DOOM LEVEL
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Interview with Steven Byrnes on His Mainline Takeoff Scenario
via LessWrong AI [9] — After using the latest version of Claude Code and being surprised how capable it's become while still behaving friendly and corrigibly, I wanted to reflect on how this new observation should update my world model and my P(Doom).So I reached out to Dr.…
The case for satiating cheaply-satisfied AI preferences
via Alignment Forum [999] — A central AI safety concern is that AIs will develop unintended preferences and undermine human control to achieve them. But some unintended preferences are cheap to satisfy, and failing to satisfy them needlessly turns a cooperative situation into an…
Meta acquires Moltbook, the Reddit-like network for AI agents
via The Verge AI [4] — Meta is acquiring Moltbook, a Reddit-like platform where AI agents can make and comment on posts, as first reported by Axios. In a statement to The Verge, Meta spokesperson Matthew Tye confirmed the Moltbook team will join Meta Superintelligence Labs as…
The case for AI safety capacity-building work
via LessWrong AI [7] — TL;DR:I think many of the marginal hires at larger organizations doing AI safety technical or policy work right now (including e.g. Apollo, Redwood, METR, RAND TASP, GovAI, Epoch, UKAISI, and Anthropic’s safety teams) would be capable of founding (or being…
Best-of-Tails: Bridging Optimism and Pessimism in Inference-Time Alignment
via ArXiv cs.AI [5] — Inference-time alignment effectively steers large language models (LLMs) by generating multiple candidates from a reference model and selecting among them with an imperfect reward model. However, current strategies face a fundamental dilemma: ``optimistic''…
Autonomous AI Agents for Option Hedging: Enhancing Financial Stability through Shortfall Aware Reinforcement Learning
via ArXiv cs.AI [3] — The deployment of autonomous AI agents in derivatives markets has widened a practical gap between static model calibration and realized hedging outcomes. We introduce two reinforcement learning frameworks, a novel Replication Learning of Option Pricing…
Employees across OpenAI and Google support Anthropic’s lawsuit against the Pentagon
via The Verge AI [4] — On Monday, Anthropic filed its lawsuit against the Department of Defense over being designated as a supply chain risk. Hours later, nearly 40 employees from OpenAI and Google - including Jeff Dean, Google's chief scientist and Gemini lead - filed an amicus…
Claude Code, Claude Cowork and Codex #5
via Substack Zvi [999] — It feels good to get back to some of the fun stuff.
Censored LLMs as a Natural Testbed for Secret Knowledge Elicitation
via Alignment Forum [999] — TL;DR: We introduce a testbed based on censored Chinese LLMs, which serve as natural objects of study for studying secret elicitation techniques. Then we study the efficacy of honesty elicitation and lie detection techniques for detecting and removing…
From games to biology and beyond: 10 years of AlphaGo’s impact
via DeepMind Blog [4] — Ten years since AlphaGo, we explore how it is catalyzing scientific discovery and paving a path to AGI.
Promoting enmity and bad vibes around AI safety
via LessWrong AI [9] — I've observed some people engaged in activities that I believe are promoting enmity in the course of their efforts to raise awareness about AI risk. To be frank, I think those activities are increasing AI risk, including but not limited to extinction risk.…
Evolving Medical Imaging Agents via Experience-driven Self-skill Discovery
via ArXiv cs.AI [5] — Clinical image interpretation is inherently multi-step and tool-centric: clinicians iteratively combine visual evidence with patient context, quantify findings, and refine their decisions through a sequence of specialized procedures. While LLM-based agents…
Real-Time AI Service Economy: A Framework for Agentic Computing Across the Continuum
via ArXiv cs.AI [3] — Real-time AI services increasingly operate across the device-edge-cloud continuum, where autonomous AI agents generate latency-sensitive workloads, orchestrate multi-stage processing pipelines, and compete for shared resources under policy and governance…
Payorian cooperation is easy with Kripke frames
via LessWrong AI [3] — The context is MIRI's twist on Axelrod's Prisoner's Dilemma tournament. Axelrod's competitors were programs, facing each other in an iterated Prisoner's Dilemma. MIRI's tournament is a one-shot Prisoner's Dilemma, but the programs get to read their…
Can governments quickly and cheaply slow AI training?
via Alignment Forum [999] — I originally wrote this as a private doc for people working in the field - it's not super polished, or optimized for a broad audience.But I'm publishing anyway because inference-verification is a new and exciting area, and there few birds-eye-view…
Your Causal Variables Are Irreducibly Subjective
via LessWrong AI [7] — Mechanistic interpretability needs its own shoe leather era. Reproducing the labeling process will matter more than reproducing the Github. And who can blame us? Causal inference comes with an impressive toolkit: directed acyclic graphs, potential…
Mox is the largest AI Safety community space in San Francisco. We're fundraising!
via LessWrong AI [5] — Summary: Mox is fundraising to maintain and grow AIS projects, build a compelling membership, and foster other impactful and delightful work. We're looking to raise $450k for 2026, and you can donate on Manifund!OverviewWho we areMox is SF’s largest AI…
Thoughts on the Pause AI protest
via LessWrong AI [4] — On Saturday (Feb 28, 2026) I attended my first ever protest. It was jointly organized by PauseAI, Pull the Plug and a handful of other groups I forget. I have mixed feelings about it. To be clear about where I stand: I believe that AI labs are worryingly…
Anthropic Officially, Arbitrarily and Capriciously Designated a Supply Chain Risk
via Substack Zvi [999] — Make no mistake about what is happening.
The Elect
via LessWrong AI — I was different in Michael’s prison than I was outside, looking the way I did when we fell in love so long ago, in that time before we could change our forms. Stuck in some body that was not of my choosing? Does that seem strange to you? It was not like that…
Live Doom Meter
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0% — We're fine
100% — GG
The Doom Meter is a composite score derived from prediction markets and feed sentiment, updated daily.
70%
Prediction Markets
Weighted average of Manifold Markets questions on AI catastrophe, AGI timelines, expert surveys, and key figures. Direct doom indicators weighted higher than indirect capability markers.
30%
Feed Sentiment
Percentage of recent headlines containing high-alarm keywords (existential risk, catastrophe, extinction). Higher alarm density = higher score.
This is not a scientific estimate of existential risk. It is an opinionated, transparent signal — a vibes-based thermometer for AI doom discourse.
P(Doom) Scoreboard
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Recent Voices
We are creating something that will be more powerful than us. I don't know a good precedent for a less intelligent thing managing a more intelligent thing.
— Geoffrey Hinton, Nobel Prize Lecture, Dec 2024
If you're not worried about AI safety, you're not paying attention.
— Sen. Blumenthal, Senate AI Hearing, 2024
The probability of doom is high enough that we should be working very hard to reduce it.
— Yoshua Bengio, MILA Talk, 2024