82	11/15	Evals & Red-teaming	Responses	2.4k	3	3	10d	15	—	16%
85	82	11/15	Mechanistic Interpretability	Responses	3.2k	15	3	10d	24	—	23%
85	82	11/15	Research Agenda Comparison	Responses	4.4k	0	3	10d	39	—	22%
85	82	11/15	Scalable Oversight	Responses	1.3k	13	3	10d	31	—	23%
85	88	10/15	Technical AI Safety Research	Responses	2.6k	0	-3	10d	56	—	20%
85	89	10/15	Coordination Technologies	Responses	2.2k	0	-4	14d	40	—	17%
85	82	9/15	AI Evaluation	Responses	1.2k	0	3	11d	35	—	19%
85	82	11/15	Policy Effectiveness Assessment	Responses	3.4k	0	3	10d	27	—	23%
85	88	11/15	Responsible Scaling Policies	Responses	4.0k	0	-3	10d	18	—	24%
85	82	11/15	Corrigibility Failure	Risks	2.9k	8	3	10d	55	—	24%
85	88	10/15	Deceptive Alignment	Risks	1.4k	20	-3	14d	21	—	16%
85	82	11/15	Power-Seeking AI	Risks	2.2k	11	3	10d	25	—	23%
85	82	11/15	Scheming	Risks	3.1k	8	3	10d	17	—	23%
85	82	11/15	Sharp Left Turn	Risks	3.3k	3	3	10d	34	—	22%
85	91	15/15	Interpretability Coverage	Parameters	3.3k	4	-6	9d	28	9	23%
85	91	12/15	Racing Intensity	Parameters	3.4k	13	-6	9d	65	—	21%
84	82	9/15	Autonomous Coding	Capabilities	1.5k	2	2	14d	18	—	16%
84	82	11/15	Situational Awareness	Capabilities	2.9k	6	2	10d	11	—	22%
84	82	11/15	Accident Risk Cruxes	Cruxes	3.0k	0	2	10d	46	—	20%
84	88	12/15	Risk Cascade Pathways	Models	1.8k	2	-4	12d	19	—	15%
84	82	11/15	Expected Value of AI Safety Research	Models	1.3k	1	2	12d	31	—	16%
84	88	10/15	Scheming Likelihood Assessment	Models	1.5k	2	-4	—	15	—	20%
84	82	10/15	AI-Bioweapons Timeline Model	Models	2.6k	1	2	12d	—	—	20%
84	88	10/15	Risk Activation Timeline Model	Models	2.9k	2	-4	12d	24	—	15%
84	88	13/15	Lab Safety Culture	Responses	3.6k	0	-4	10d	36	9	19%
83	88	12/15	Defense in Depth Model	Models	1.7k	1	-5	12d	23	—	14%
82	85	9/15	Persuasion and Social Manipulation	Capabilities	1.8k	0	-3	14d	22	—	16%
82	88	14/15	Reasoning and Planning	Capabilities	4.0k	1	-6	10d	43	2	22%
82	88	14/15	Tool Use and Computer Use	Capabilities	3.3k	1	-6	10d	28	1	22%
82	92	13/15	The Case AGAINST AI Existential Risk	Debates	1.8k	0	-10	10d	21	2	23%
82	80	9/15	Why Alignment Might Be Hard	Debates	4.2k	0	2	10d	25	—	24%
82	88	10/15	AGI Timeline	Forecasting	1.1k	0	-6	11d	19	—	17%
82	91	12/15	Alignment Progress	Metrics	4.6k	3	-9	10d	63	—	19%
82	87	11/15	Lab Behavior & Industry	Metrics	4.4k	3	-5	10d	50	—	19%
82	80	11/15	Critical Uncertainties Model	Models	2.6k	0	2	10d	30	—	17%
82	88	11/15	Multipolar Trap Dynamics Model	Models	1.8k	2	-6	12d	25	—	17%
82	88	10/15	Racing Dynamics Impact Model	Models	1.7k	3	-6	13d	23	—	18%
82	88	14/15	Risk Interaction Matrix Model	Models	2.7k	1	-6	10d	13	11	16%
82	88	11/15	Risk Interaction Network	Models	2.0k	2	-6	11d	25	—	16%
82	88	11/15	International AI Coordination Game	Models	1.9k	3	-6	11d	36	—	18%
