DOOM LEVEL
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Google’s AI architect lived rent-free in Elon Musk’s head
via The Verge AI [4] — About a week into the Musk v. Altman trial, we've heard from some of the most powerful people in tech - including OpenAI president Greg Brockman, Elon Musk's fixer Jared Birchall, and Musk himself. But one of the most prominent characters is hovering…
Understanding Emergent Misalignment via Feature Superposition Geometry
via ArXiv cs.AI [6] — Emergent misalignment, where fine-tuning on narrow, non-harmful tasks induces harmful behaviors, poses a key challenge for AI safety in LLMs. Despite growing empirical evidence, its underlying mechanism remains unclear. To uncover the reason behind this…
OpenAI and PwC collaborate to reimagine the office of the CFO
via OpenAI Blog [6] — OpenAI and PwC are partnering to help enterprises use AI agents to automate finance workflows, improve forecasting, strengthen controls, and modernize the CFO function.
Housing Roundup #15: The War Against Renters
via Substack Zvi [999] — So many are under the strange belief that there is something terrible about not owning the house in which you live.
The creator of Roomba is back with a furry robot companion
via The Verge AI [4] — Colin Angle, the maker of the Roomba and the man who helped put 50 million household robots into people's homes, is back with a new robot. But this one is designed as a companion, not a cleaner. The first robot from Angle's new company, Familiar Machines &…
AI Industrial Takeoff — Part 1: Maximum growth rates with current technology
via LessWrong AI [4] — How fast could an AI-driven economy grow? Most economists expect a few percentage points at best, comparable to previous general-purpose technologies (Acemoglu (2024)). Those closer to AI development tend to imagine something much more radical (Shulman…
Tailoring AI solutions for health care needs
via MIT Technology Review [4] — The AI market is full of big promises of grand transformation. Health care is a prime target for those promises, beset as it is by financial pressures, labor shortages, and the growing burden of caring for an aging population. AI developers are…
TUR-DPO: Topology- and Uncertainty-Aware Direct Preference Optimization
via ArXiv cs.AI [9] — Aligning large language models (LLMs) with human preferences is commonly done via reinforcement learning from human feedback (RLHF) with Proximal Policy Optimization (PPO) or, more simply, via Direct Preference Optimization (DPO). While DPO is stable and…
Minimal, Local, Causal Explanations for Jailbreak Success in Large Language Models
via ArXiv cs.AI [5] — Safety trained large language models (LLMs) can often be induced to answer harmful requests through jailbreak prompts. Because we lack a robust understanding of why LLMs are susceptible to jailbreaks, future frontier models operating more autonomously in…
OpenAI's red line for AI self-improvement is fundamentally flawed
via LessWrong AI [4] — TL;DR. OpenAI's "Critical" threshold for AI self-improvement in the Preparedness Framework v2 has three structural problems:It fires too late. The lagging indicator, 5× generational acceleration sustained for several months, lets ~3 years of effective…
Exploration Hacking: Can LLMs Learn to Resist RL Training?
via Alignment Forum [999] — We empirically investigate exploration hacking (EH) — where models strategically alter their exploration to resist RL training — by creating model organisms that resist capability elicitation, evaluating countermeasures, and auditing frontier models…
Risk from fitness-seeking AIs: mechanisms and mitigations
via Alignment Forum [999] — Current AIs routinely take unintended actions to score well on tasks: hardcoding test cases, training on the test set, downplaying issues, etc. This misalignment is still somewhat incoherent, but it increasingly resembles what I call…
Housing Roundup #14: You Can't Build That
via Substack Zvi [999] — Why can’t you build it?
AI unemployment and AI extinction are often the same
via LessWrong AI [10] — My sense is that people think of AI existential risk and AI unemployment as distinct issues. Some people are extremely concerned about extinction and perhaps even indifferent to total unemployment. Some people think of moderate AI unemployment as a…
Pentagon strikes classified AI deals with OpenAI, Google, and Nvidia — but not Anthropic
via The Verge AI [4] — The Pentagon has struck deals with OpenAI, Google, Microsoft, Amazon, Nvidia, Elon Musk's xAI, and the startup Reflection, allowing the agency to use their AI tools in classified settings, according to an announcement on Friday. At the same time, the…
Microsoft wants lawyers to trust its new AI agent in Word documents
via The Verge AI [4] — Microsoft is launching a new AI agent inside Word that's specifically designed for legal teams. Legal Agent handles document edits, negotiation history, and complex documents to help legal teams handle tasks like reviewing contracts. "Instead of relying on…
AI risk was not invented by AI CEOs to hype their companies
via LessWrong AI [9] — I hear that many people believe that the idea of advanced AI threatening human existence was invented by AI CEOs to hype their products. I’ve even been condescendingly informed of this, as if I am the one at risk of naively accepting AI companies’…
Binary Spiking Neural Networks as Causal Models
via ArXiv cs.AI [4] — We provide a causal analysis of Binary Spiking Neural Networks (BSNNs) to explain their behavior. We formally define a BSNN and represent its spiking activity as a binary causal model. Thanks to this causal representation, we are able to explain the output…
This startup’s new mechanistic interpretability tool lets you debug LLMs
via MIT Technology Review [8] — The San Francisco–based startup Goodfire just released a new tool, called Silico, that lets researchers and engineers peer inside an AI model and adjust its parameters—the settings that determine a model’s behavior—during training. This could give…
AI #166: Google Sells Out
via Substack Zvi [999] — This was the week of GPT-5.5.
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