Discourse monitor
How the monitored publications were assessed
Discourse valence across every scored item: what the sampled sources published and how independent models read it. It is not a measure of public opinion, not a measure of the state of the world, and article volume is not agreement.
Mean discourse valence per day · agi-timelines · last 365 days
This line is the mean of every item scored on each day. It deliberately ignores the reading filter, because a daily mean of only the adverse items would move with how many were filtered out rather than with the discourse.
Discourse valence, adverse
-40
Adverse
59 items · range -63 to -20
-100
-50
0
+50
+100
-40
Adverse readingFavourable reading
59 items read as adverse
- MoFlow: Multi-Objective Agentic Workflow Generation
- Progressive Misalignment Can Emerge from Benign Recursive Self-Distillation
- How would AI actually ‘kill all humans’? Here are the top five most likely scenarios | Toby Walsh
- OpenAI boss and Elon Musk back calls to put brakes on ‘reckless’ AI development
- Halt super-intelligent AI with non-proliferation treaty, Ed Davey to say
- Anthropic IPO warns its AI could blackmail people, become sentient, end humanity
- Why a decade of doomsday warnings failed to slow the AI race
- Microsoft says AI rival Anthropic could have 'disastrous impact' on humanity
- More Anthropic researchers warn of AI’s perils as Musk terms fears a ‘psyop’
- Anthropic Researchers Raise Alarm Over A.I. Acceleration, Warning of Threat to Humanity
- AI’s mathematics blitz pushes science into strange new territory
- OpenAI claims to have solved hundreds of long-standing maths problems
- How should investors position for the robot apocalypse?
- AI must not outrun safety controls, DeepMind co-founder warns
- Adapting the Process of Adaptation: Darwinian, Lamarckian, and Agent-Directed Evolution in AI
- Could A.I. Really Kill All Humans?
- Will the real Anthropic please stand up
- Harness^2: Recursive Agent Harnessing for an Open World
- Inside the Discussions at AI Companies Over a Superintelligence Doomsday
- Stronger artificial intelligence breakthroughs hasten their own exhaustion
- AI CEOs say they need to slow the pace of development. But will they?
- Could AI really end humanity?
- Visualizing the World Model in an Agent's Value Function
- China’s AI labs must accelerate development, says Huawei chair
- The Big Threat Has Been Climate Change. Now Comes A.I.
- Could AI really end humanity? Post your questions for our tech reporters now
- Feeling overwhelmed by the AI doom loop? Here’s the essential reading list to make sense of it all
- When Reality Outpaces Cognition: A New Scaling Principle for Reliable Intelligence
- Roundtables: Could AI really kill us all?
- AI will make it possible to design and build organisms from scratch
- A.I. Agents: Cute, Cuddly and Maybe Catastrophically Dangerous?
- Elon Musk Says SpaceX and Tesla Are Exploring a Merger
- Open-world AI: a Tale of Three Requirements
- Artificiality's First Exam: An LLM-Referenced C-test for Supraintelligence
- What Anthropic CEO Dario Amodei Argued in His Call for AI Slowdown
- AI companies want to become frontier scientific researchers
- What if automating AI R&D triggers an intelligence explosion?
- AI will transform capitalism – but how?
- How to think about the end of the world
- Space as an Interventional Invariant: Cross-Modal Predictive Geometry for Stratified Cities and Em-Spaced Intelligence
- Introducing GPT-6 Sol and Luna
- More Australians will be dying than being born in 40 years as major report predicts future of lower growth
- Is Universal Basic Income the Answer to A.I.-Fueled Job Losses?
- Can a System-One LLM Perform Knowledge Tracing When Few or No Learners Are Logged?
- Risk Ceilings and Development Deadlines: Pacing AI under Uncertain Safety Productivity
- Is AI about to produce explosive economic growth?
- Zuckerberg says Meta has reached AI ‘frontier’ and rejects calls for slowdown
- Self-discovering RL in the Era of Experience: Is Learning History an Asset or a Burden?
- Who’s Who In The Fight Over Whether AI Will Kill Us
- Is Claude Conscious? Inside Anthropic’s Quest to Instill Morality Into Its A.I. Models
- Artificial intelligence now beats some of the best human forecasters
- Will China deploy humanoid robots to fight?
- Calls for AI slowdown send shockwaves through Washington
- Big tech says AI can find a cure for cancer. So where is it?
- Why are there concerns AI could threaten humanity, and how real are they?
- How to spend $25 billion on science: OpenAI’s staggeringly rich research charity gets under way
- Will AI really kill us all? The science behind the hype
- Anthropic’s IPO S-1 Spells Out a Future of Promise and Peril
- Don’t be fooled by this summer of AI hype
3560
discovered, all time
984
passed triage
2574
rejected at triage
3464
model assessments
710
multi-model panels
1780
distinct claims tracked
Across the whole window
The two tables below describe every item in the last 365 days under agi-timelines. They are deliberately not narrowed by the reading filter (currently adverse), because a mean taken only over items already selected for their score would just restate the filter.
By topic
| Topic | Branch | Items | Mean | Position |
|---|---|---|---|---|
| Existential and catastrophic risk | risk | 568 | -42 | |
| Governance and regulation | structural | 459 | -31 | |
| Concentration of power | risk | 451 | -36 | |
| Loss of control and alignment | risk | 337 | -49 | |
| Human agency and epistemics | risk | 166 | -26 | |
| Cyber capability | risk | 165 | -44 | |
| Evaluation and measurement | structural | 159 | -19 | |
| Scaling and architecture | structural | 137 | -16 | |
| AGI and timelines | structural | 132 | -29 | |
| Synthetic media and manipulation | risk | 104 | -44 | |
| Employment and displacement | risk | 62 | -31 | |
| Medicine and health | benefit | 43 | -14 | |
| Scientific acceleration | benefit | 42 | -4 | |
| Education and access to expertise | benefit | 29 | -17 | |
| Biological and chemical uplift | risk | 26 | -25 | |
| Climate and energy | structural | 20 | -33 | |
| Compute and infrastructure | structural | 18 | -8 | |
| Productivity and growth | benefit | 6 | -3 | |
| Abundance and material wellbeing | benefit | 5 | -1 | |
| Hype and disillusionment | structural | 5 | -45 |
By source
A source's mean says how the items it published were read. It is not a rating of the source.
| Source | Kind | Tier | Items | Mean |
|---|---|---|---|---|
| The Guardian: Artificial Intelligence | news | 1 | 241 | -52 |
| arXiv cs.CY (Computers and Society) | academic | 1 | 217 | -24 |
| Financial Times: Artificial Intelligence | news | 1 | 112 | -40 |
| arXiv cs.AI | academic | 1 | 99 | -15 |
| The New York Times: Technology | news | 1 | 60 | -36 |
| Ars Technica: AI | news | 1 | 59 | -51 |
| MIT Technology Review: AI | news | 1 | 34 | -42 |
| Nature | academic | 1 | 31 | -25 |
| BBC News: Technology | news | 1 | 29 | -35 |
| OpenAI | lab | 1 | 24 | -8 |
| arXiv cs.LG (Machine Learning) | academic | 1 | 24 | -16 |
| IEEE Spectrum: AI | news | 1 | 19 | -19 |
| The Economist: Science and Technology | news | 1 | 10 | -37 |
| CSET, Georgetown | government | 1 | 9 | -37 |
| Microsoft Research | lab | 1 | 8 | 0 |
| Google DeepMind | lab | 1 | 6 | -4 |
| Google AI Blog | lab | 1 | 2 | -9 |