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The Index recomputed live from the record

What the evidence says.What the public feels.

The record holds 929 sourced gains and 770 sourced problems, averaging 68 and 66 on the index score. Readers have logged 22 public signals on the Pulse, which is kept apart and never counted as evidence.

929 gains
770 problems
Every sourced claim in the Index, one square each, shaded by the strength of its evidence. High Moderate Emerging

Ranks distinct AI gain and problem claims from the published record. Scores reward impact, independent source strength, scale, confidence, and recency.

1,699 results
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AI gains · 929

49
ClimateStableModerate evidence · 1 source

Gradient-boosted machine learning predicted carbapenem MICs from resistance gene profiles with strong performance for imipenem and ertapenem, supporting AMR surveillance.

A One-Health study analyzed 30,554 E. coli whole-genome sequences from human, animal and environmental sources across 126 countries from 2000 to 2025, using AMRFinderPlus and MLST to map resistance genes and clones, and applied gradient-boosted machine learning to predict MICs from gene profiles and chromosomal features.

Impact 30%
49
Evidence 25%
95
Scale 20%
85
Confidence 15%
87
Recency 10%
86

Updated Jul 29, 2026 · TRV-2026-0584

77Index score
50
EducationStableModerate evidence · 1 source

Universities are developing ethical-use guidelines, authentic assessments, and training programs that enhance teaching and learning and foster GAI literacy.

Published December 19, 2024, this peer-reviewed study analyzed generative AI adoption policies and guidelines from 40 universities across six global regions through the lens of Diffusion of Innovations Theory. It examined how institutions frame compatibility, trialability, observability, communication channels, and roles and responsibilities.

Impact 30%
49
Evidence 25%
95
Scale 20%
85
Confidence 15%
87
Recency 10%
85

Updated Jul 24, 2026 · TRV-2026-0549

77Index score
51
ClimateStableModerate evidence · 1 source

Aurora foundation model outperforms operational forecasts for air quality, ocean waves, tropical cyclone tracks and high-resolution weather while running at orders of magnitude lower computational cost.

On May 21, 2025, a Nature peer-reviewed paper introduced Aurora, a large-scale foundation model trained on more than one million hours of diverse geophysical data. The authors report it outperforms operational forecasts for air quality, ocean wave dynamics, tropical cyclone tracks and high-resolution weather at orders of magnitude lower computational cost.

Impact 30%
49
Evidence 25%
95
Scale 20%
85
Confidence 15%
87
Recency 10%
85

Updated Jul 24, 2026 · TRV-2026-0528

77Index score
52
BusinessStableModerate evidence · 1 source

Integration of sensor networks with AI and ML platforms enables real-time monitoring and predictive analytics for disease outbreaks and yield forecasting, allowing targeted irrigation, fertilization and pest management that optimizes resource use and improves sustainable farming efficiency.

A peer-reviewed review published May 14 2025 examined the integration of smart sensors and IoT in precision agriculture, detailing how soil and plant stress sensors provide real-time data that is analyzed via AI and ML on IoT platforms for remote monitoring and automated control.

Impact 30%
49
Evidence 25%
95
Scale 20%
85
Confidence 15%
87
Recency 10%
85

Updated Jul 24, 2026 · TRV-2026-0527

77Index score

AI problems · 770

49
HealthStableModerate evidence · 1 source

Most AI hypertension studies remain retrospective or internally validated, with few demonstrating external validation or gains in hard outcomes like cardiovascular events or mortality, plus barriers of bias, interpretability, and infrastructure.

A structured narrative review of literature from January 2015 to December 2025 examined AI for hypertension screening, diagnosis, risk stratification, treatment optimization and remote monitoring. It found ML models often outperformed conventional risk scores with AUCs of 0.75 to 0.90 and showed promise for personalized therapy and continuous monitoring.

Impact 30%
49
Evidence 25%
95
Scale 20%
85
Confidence 15%
87
Recency 10%
84

Updated Jul 19, 2026 · TRV-2026-0269

77Index score
50
LifestyleStableModerate evidence · 1 source

Widespread use of synthetic AI companions risks emotional over-reliance, distorted expectations for human interaction, privacy harms, and altered norms of intimacy.

This review examines generative AI-enabled synthetic relationships, defined as ongoing associations with AI companions designed to simulate human-like bonds, as a potential intervention for loneliness where traditional approaches face availability and scalability limits.

Impact 30%
49
Evidence 25%
95
Scale 20%
85
Confidence 15%
87
Recency 10%
84

Updated Jul 17, 2026 · TRV-2026-0254

77Index score
51
PolicyStableModerate evidence · 1 source

The same Chinese and South Korean regulatory models for AI journalism face contrasting trade-offs between regulatory efficiency and editorial independence.

This comparative study analyzed China and South Korea's distinct approaches to governing AI journalism and algorithmic news curation, examining policy documents and evidence from Toutiao and Naver to assess how each balances fairness and accountability.

Impact 30%
49
Evidence 25%
95
Scale 20%
85
Confidence 15%
87
Recency 10%
84

Updated Jul 17, 2026 · TRV-2026-0247

77Index score
52
HealthStableModerate evidence · 1 source

AI-assisted retinal analysis faces implementation hurdles including lack of multicenter validation, need for prospective clinical trials, and unresolved data fusion and regulatory requirements.

A May 2026 review in Graefe's Archive describes AI combined with multimodal retinal imaging as a non-invasive approach to detect and monitor systemic vascular and neurodegenerative conditions. It outlines how fundus photography, OCT, OCTA and metabolic-sensitive imaging capture retinal vascular and nerve changes that reflect cardiovascular, metabolic and neurological disease, analyzed with deep learning and multimodal fusion.

Impact 30%
49
Evidence 25%
95
Scale 20%
85
Confidence 15%
87
Recency 10%
83

Updated Jul 13, 2026 · TRV-2026-0192

77Index score

Recomputed live from the record · Oct 11, 2026, 5:13 AM