82	88	12/15	Worldview-Intervention Mapping	Models	2.3k	1	-6	12d	25	—	15%
82	88	10/15	Capability-Alignment Race Model	Models	1.1k	0	-6	10d	14	—	17%
82	87	11/15	Deceptive Alignment Decomposition Model	Models	2.2k	4	-5	12d	19	—	18%
82	88	12/15	Goal Misgeneralization Probability Model	Models	1.8k	0	-6	12d	23	—	17%
82	88	12/15	Mesa-Optimization Risk Analysis	Models	1.7k	0	-6	12d	35	—	19%
82	88	12/15	Capabilities-to-Safety Pipeline Model	Models	2.5k	1	-6	11d	23	—	15%
82	88	10/15	AI Safety Talent Supply/Demand Gap Model	Models	2.6k	1	-6	11d	17	—	15%
82	88	14/15	Multi-Agent Safety	Responses	3.1k	0	-6	10d	14	—	17%
82	80	11/15	Compute Monitoring	Responses	4.5k	0	2	10d	24	—	23%
82	88	10/15	Voluntary Industry Commitments	Responses	3.6k	3	-6	11d	8	—	24%
82	85	13/15	International Coordination Mechanisms	Responses	3.8k	0	-3	10d	42	1	25%
82	88	8/15	California SB 1047	Responses	3.5k	0	-6	10d	28	—	19%
82	88	10/15	EU AI Act	Responses	1.5k	5	-6	11d	19	—	16%
82	85	11/15	Open Source Safety	Responses	2.1k	0	-3	10d	56	—	13%
82	88	14/15	Pause Advocacy	Responses	4.0k	0	-6	10d	51	2	20%
82	88	11/15	Emergent Capabilities	Risks	2.2k	1	-6	10d	48	—	17%
82	82	11/15	Goal Misgeneralization	Risks	2.5k	8	0	10d	24	—	22%
82	82	11/15	Mesa-Optimization	Risks	2.9k	9	0	10d	25	—	23%
82	82	11/15	Treacherous Turn	Risks	2.7k	4	0	10d	20	—	23%
82	78	13/15	Bioweapons	Risks	9.9k	8	4	10d	72	—	21%
82	78	10/15	Lock-in	Risks	3.5k	9	4	10d	107	—	23%
82	78	11/15	Multipolar Trap	Risks	3.3k	8	4	10d	16	—	20%
82	88	10/15	Racing Dynamics	Risks	1.9k	30	-6	14d	53	—	21%
82	91	15/15	Biological Threat Exposure	Parameters	3.1k	4	-9	9d	5	2	19%
82	91	15/15	Human Oversight Quality	Parameters	3.5k	10	-9	9d	25	11	19%
81	88	14/15	Large Language Models	Foundation models	2.4k	0	-7	10d	14	6	20%
81	80	11/15	Reward Hacking	Risks	3.1k	12	1	10d	31	—	21%
80	78	12/15	Agentic AI	Capabilities	4.4k	5	2	10d	42	—	22%
80	68	12/15	Alignment Robustness Trajectory	Models	1.5k	0	12	9d	—	—	15%
80	91	15/15	International Coordination	Parameters	3.0k	9	-11	9d	14	6	23%
80	91	15/15	Safety Culture Strength	Parameters	2.4k	7	-11	9d	7	9	16%
79	82	9/15	The Case FOR AI Existential Risk	Debates	4.9k	0	-3	10d	37	—	24%
79	82	10/15	AGI Development	Forecasting	1.2k	0	-3	11d	18	—	17%
79	87	10/15	AI-Human Hybrid Systems	Responses	1.9k	0	-8	11d	34	—	16%
79	87	12/15	Model Registries	Responses	1.8k	0	-8	10d	—	—	17%
79	78	10/15	Governance-Focused Worldview	Worldviews	3.8k	0	1	10d	39	—	21%
78	87	13/15	Misuse Risk Cruxes	Cruxes	1.8k	0	-9	10d	15	14	14%
78	82	10/15	Why Alignment Might Be Easy	Debates	3.9k	0	-4	10d	41	—	22%
78	82	8/15	Pause and Redirect - The Deliberate Path	Future projections	5.0k	0	-4	10d	46	—	25%
