Sensitivity and network position
- Rank
- 75of 250
- Sensitivity
- 7.5rank 161
- Breadth
- 0of 20 scenarios High or above
- PageRank
- 41.3rank 79
- Eigenvector
- 29.6
- Betweenness
- 28.6
- Links
- 13trends at Moderate similarity or above
- Composite
- 26.8
Attention over three years
How much this trend is read about on Wikipedia and searched for on Google, week by week, set against the typical trend in the list so that what moves every trend at once is taken out. 100 is this trend's own three-year average. The score measures public attention, which is not the same as the strength of the force: a trend can deepen unnoticed, and a news event can lift attention for a fortnight.
- Now
- 144
- Over a year
- −5%Steady
- Over three years
- +144%
- Peak
- 27028 Sept 2025
- Sources
- Bothagreement 0.26
- Coverage
- 5languages · 50 nations
Trailing 4-week average. 100 is this trend’s three-year average.
By language
Wikipedia reading in each language edition where the trend’s pages are read enough to measure (5 of 28). Share is of all the readers counted.
| Language | Share | Now | Over a year | Three years |
|---|---|---|---|---|
| English | 78% | 105 | −4% | |
| Russian | 12% | 105 | −2% | |
| Arabic | 6% | 80 | −66% | |
| Spanish | 3% | 128 | +16% | |
| Portuguese | 1% | 107 | −6% |
By country
Google search interest over the three years, as a share of each country’s searching. 100 is the nation where interest is highest. The search terms are English, which favours countries that search in English.
Singapore
South Korea
United States
Australia
Netherlands
Canada
United Arab Emirates
Taiwan
United Kingdom
India
Japan
New Zealand
100
96
40
35
34
27
26
25
24
23
23
23
The 12 highest of 50 nations with a reading.
By region and G20 member
Attention to this trend inside each place, from Google searches made in its countries and Wikipedia reading in the languages mostly read there, averaged where both exist. Each line compares the trend with its own past in that place; the lines do not compare places.
Regions
| Place | Read from | Now | 90 days | 1 year | 3 years | Three years |
|---|---|---|---|---|---|---|
| North America | Google in 2 countries + Wikipedia in English | 117 | −19% | −16% | +115% | |
| Europe | Google in 4 countries | 156 | −31% | +159% | +300% | |
| Indo-Pacific | Google in 5 countries | 171 | −33% | +157% | +342% | |
| South Asia | Google in 2 countries | 183 | −30% | +83% | +796% | |
| Gulf and Middle East | Google in 1 country + Wikipedia in Arabic | 71 | +20% | −62% | −40% | |
| Africa | Google in 1 country | 105 | −52% | −7% | 0% | |
| Latin America and Caribbean | Google in 2 countries + Wikipedia in Spanish, Portuguese | 129 | −29% | +55% | +157% | |
| Russia and Eurasia | Google in 1 country + Wikipedia in Russian | 144 | +21% | +158% | +12% |
G20 members
| Place | Read from | Now | 90 days | 1 year | 3 years | Three years |
|---|---|---|---|---|---|---|
| Australia | 162 | −40% | +114% | +453% | ||
| Brazil | Google + Wikipedia in Portuguese | 124 | −35% | +72% | +144% | |
| Canada | 148 | −34% | +60% | +330% | ||
| Germany | 195 | −42% | +567% | +1931% | ||
| India | 167 | −33% | +65% | +534% | ||
| Indonesia | 207 | −17% | +401% | +469% | ||
| Italy | 96 | −30% | −7% | +13% | ||
| Japan | 179 | −56% | +702% | +1074% | ||
| Mexico | 136 | −32% | +56% | +620% | ||
| Russia | Wikipedia in Russian | 105 | +7% | −2% | +9% | |
| South Africa | 105 | −52% | −7% | 0% | ||
| Türkiye | 62 | +46% | −55% | −57% | ||
| United Kingdom | 207 | +1% | +144% | +515% | ||
| United States | Google + Wikipedia in English | 114 | −19% | −26% | +115% |
Relation to each scenario
A trend relates to a scenario when it changes how likely the scenario is, how hard it lands, or is itself sharply changed by it. Each score is the median of three scores given separately by the members of the model panel.
