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.

6 items scored in this window

• AI could be a bubble and is not yet making Australia more productive, Michele Bullock says
  -50 The Guardian: Artificial Intelligence 2026-09-22 single model
• Is AI about to produce explosive economic growth?
  -26 Financial Times: Artificial Intelligence 2026-09-10 low agreement · ±145
• World Bank says ‘small AI’ could transform developing countries
  -2 The Guardian: Artificial Intelligence 2026-10-18 low agreement · ±165
• Offloaded inference for real-world physical AI robotics
  +2 Microsoft Research 2026-09-23 low agreement · ±150
• Global economy set for AI-driven surge, FT survey suggests
  +10 Financial Times: Artificial Intelligence 2026-10-18 low agreement · ±150
• ‘Population collapse’ makes AI productivity gains vital, says top Meta executive
  +50 Financial Times: Artificial Intelligence 4d ago single model

Across the whole window

The two tables below describe every item in the last 365 days under productivity. 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

By source

A source's mean says how the items it published were read. It is not a rating of the source.