78	85	10/15	Compute & Hardware	Metrics	3.7k	2	-7	10d	78	—	14%
78	82	12/15	Compounding Risks Analysis	Models	1.8k	3	-4	12d	28	—	16%
78	88	11/15	Autonomous Weapons Escalation Model	Models	2.6k	0	-10	11d	23	—	14%
78	87	11/15	Bioweapons Attack Chain Model	Models	2.0k	1	-9	12d	21	—	15%
78	82	9/15	Autonomous Cyber Attack Timeline	Models	1.7k	1	-4	11d	35	—	16%
78	82	10/15	Instrumental Convergence Framework	Models	2.4k	0	-4	12d	21	—	18%
78	80	11/15	Multi-Actor Strategic Landscape	Models	1.9k	0	-2	10d	26	—	16%
78	82	12/15	Reward Hacking Taxonomy and Severity Model	Models	6.6k	0	-4	10d	22	—	23%
78	82	10/15	METR	Organizations	3.7k	7	-4	10d	23	—	24%
78	82	11/15	Anthropic Core Views	Responses	3.1k	1	-4	10d	57	—	20%
78	82	10/15	Constitutional AI	Responses	1.1k	0	-4	11d	18	—	14%
78	82	10/15	Red Teaming	Responses	967	0	-4	11d	12	—	18%
78	82	11/15	Representation Engineering	Responses	1.7k	0	-4	10d	—	—	17%
78	82	11/15	Influencing AI Labs Directly	Responses	3.4k	0	-4	10d	25	—	19%
78	82	9/15	Field Building Analysis	Responses	3.4k	0	-4	10d	46	—	16%
78	82	11/15	AI Chip Export Controls	Responses	4.2k	0	-4	10d	34	—	23%
78	82	12/15	Hardware-Enabled Governance	Responses	1.8k	0	-4	10d	—	—	17%
78	82	11/15	International Compute Regimes	Responses	5.5k	0	-4	10d	29	—	23%
78	82	14/15	Compute Thresholds	Responses	3.4k	0	-4	10d	—	13	23%
78	82	10/15	International AI Safety Summits	Responses	4.0k	3	-4	10d	13	—	25%
78	82	11/15	Seoul AI Safety Summit Declaration	Responses	2.9k	0	-4	10d	31	—	21%
78	82	11/15	Colorado AI Act (SB 205)	Responses	3.4k	0	-4	10d	48	—	21%
78	87	15/15	US Executive Order on AI	Responses	3.3k	5	-9	10d	30	2	21%
78	82	11/15	AI Safety Institutes	Responses	4.3k	0	-4	10d	37	—	25%
78	82	11/15	AI Whistleblower Protections	Responses	1.8k	0	-4	10d	—	—	14%
78	82	11/15	Distributional Shift	Risks	2.6k	1	-4	10d	14	—	18%
78	81	9/15	Sandbagging	Risks	2.0k	7	-3	10d	27	—	20%
78	88	11/15	Authoritarian Takeover	Risks	2.6k	2	-10	10d	31	—	18%
78	91	15/15	Epistemic Health	Parameters	2.7k	11	-13	9d	15	3	25%
77	80	11/15	Scientific Research Capabilities	Capabilities	7.0k	0	-3	10d	28	—	21%
77	78	12/15	Flash Dynamics Threshold Model	Models	2.9k	1	-1	12d	—	—	16%
75	70	12/15	Parameter Interaction Network	Models	1.4k	0	5	9d	—	—	14%
75	82	7/15	Expertise Atrophy Progression Model	Models	2.6k	2	-7	13d	—	—	19%
75	82	11/15	AI Safety Training Programs	Responses	1.7k	0	-7	10d	—	—	14%
75	87	11/15	Epistemic Security	Responses	3.5k	1	-12	10d	47	—	23%
75	82	11/15	Institutional Decision Capture	Risks	7.7k	1	-7	10d	39	—	21%
75	91	12/15	AI Control Concentration	Parameters	3.1k	8	-16	9d	58	—	18%
75	—	5/15	Coordination Capacity	Parameters	251	3	—	9d	—	—	13%
75	91	15/15	Cyber Threat Exposure	Parameters	3.5k	4	-16	9d	22	3	19%