| Relation | Scenario | Family |
|---|---|---|
| 3 · Moderate | An AI deployment step causes abrupt labour displacement S08 | Technology and infrastructure |
| 3 · Moderate | A public service platform reaches inclusive operation S18 ↗ | Technology and infrastructure |
| 1 · Very low | A cryptographic breakthrough invalidates digital trust S09 | Technology and infrastructure |
| 1 · Very low | A novel respiratory pathogen exceeds health surge capacity S10 | Health |
| 1 · Very low | AI-directed research produces a reproducible discovery step S17 ↗ | Technology and infrastructure |
| 0 · Not related | Critical trade divides into rival blocs S01 | Economic and trade |
| 0 · Not related | A global funding seizure reaches sovereign balance sheets S02 | Economic and trade |
| 0 · Not related | A regional war closes a globally important sea route S03 | Geopolitical and security |
| 0 · Not related | Hybrid coercion ends in an infrastructure blackout S04 | Geopolitical and security |
| 0 · Not related | A disputed transfer of power breaks effective government S05 | Geopolitical and security |
| 0 · Not related | Two breadbasket failures trigger a food availability crisis S06 | Energy, climate and resources |
| 0 · Not related | A major disaster disables the national economic core S07 | Energy, climate and resources |
| 0 · Not related | A creditor agreement releases fiscal capacity S11 ↗ | Economic and trade |
| 0 · Not related | A cross-regional market access compact redirects investment S12 ↗ | Economic and trade |
| 0 · Not related | A great-power agreement lowers economic security barriers S13 ↗ | Geopolitical and security |
| 0 · Not related | A verified Middle East settlement restores access S14 ↗ | Geopolitical and security |
| 0 · Not related | Cheap firm clean power becomes available at scale S15 ↗ | Energy, climate and resources |
| 0 · Not related | A validated farming package raises water-efficient output S16 ↗ | Energy, climate and resources |
| 0 · Not related | Affordable preventive treatments reduce chronic illness S19 ↗ | Health |
| 0 · Not related | A live outbreak proves rapid distributed pandemic defence S20 ↗ | Health |
Related trends
Similarity = 0.3 × shared tags (Jaccard) + 0.3 × likeness of scenario profiles (cosine) + 0.3 × likeness of names and descriptions (TF-IDF cosine) + 0.1 if in the same capability domain, cut into seven levels at 0.12, 0.22, 0.33, 0.45, 0.58, 0.72. Shown at Moderate and above.
| Similarity | Trend | Theme | Rank |
|---|---|---|---|
| 5 · Very high | AI safety & governance | State capacity & governance | 69 |
| 4 · High | Official statistics & data capacity | State capacity & governance | 21 |
| 4 · High | Digital public infrastructure | State capacity & governance | 31 |
| 4 · High | Adaptive regulation | State capacity & governance | 33 |
| 4 · High | Data protection & digital rights | State capacity & governance | 44 |
| 4 · High | Algorithmic accountability & bias | State capacity & governance | 135 |
| 3 · Moderate | Civil service capability & pay | State capacity & governance | 2 |
| 3 · Moderate | Public procurement capability | State capacity & governance | 6 |
| 3 · Moderate | Regulatory capture & lobbying power | State capacity & governance | 8 |
| 3 · Moderate | Illicit finance & beneficial ownership | State capacity & governance | 20 |
| 3 · Moderate | Citizen participation & deliberative democracy | State capacity & governance | 60 |
| 3 · Moderate | Digital language representation gaps | Information & trust | 193 |
| 3 · Moderate | Biometric identification | State capacity & governance | 213 |