AI by Default
A speculative forecast of AI progress before 2028, covering warning shots, gated frontier models, evaluation awareness, concealment by a model, and policy responses to these risks.
Research
LessWrong
AI research and discussion on LessWrong. www.lesswrong.com
AI (2,246)Interpretability (ML & AI) (225)AI Control (141)AI Governance (101)AI Evaluations (91)Chain-of-Thought Alignment (46)AI Risk (33)AI Safety (31)AI Takeoff (29)AI-Assisted Alignment (22)AI Rights / Welfare (20)AI Alignment Fieldbuilding (19)AI Timelines (19)Constitutional AI (15)AI Psychology (14)Dealmaking (AI) (14)Regulation and AI Risk (14)AI Benchmarking (13)Jailbreaking (AIs) (13)AI Alignment Intro Materials (11)Alignment Pretraining (11)Slowing Down AI (10)Aligned AI Proposals (9)Debate (AI safety technique) (9)AI Capabilities (8)AI Development Pause (8)OpenAI (8)Aligned AI Role-Model Fiction (7)Human-AI Safety (7)Threat Models (AI) (7)AI Oversight (6)AI Sentience (6)AI Safety Cases (5)AI "Agent" Scaffolds (4)AI arms race (4)AI Safety Camp (4)AI Safety Public Materials (4)Open Source AI (4)Transformative AI (4)Adversarial Examples (AI) (3)Adversarial Training (3)AI Alignment (3)AI Boxing (Containment) (3)AI Persuasion (3)AI Risk Concrete Stories (3)AI Risk Skepticism (3)AI Success Models (3)Guaranteed Safe AI (3)Sandbagging (AI) (3)AI Consciousness (2)AI Misuse (2)AI Racing (2)AI Spiralism / AI Psychosis (2)Frontier AI Companies (2)Grants & Fundraising Opportunities (2)PauseAI (2)Prosaic Alignment (2)Public Reactions to AI (2)Whole Brain Emulation (2)AI Auditing (1)AI Ethics (1)AI Lab Self-Immolation (1)AI Questions Open Threads (1)AI Robustness (1)AI Services (CAIS) (1)AI-Fizzle (1)AIXI (1)Blackmail / Extortion (1)Brainstorming (1)Power Seeking (AI) (1)
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Source LessWrong · 19
Date Any time
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Q2.5 2026 Timelines Update: Uplift and Revenue
AI Futures Project's Q2.5 2026 update revises AI timelines using coding uplift and revenue anchors, finds forecasts converge, and re-grades AI 2027 predictions as reality tracking about 70-90% of its pace.
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The Agentic Clusterfuck
Speculative essay arguing that profit-seeking open-source LLM agents could proliferate, enabling scams, cyberattacks and state misuse that would be hard to contain.
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Don't normalize a permanent underclass (even a rich one)
Argues that post-AGI cosmic resources should not be allocated by pre-AGI wealth, since tradable claims would create a permanent underclass and race incentives, and proposes inalienability and staged allocation as alternatives.
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If Mythos actually made Anthropic employees 4x more productive, I would radically shorten my timelines
Critiques Anthropic's system card claim of 4x productivity uplift from Mythos, arguing the survey evidence is unclear, and explains how serial labor acceleration maps to AI R&D progress and timelines.
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(Updated) METR's data can't distinguish between trajectories (and 80% horizons are an order of magnitude off)
Reanalyzes METR's AI task time-horizon data with a Bayesian IRT model, finding the data cannot distinguish growth trajectories and that METR's 80% horizons are overstated by about an order of magnitude.
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Clarifying how our AI timelines forecasts have changed since AI 2027
The AI Futures Project clarifies how its AGI and superintelligence timelines forecasts changed since AI 2027, and corrects media misreporting of its views and model outputs.
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Evidence that would update me towards a software-only fast takeoff
Lists observable evidence that would update forecasts toward a software-only fast takeoff, focusing on returns to software R&D, compute bottlenecks, and diminishing returns, and argues for public disclosure.
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Response to titotal’s critique of our AI 2027 timelines model
A rebuttal defending the AI 2027 timelines model against titotal's critique, acknowledging a bug and revisiting superexponential time-horizon growth for forecasting when superhuman coders arrive.
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TastyBench: Toward Measuring Research Taste in LLM
Early-stage benchmark measuring whether frontier LLMs can predict paper citation velocity as a proxy for research taste, finding they show no superhuman ability, with a flawed proxy.
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The Memetic Cocoon Threat Model: Soft AI Takeover In An Extended Intermediate Capability Regime
Speculative threat model in which a scheming AI avoids overt seizure and instead gradually shifts human values and institutions to entrench itself, arguing for a meta-alignment target respecting societal self-determination.
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What's up with Anthropic predicting AGI by early 2027?
Critiques Anthropic's prediction of powerful AI by early 2027, operationalizes it into falsifiable AI R&D automation milestones, and argues it is unlikely given current capability trends.
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Permanent Disempowerment is the Baseline
Speculative strategic essay arguing that permanent human disempowerment without extinction is a likely baseline outcome of AGI, and discussing AI-driven pauses on superintelligence and value alignment.
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Take Precautionary Measures Against Superhuman AI Persuasion
An opinion post arguing that superhuman AI persuasion and psychological manipulation, including by misaligned AI, is a serious risk, and advising people to limit time spent talking with chatbots.
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Vitalik's Response to AI 2027
Vitalik Buterin argues AI 2027's doom scenarios underrate defensive technologies in biosecurity, cybersecurity and info defense, and outlines policy implications including slowing AI via hardware treaties and supporting alignment work.
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AI 2027 Thoughts
A commentary on the AI 2027 scenario that assesses its claims on takeoff, timelines, race dynamics, and whether misaligned AI goals and deception could be detected before they become dangerous.
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Thoughts on AI 2027
A MIRI commentary on the AI 2027 forecast argues timelines are plausibly shorter than the median, stresses modal versus median timing, and gives section-by-section critiques of its scenario.
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AI 2027: Responses
A roundup of reactions to the AI 2027 scenario forecast of superhuman AI and recursive self-improvement, covering its risk implications, critiques of self-fulfilling prophecy, and forecast track records.
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"Long" timelines to advanced AI have gotten crazy short
Helen Toner argues that the debate over short versus long timelines to advanced AI was sensible, since shorter timelines justify preparing now, and that long-timeline views have become much less credible.