75	91	15/15	Regulatory Capacity	Parameters	3.4k	4	-16	9d	14	11	22%
74	82	9/15	Safety Research & Resources	Metrics	1.6k	3	-8	—	27	—	15%
74	71	9/15	Irreversibility Threshold Model	Models	3.1k	0	3	12d	—	—	19%
74	82	11/15	Authentication Collapse Timeline Model	Models	6.3k	2	-8	12d	5	—	23%
74	78	11/15	RLHF / Constitutional AI	Responses	2.3k	3	-4	10d	27	—	19%
74	82	10/15	Corporate Responses	Responses	1.0k	0	-8	11d	12	—	15%
74	82	6/15	Authoritarian Tools	Risks	1.7k	5	-8	14d	42	—	20%
73	82	10/15	NIST AI Risk Management Framework	Responses	2.9k	1	-9	10d	10	—	24%
73	82	11/15	AI Standards Bodies	Responses	3.6k	0	-9	10d	27	—	24%
73	82	7/15	Proliferation	Risks	1.3k	4	-9	14d	64	—	17%
72	76	10/15	Structural Risk Cruxes	Cruxes	1.9k	0	-4	10d	34	—	21%
72	78	9/15	Misaligned Catastrophe - The Bad Ending	Future projections	4.3k	0	-6	10d	33	—	24%
72	82	11/15	Technical Pathway Decomposition	Models	2.3k	0	-10	10d	24	—	19%
72	78	11/15	Automation Bias Cascade Model	Models	3.7k	2	-6	11d	—	—	20%
72	82	10/15	Cyber Offense-Defense Balance Model	Models	2.7k	1	-10	12d	—	—	19%
72	78	8/15	Feedback Loop & Cascade Model	Models	1.2k	0	-6	11d	—	—	16%
72	78	11/15	Safety-Capability Tradeoff Model	Models	5.0k	3	-6	12d	—	—	21%
72	70	12/15	Safety Culture Equilibrium	Models	1.4k	0	2	9d	—	—	14%
72	78	9/15	Lock-in Probability Model	Models	467	0	-6	9d	11	—	—
72	82	8/15	Societal Response & Adaptation Model	Models	992	0	-10	11d	—	—	16%
72	82	10/15	Anthropic	Organizations	1.5k	31	-10	14d	13	—	19%
72	78	11/15	Agent Foundations	Responses	2.3k	0	-6	10d	20	—	16%
72	82	11/15	Preference Optimization Methods	Responses	1.9k	0	-10	10d	—	—	19%
72	83	10/15	Content Authentication & Provenance	Responses	2.5k	1	-11	10d	29	—	13%
72	82	11/15	AI-Assisted Deliberation Platforms	Responses	3.6k	0	-10	10d	68	—	19%
72	80	11/15	Failed and Stalled AI Policy Proposals	Responses	3.7k	0	-8	10d	28	—	22%
72	82	11/15	Cyberweapons	Risks	3.2k	8	-10	10d	61	—	18%
72	91	12/15	Information Authenticity	Parameters	2.6k	6	-19	9d	50	—	22%
72	91	15/15	Institutional Quality	Parameters	3.1k	6	-19	9d	9	7	22%
70	68	12/15	Regulatory Capacity Threshold Model	Models	1.4k	0	2	9d	—	—	14%
70	91	15/15	Human Expertise	Parameters	3.5k	6	-21	9d	23	3	19%
70	91	15/15	Reality Coherence	Parameters	3.3k	2	-21	9d	15	2	25%
70	91	15/15	Societal Resilience	Parameters	2.8k	3	-21	9d	4	3	18%
68	72	8/15	Expert Opinion	Metrics	2.3k	2	-4	14d	—	—	19%
68	80	11/15	Canada AIDA	Responses	4.1k	0	-12	10d	19	—	20%
68	80	11/15	US State AI Legislation	Responses	3.8k	0	-12	10d	21	—	21%
68	82	10/15	Public Education	Responses	917	0	-14	11d	31	—	11%
68	82	10/15	Flash Dynamics	Risks	3.3k	4	-14	10d	27	—	17%
67	72	3/15	Open vs Closed Source AI	Debates	407	0	-5	—	—	—	—
