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 · climate-energy · last 180 days
The trend line needs at least two days of readings and there is one so far. It appears on its own once the pipeline has run across a second day. Today's readings are on the axis below.
Discourse valence, window mean
-46
Adverse
1 item · range -46 to -46
-100
-50
0
+50
+100
-46
Adverse readingFavourable reading
1 item scored in this window
167
discovered, all time
57
passed triage
108
rejected at triage
230
model assessments
49
multi-model panels
112
distinct claims tracked
Across the whole window
The two tables below describe every item in the last 180 days under climate-energy. They are deliberately not narrowed by the reading filter, 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 | 28 | -56 | |
| AGI and timelines | structural | 21 | -37 | |
| Loss of control and alignment | risk | 21 | -66 | |
| Governance and regulation | structural | 19 | -20 | |
| Concentration of power | risk | 17 | -37 | |
| Evaluation and measurement | structural | 10 | -22 | |
| Scaling and architecture | structural | 9 | -8 | |
| Cyber capability | risk | 8 | -56 | |
| Human agency and epistemics | risk | 7 | -22 | |
| Synthetic media and manipulation | risk | 6 | -63 | |
| Medicine and health | benefit | 5 | +0 | |
| Biological and chemical uplift | risk | 4 | -20 | |
| Scientific acceleration | benefit | 4 | +17 | |
| Abundance and material wellbeing | benefit | 2 | -8 | |
| Compute and infrastructure | structural | 2 | -13 | |
| Education and access to expertise | benefit | 2 | -37 | |
| Climate and energy | structural | 1 | -46 | |
| Employment and displacement | risk | 1 | -5 | |
| Productivity and growth | benefit | 1 | -26 |
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 | 9 | -55 |
| Financial Times: Artificial Intelligence | news | 1 | 8 | -53 |
| arXiv cs.CY (Computers and Society) | academic | 1 | 8 | -26 |
| The New York Times: Technology | news | 1 | 7 | -31 |
| BBC News: Technology | news | 1 | 6 | -36 |
| Ars Technica: AI | news | 1 | 5 | -73 |
| OpenAI | lab | 1 | 3 | -17 |
| IEEE Spectrum: AI | news | 1 | 3 | +2 |
| MIT Technology Review: AI | news | 1 | 2 | -50 |
| arXiv cs.AI | academic | 1 | 2 | -8 |
| The Economist: Science and Technology | news | 1 | 1 | -16 |
| Google DeepMind | lab | 1 | 1 | +7 |
| CSET, Georgetown | government | 1 | 1 | -22 |
| arXiv cs.LG (Machine Learning) | academic | 1 | 1 | +4 |