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.

Window
30 days90 days180 days365 days
Reading
All readings Strongly adverseAdverseMixed or uncertainFavourableStrongly favourable
Topic
All topics Existential and catastrophic riskConcentration of powerGovernance and regulationLoss of control and alignmentAGI and timelinesCyber capabilityEvaluation and measurementHuman agency and epistemicsScaling and architectureSynthetic media and manipulation
Range
Mean discourse valence per day · power-concentration · last 180 days
-100-500+50+100 2026-09-10: -24 (6 items)2026-09-11: -5 (6 items) 2026-09-10 2026-09-11

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
-39
Adverse
9 items · range -55 to -20
Adverse readingFavourable reading
Mean across the 9 items matching this filter under power-concentration in the last 180 days.

9 items read as adverse

206
discovered, all time
64
passed triage
140
rejected at triage
256
model assessments
55
multi-model panels
126
distinct claims tracked

Across the whole window

The two tables below describe every item in the last 180 days under power-concentration. 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

TopicBranchItemsMeanPosition
Existential and catastrophic risk risk 32 -50
Concentration of power risk 23 -28
Governance and regulation structural 22 -20
Loss of control and alignment risk 22 -63
AGI and timelines structural 21 -37
Cyber capability risk 10 -45
Evaluation and measurement structural 10 -22
Human agency and epistemics risk 9 -17
Scaling and architecture structural 9 -8
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
Education and access to expertise benefit 3 -24
Abundance and material wellbeing benefit 2 -8
Climate and energy structural 2 -6
Compute and infrastructure structural 2 -13
Employment and displacement risk 2 -4
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.

SourceKindTierItemsMean
arXiv cs.CY (Computers and Society)academic114-20
The Guardian: Artificial Intelligencenews19-55
Financial Times: Artificial Intelligencenews18-53
The New York Times: Technologynews17-31
BBC News: Technologynews16-36
Ars Technica: AInews15-73
OpenAIlab13-17
IEEE Spectrum: AInews13+2
arXiv cs.AIacademic13+6
MIT Technology Review: AInews12-50
The Economist: Science and Technologynews11-16
Google DeepMindlab11+7
CSET, Georgetowngovernment11-22
arXiv cs.LG (Machine Learning)academic11+4