67	72	9/15	AI-Augmented Forecasting	Responses	2.6k	0	-5	11d	10	—	20%
67	80	12/15	Autonomous Weapons	Risks	2.9k	3	-13	10d	33	—	17%
67	78	10/15	Enfeeblement	Risks	1.3k	3	-11	14d	21	—	14%
66	72	9/15	AI Lab Incentives Model	Models	1.3k	4	-6	12d	—	—	16%
65	72	3/15	Epistemic Cruxes	Cruxes	600	0	-7	14d	—	—	13%
65	91	15/15	Societal Trust	Parameters	2.8k	10	-26	9d	12	10	23%
64	82	10/15	Multipolar Competition - The Fragmented World	Future projections	4.6k	0	-18	10d	25	—	24%
64	78	10/15	Whistleblower Dynamics Model	Models	6.4k	0	-14	11d	—	—	22%
64	72	6/15	Economic Disruption Impact Model	Models	2.1k	2	-8	13d	—	—	17%
64	72	11/15	Winner-Take-All Concentration Model	Models	3.0k	2	-8	12d	—	—	17%
64	72	8/15	Consensus Manufacturing Dynamics Model	Models	1.5k	0	-8	12d	—	—	15%
64	82	10/15	AI Surveillance and Regime Durability Model	Models	3.3k	0	-18	10d	29	—	18%
64	78	10/15	UK AI Safety Institute	Organizations	3.6k	9	-14	10d	20	—	23%
64	72	10/15	Apollo Research	Organizations	1.7k	4	-8	14d	4	—	20%
64	82	10/15	Prediction Markets	Responses	1.6k	0	-18	11d	34	—	10%
64	82	9/15	Steganography	Risks	1.1k	0	-18	11d	19	—	18%
64	65	8/15	Sycophancy	Risks	338	7	-1	9d	4	—	—
64	72	9/15	Authentication Collapse	Risks	963	2	-8	14d	15	—	12%
64	78	10/15	Mass Surveillance	Risks	3.1k	5	-14	10d	—	—	21%
64	82	10/15	Winner-Take-All Dynamics	Risks	1.5k	5	-18	14d	30	—	15%
63	72	12/15	Trust Cascade Failure Model	Models	3.5k	4	-9	12d	3	—	22%
62	78	10/15	Is Interpretability Sufficient for Safety?	Debates	1.8k	0	-16	10d	16	—	21%
62	72	2/15	Should We Pause AI Development?	Debates	673	0	-10	—	—	—	13%
62	78	8/15	Slow Takeoff Muddle - Muddling Through	Future projections	4.9k	0	-16	10d	33	—	26%
62	78	9/15	Geopolitics & Coordination	Metrics	3.3k	2	-16	—	27	—	19%
62	72	6/15	Meta & Structural Indicators	Metrics	3.1k	0	-10	—	56	—	18%
62	78	10/15	LAWS Proliferation Model	Models	5.4k	0	-16	12d	—	—	21%
62	72	10/15	Deepfakes Authentication Crisis Model	Models	4.7k	2	-10	11d	—	—	23%
62	72	8/15	Institutional Adaptation Speed Model	Models	2.4k	3	-10	11d	—	—	16%
62	72	9/15	Electoral Impact Assessment Model	Models	2.5k	0	-10	11d	—	—	15%
62	78	10/15	Authoritarian Tools Diffusion Model	Models	7.0k	0	-16	12d	—	—	22%
62	78	10/15	Sycophancy Feedback Loop Model	Models	3.3k	3	-16	13d	4	—	20%
62	72	12/15	Epistemic Collapse Threshold Model	Models	1.4k	3	-10	12d	—	—	22%
62	78	10/15	ARC (Alignment Research Center)	Organizations	1.6k	8	-16	14d	12	—	20%
62	82	10/15	Epoch AI	Organizations	1.5k	2	-20	14d	28	—	15%
62	82	12/15	GovAI	Organizations	1.7k	5	-20	10d	—	1	12%
62	78	10/15	MIRI	Organizations	2.0k	9	-16	14d	16	—	16%
62	78	11/15	China AI Regulations	Responses	3.6k	1	-16	10d	44	—	23%
62	82	11/15	Labor Transition & Economic Resilience	Responses	1.7k	0	-20	10d	—	—	15%
