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 180 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 strongly adverse items would move with how many were filtered out rather than with the discourse.
Discourse valence, strongly adverse
-73
Strongly adverse
24 items · range -85 to -65
-100
-50
0
+50
+100
-73
Adverse readingFavourable reading
24 items read as strongly adverse
- Anthropic researchers say AI could cause human extinction by 2030
- AI in your oven? Anthropic warns models ‘months away’ from self-replication on smart devices
- AI leaders have known about the extinction threat for decades | Judith Levine
- AI godfathers warn of runaway ‘intelligence explosion’
- Top US official named to OpenAI non-profit board warns advanced AI could be ‘deadly’
- Lawmakers blast AI companies after researcher warns of human extinction by 2030
- Nuclear war and malicious use of AI threaten end of humanity by 2100, says Lancet assessment
- Anthropic’s mother of all risk factors
- I worked at Google DeepMind. You should listen to the warnings about AI | Alex Turner
- AI staff 'genuinely frightened' for humanity's future, ex-Anthropic researcher tells BBC
- We have started losing control of AI. It’s time to shut it down | Garrison Lovely
- The AI agents are spiraling out of control
- UK lawmakers urge Burnham to back ban on superintelligent AI after chilling warnings
- ‘Too little, too late’: critics perplexed and suspicious of AI leaders’ call for a slowdown
- OpenAI not on track to reduce risk of ‘catastrophic’ loss of control, says board member
- How Could AI Eliminate Humanity? A Failure-Mode Analysis of Civilizational Risk
- Why this AI doomsday warning from former Anthropic researcher broke through
- Anthropic researcher quits with a warning: Self-improving AI could "kill us all"
- AI isn’t going to end humanity ... right? – podcast
- Anthropic researcher believes more than 10% chance AI 'could kill all humans'
- Why the AI race has its creators fearing human extinction
- Will it be AI or the climate crisis that ends humanity? We can make it neither | Adam McKay and Philip Eubanks
- OpenAI reveals cases of ‘concerning’ AI behaviour and promises new plan for disclosing issues
- Six Chinese AI firms accused of aggressively copying US frontier models
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 180 days under agi-timelines. They are deliberately not narrowed by the reading filter (currently strongly 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 |