DOOM LEVEL
--
%
Latest Headlines
Auto-Updated
Resources for starting and growing an AI safety org
via LessWrong AI [5] — It seems that AI safety is at least partly bottlenecked by a lack of orgs. To help address that, we’ve added a page to AISafety.com aimed at lowering the friction for starting one: AISafety.com/founders.This page was built largely as the result of a…
LLM Reasoning Is Latent, Not the Chain of Thought
via ArXiv cs.AI [5] — This position paper argues that large language model (LLM) reasoning should be studied as latent-state trajectory formation rather than as faithful surface chain-of-thought (CoT). This matters because claims about faithfulness, interpretability, reasoning…
Reevaluating "AGI Ruin: A List of Lethalities" in 2026
via LessWrong AI [7] — It's been about four years since Eliezer Yudkowsky published AGI Ruin: A List of Lethalities, a 43-point list of reasons the default outcome from building AGI is everyone dying. A week later, Paul Christiano replied with Where I Agree and Disagree with…
Consent-Based RL: Letting Models Endorse Their Own Training Updates
via LessWrong AI [5] — AKA scalable oversight of value driftTL;DR LLMs could be aligned but then corrupted through RL, instrumentally converging on deep consequentialism. If LLMs are sufficiently aligned and can properly oversee their training updates, we they can prevent…
Prompted CoT Early Exit Undermines the Monitoring Benefits of CoT Uncontrollability
via Alignment Forum [999] — Code: github.com/ElleNajt/controllability tldr: Yueh-Han et al. (2026) showed that models have a harder time making their chain of thought follow user instruction compared to controlling their response (the non-thinking, user-facing output). Their CoT…
AI #164: Pre Opus
via Substack Zvi [999] — This is a day late because, given the discourse around Dwarkesh Patel’s interview with Jensen Huang, I pushed the weekly to Friday.
On Dwarkesh Patel's Podcast With Nvidia CEO Jensen Huang
via Substack Zvi [999] — Some podcasts are self-recommending on the ‘yep, I’m going to be breaking this one down’ level.
OpenAI’s big Codex update is a direct shot at Anthropic’s Claude Code
via The Verge AI [4] — OpenAI is beefing up its agentic coding and development system Codex with a suite of updates that let it use your computer, generate images, and remember from past experiences. Codex will now be able to operate desktop apps on your computer, OpenAI says in…
You can only build safe ASI if ASI is globally banned
via Alignment Forum [999] — Sometimes people make various suggestions that we should simply build "safe" artificial Superintelligence (ASI), rather than the presumably "unsafe" kind.[1]There are various flavors of “safe” people suggest.Sometimes they suggest building “aligned”…
Optimizing Earth Observation Satellite Schedules under Unknown Operational Constraints: An Active Constraint Acquisition Approach
via ArXiv cs.AI [4] — Earth Observation (EO) satellite scheduling (deciding which imaging tasks to perform and when) is a well-studied combinatorial optimization problem. Existing methods typically assume that the operational constraint model is fully specified in advance. In…
What is the Iliad Intensive?
via LessWrong AI [9] — Almost two months ago, Iliad announced the Iliad Intensive and Iliad Fellowship. Fellowships are a well-understood unit, but what is an intensive? This post explains this in more detail!Comparison. The Iliad Intensive has similarities to ARENA, but focuses…
Current AIs seem pretty misaligned to me
via Alignment Forum [999] — Many people—especially AI company employees [1] —believe current AI systems are well-aligned in the sense of genuinely trying to do what they're supposed to do (e.g., following their spec or constitution, obeying a reasonable interpretation of…
Claude Code, Codex and Agentic Coding #7: Auto Mode
via Substack Zvi [999] — As we all try to figure out what Mythos means for us down the line, the world of practical agentic coding continues, with the latest array of upgrades.
Diary of a "Doomer": 12+ years arguing about AI risk (part 1)
via LessWrong AI [4] — How I learned about Deep Learning.As far as I know, I’m the second person ever to get into the field of AI largely because I was worried about the risk of human extinction.1In late 2012, while recovering from some minor heartbreak with the help of some…
Redefining the future of software engineering
via MIT Technology Review [4] — Software engineering has experienced two seismic shifts this century. First was the rise of the open source movement, which gradually made code accessible to developers and engineers everywhere. Second, the adoption of development operations…
A Retrospective of Richard Ngo's 2022 List of Conceptual Alignment Projects
via LessWrong AI [8] — Written very quickly for the InkHaven Residency.In 2022, Richard Ngo wrote a list of 26 Conceptual Alignment Research Projects. Now that it’s 2026, I’d like to revisit this list of projects, note which ones have already been done, and give my thoughts on…
Claude Mythos #3: Capabilities and Additions
via Substack Zvi [999] — To round out coverage of Mythos, today covers capabilities other than cyber, and anything else additional not covered by the first two posts, including new reactions and details.
OpeFlo: Automated UX Evaluation via Simulated Human Web Interaction with GUI Grounding
via ArXiv cs.AI [4] — Evaluating web usability typically requires time-consuming user studies and expert reviews, which often limits iteration speed during product development, especially for small teams and agile workflows. We present OpenFlo, a user-experience evaluation agent…
Anthropic repeatedly accidentally trained against the CoT, demonstrating inadequate processes
via Alignment Forum [999] — It turns out that Anthropic accidentally trained against the chain of thought of Claude Mythos Preview in around 8% of training episodes. This is at least the second independent incident in which Anthropic accidentally exposed their model's CoT to the…
Summary: AI Governance to Avoid Extinction
via MIRI [999] — With AI capabilities rapidly increasing, humans appear close to developing AI systems that are better than human experts across all domains. This raises a series of questions about how the world will—and should—respond. In the research paper AI Governance to…
Live Doom Meter
--
%
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
0%25%50%75%100%
Loading estimates...
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