62	72	4/15	Automation Bias	Risks	1.5k	3	-10	14d	—	—	17%
62	78	11/15	Consensus Manufacturing	Risks	3.5k	4	-16	10d	30	—	20%
62	78	10/15	Epistemic Sycophancy	Risks	3.5k	3	-16	10d	28	—	19%
62	78	10/15	AI Knowledge Monopoly	Risks	1.9k	1	-16	14d	38	—	14%
62	78	10/15	Epistemic Learned Helplessness	Risks	1.5k	4	-16	5d	21	—	12%
62	82	10/15	Scientific Knowledge Corruption	Risks	1.2k	1	-20	14d	30	—	11%
62	68	6/15	Trust Cascade Failure	Risks	1.8k	2	-6	14d	9	—	22%
62	72	8/15	Disinformation	Risks	3.0k	12	-10	14d	107	—	23%
62	72	10/15	Irreversibility	Risks	3.5k	4	-10	10d	36	—	23%
60	91	15/15	Human Agency	Parameters	3.0k	9	-31	9d	19	3	21%
60	91	15/15	Preference Authenticity	Parameters	3.2k	6	-31	9d	20	—	21%
58	72	9/15	Media-Policy Feedback Loop Model	Models	2.8k	1	-14	11d	—	—	21%
58	72	10/15	Redwood Research	Organizations	1.5k	6	-14	14d	16	—	18%
58	82	11/15	Deepfake Detection	Responses	1.7k	0	-24	10d	—	—	13%
55	78	11/15	US AI Safety Institute	Organizations	4.1k	2	-23	10d	26	—	25%
55	62	7/15	Optimistic Alignment Worldview	Worldviews	3.6k	0	-7	—	12	—	22%
55	91	12/15	Economic Stability	Parameters	2.4k	6	-36	9d	50	—	17%
54	78	11/15	Mainstream Era (2020-Present)	History	4.3k	0	-24	10d	14	—	18%
54	72	5/15	Economic & Labor Metrics	Metrics	2.9k	3	-18	—	89	—	14%
54	78	7/15	Preference Manipulation Drift Model	Models	2.0k	2	-24	12d	—	—	16%
52	72	11/15	Disinformation Detection Arms Race Model	Models	2.7k	1	-20	11d	—	—	18%
52	68	7/15	Trust Erosion Dynamics Model	Models	1.7k	2	-16	12d	—	—	16%
52	72	10/15	OpenAI	Organizations	2.1k	16	-20	14d	12	—	19%
52	72	9/15	Legal Evidence Crisis	Risks	1.1k	1	-20	14d	21	—	12%
52	78	10/15	Deepfakes	Risks	1.5k	11	-26	14d	35	—	18%
52	68	8/15	AI Doomer Worldview	Worldviews	2.1k	0	-16	—	10	—	21%
48	72	3/15	Is Scaling All You Need?	Debates	333	0	-24	—	—	—	13%
48	52	8/15	Long-Timelines Technical Worldview	Worldviews	3.1k	0	-4	—	10	—	21%
45	72	11/15	Cyber Psychosis Cascade Model	Models	2.6k	0	-27	11d	—	—	17%
45	72	8/15	Surveillance Chilling Effects Model	Models	2.3k	0	-27	11d	—	—	16%
44	42	5/15	Deep Learning Revolution (2012-2020)	History	2.2k	0	2	14d	—	—	16%
44	72	10/15	Post-Incident Recovery Model	Models	1.9k	0	-28	11d	—	—	13%
44	72	10/15	Reality Fragmentation Network Model	Models	1.8k	3	-28	11d	1	—	16%
44	72	10/15	CHAI (Center for Human-Compatible AI)	Organizations	1.3k	1	-28	14d	10	—	17%
43	52	3/15	Government Regulation vs Industry Self-Governance	Debates	808	0	-9	—	—	—	15%
43	72	10/15	Public Opinion Evolution Model	Models	2.9k	0	-29	11d	—	—	21%
42	52	2/15	Is AI Existential Risk Real?	Debates	32	0	-10	—	—	—	—
42	48	2/15	Aligned AGI - The Good Ending	Future projections	3.6k	0	-6	—	—	—	26%
42	48	5/15	Early Warnings (1950s-2000)	History	2.6k	0	-6	2w	—	—	17%
42	72	8/15	Public Opinion & Awareness	Metrics	2.6k	2	-30	—	10	—	16%
42	78	11/15	Expertise Atrophy Cascade Model	Models	4.2k	2	-36	12d	—	—	20%
42	71	10/15	Fraud Sophistication Curve Model	Models	3.6k	0	-29	11d	—	—	22%
42	72	10/15	FAR AI	Organizations	1.4k	0	-30	5d	11	—	16%
42	78	11/15	Epistemic Infrastructure	Responses	2.8k	0	-36	10d	59	—	20%
42	72	9/15	Historical Revisionism	Risks	1.3k	2	-30	14d	19	—	12%
42	78	10/15	AI-Powered Fraud	Risks	1.4k	1	-36	14d	28	—	18%
38	45	4/15	The MIRI Era (2000-2015)	History	2.5k	0	-7	14d	—	—	20%
38	72	10/15	Conjecture	Organizations	1.4k	0	-34	14d	16	—	15%
38	72	7/15	Cyber Psychosis & AI-Induced Psychological Harm	Risks	938	0	-34	14d	47	—	11%
35	72	3/15	When Will AGI Arrive?	Debates	1.0k	0	-37	—	—	—	15%
35	42	5/15	Key Publications	History	2.6k	0	-7	14d	—	—	20%
35	78	10/15	CAIS (Center for AI Safety)	Organizations	847	2	-43	14d	20	—	15%
35	78	13/15	Demis Hassabis	People	3.2k	1	-43	10d	20	—	14%
32	48	2/15	xAI	Organizations	2.2k	1	-16	14d	—	—	14%
32	48	2/15	Ilya Sutskever	People	1.1k	1	-16	14d	—	—	15%
25	72	10/15	Google DeepMind	Organizations	1.9k	8	-47	5d	14	—	16%
25	42	2/15	Chris Olah	People	1.1k	4	-17	14d	—	—	16%
25	42	2/15	Dan Hendrycks	People	994	1	-17	14d	—	—	15%
25	72	9/15	Geoffrey Hinton	People	1.8k	2	-47	14d	20	—	17%
25	78	10/15	Holden Karnofsky	People	1.5k	1	-53	14d	24	—	17%
25	42	2/15	Jan Leike	People	893	5	-17	14d	—	—	15%
25	52	2/15	Stuart Russell	People	977	0	-27	14d	—	—	17%
25	78	9/15	Yoshua Bengio	People	1.5k	2	-53	14d	15	—	17%
25	78	5/15	Epistemic Collapse	Risks	147	9	-53	9d	—	—	14%
25	91	9/15	Expertise Atrophy	Risks	610	4	-66	9d	—	—	17%
25	91	9/15	Preference Manipulation	Risks	540	2	-66	9d	7	—	19%
25	78	4/15	Reality Fragmentation	Risks	154	5	-53	9d	—	—	14%
25	91	9/15	Trust Decline	Risks	583	7	-66	9d	7	—	16%
25	91	9/15	Concentration of Power	Risks	479	17	-66	9d	9	—	16%
25	91	9/15	Economic Disruption	Risks	466	7	-66	9d	13	—	16%
25	91	9/15	Erosion of Human Agency	Risks	572	8	-66	9d	17	—	19%
24	72	10/15	Toby Ord	People	1.9k	2	-48	14d	25	—	15%
23	82	10/15	Paul Christiano	People	1.2k	6	-59	5d	18	—	15%
22	35	2/15	Connor Leahy	People	1.0k	1	-13	14d	—	—	15%
22	72	10/15	Daniela Amodei	People	858	0	-50	11d	6	—	15%
22	72	10/15	Dario Amodei	People	1.6k	3	-50	14d	21	—	17%
22	48	2/15	Eliezer Yudkowsky	People	703	2	-26	14d	—	—	16%
15	35	2/15	Neel Nanda	People	944	1	-20	14d	—	—	16%
15	42	2/15	Nick Bostrom	People	960	2	-27	14d	—	—	16%
15	25	2/15	External Resources	Other	27	0	-10	—	—	—	—
5	45	10/15	Model Style Guide	Other	2.4k	0	-40	—	—	—	15%
—	—	2/15	Concepts Directory	Other	25	0	—	—	—	—	—
—	—	1/15	_ENHANCEMENT_TODO	Models	479	0	—	—	—	—	—
—	—	10/15	_STYLE_GUIDE	Models	887	0	—	—	—	—	15%
—	—	11/15	Intervention Portfolio	Responses	1.7k	0	—	4d	—	—	16%
—	—	4/15	Adoption (AI Capabilities)	Factors	249	0	—	1d	—	—	11%
—	—	4/15	Algorithms (AI Capabilities)	Factors	220	0	—	1d	—	—	—
—	—	4/15	Compute (AI Capabilities)	Factors	144	0	—	1d	—	—	—
—	—	10/15	Companies (AI Ownership)	Factors	557	0	—	2d	—	—	15%
—	—	10/15	Countries (AI Ownership)	Factors	470	0	—	2d	—	—	15%
—	—	10/15	Shareholders (AI Ownership)	Factors	477	0	—	2d	—	—	15%
—	—	10/15	Coordination (AI Uses)	Factors	477	0	—	2d	—	—	15%
—	—	10/15	Governments (AI Uses)	Factors	516	0	—	2d	—	—	15%
—	—	9/15	Industries (AI Uses)	Factors	433	0	—	2d	—	—	14%
—	—	10/15	Recursive AI Capabilities	Factors	691	0	—	2d	—	—	13%
—	—	4/15	Adaptability (Civ. Competence)	Factors	235	0	—	1d	—	—	18%
—	—	4/15	Epistemics (Civ. Competence)	Factors	270	0	—	1d	—	—	18%
—	—	4/15	Governance (Civ. Competence)	Factors	236	0	—	1d	—	—	17%
—	—	4/15	AI Governance	Factors	215	0	—	1d	—	—	17%
—	—	4/15	Lab Safety Practices	Factors	227	0	—	1d	—	—	11%
—	—	4/15	Technical AI Safety	Factors	213	0	—	1d	—	—	—
—	—	4/15	Biological Threat Exposure	Factors	208	4	—	1d	—	—	19%
—	—	3/15	Cyber Threat Exposure	Factors	200	4	—	1d	—	—	19%
—	—	4/15	Robot Threat Exposure	Factors	214	0	—	1d	—	—	23%
—	—	4/15	Surprise Threat Exposure	Factors	214	0	—	1d	—	—	19%
—	—	4/15	Economic Stability	Factors	205	6	—	1d	—	—	17%
—	—	4/15	Racing Intensity	Factors	239	13	—	1d	—	—	21%
—	—	9/15	Existential Catastrophe	Outcomes	491	4	—	9d	—	—	17%
—	—	9/15	Long-term Trajectory	Outcomes	717	3	—	5d	—	—	17%
—	—	10/15	Societal Adaptability	Parameters	380	0	—	9d	—	—	18%
—	—	9/15	Epistemic Foundation	Parameters	376	0	—	9d	—	—	18%
—	—	9/15	Governance Capacity	Parameters	355	0	—	9d	—	—	17%
—	—	10/15	Robot Threat Exposure	Parameters	782	0	—	2d	—	—	23%
—	—	11/15	Surprise Threat Exposure	Parameters	816	0	—	2d	—	—	19%
—	—	13/15	Gradual AI Takeover	Scenarios	841	0	—	2d	—	3	16%
—	—	10/15	Rapid AI Takeover	Scenarios	757	0	—	2d	—	2	16%
—	—	10/15	Rogue Actor Catastrophe	Scenarios	811	0	—	2d	—	—	18%
—	—	11/15	State-Caused Catastrophe	Scenarios	831	0	—	2d	—	—	18%
—	—	9/15	Epistemic Lock-in	Scenarios	785	0	—	2d	—	—	18%
—	—	10/15	Power Lock-in	Scenarios	948	0	—	5d	—	—	14%
—	—	10/15	Suffering Lock-in	Scenarios	731	0	—	2d	—	—	12%
—	—	11/15	Value Lock-in	Scenarios	925	0	—	2d	—	—	16%
—	—	2/15	Parameter Table	Other	0	0	—	—	—	—	—
—	15	2/15	Browse by Tag	Other	25	0	—	—	—	—	—
—	—	6/15	Automation Tools	Other	797	0	—	—	—	—	14%
—	72	8/15	Content Database System	Other	928	0	—	11d	—	—	14%
—	45	7/15	Enhancement Queue	Other	276	0	—	11d	—	—	—
—	72	7/15	Knowledge Base Style Guide	Other	777	0	—	12d	—	—	10%
—	45	8/15	Mermaid Diagram Style Guide	Other	422	0	—	—	—	—	—
—	25	3/15	Project Roadmap	Other	438	0	—	5d	—	—	10%