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The Index recomputed live from the record

What the evidence says.What the public feels.

The record holds 932 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.

932 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.

1,702 results
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AI gains · 932

73
ScienceStableModerate evidence · 1 source

The integrated ACME framework increased ship fuel consumption prediction accuracy and generalisation, outperforming mainstream models and providing data-driven tools for energy efficiency management and decarbonisation in maritime transport.

By April 2026, researchers had developed and tested an integrated framework combining advanced optimisation with adaptive ensemble learning for ship fuel consumption prediction. The system fused noon reports, AIS, and meteorological and oceanographic reanalysis data, applied SHAP-weighted feature selection and hierarchical parameter search, and used cluster-based multi-ensemble learning to adapt to different operational conditions.

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

Updated Jul 13, 2026 · TRV-2026-0150

77Index score
74
CrimeStableModerate evidence · 1 source

Open-source MCP servers demonstrated strong health metrics despite rapid adoption with SDK downloads surpassing twenty five million per week.

In a first large-scale empirical study published May 2026, researchers examined 1,899 open-source Model Context Protocol servers, the standard introduced by Anthropic in late 2024 to unify tool calling for Foundation Models. Using health metrics and a combined general and MCP-specific scanner, they measured adoption signals and code quality across the ecosystem.

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

Updated Jul 13, 2026 · TRV-2026-0137

77Index score
75
HealthStableModerate evidence · 1 source

A Random Forest model trained on linguistic, emotional, cognitive, behavioral and temporal features from Weibo posts predicted Self-Rating Anxiety Scale scores among consenting Chinese college students with R2 0.77 on the test set.

Researchers surveyed college students in China with the Self-Rating Anxiety Scale and, with informed consent, analyzed their public Weibo posts. Using multi-dimensional features, a Random Forest model predicted anxiety scores within the study sample, achieving the best test performance among four models tested.

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

Updated Jul 13, 2026 · TRV-2026-0121

77Index score
76
HealthStableHigh evidence · 5 sources

AI-enabled hierarchical medical system increased hypertension control target achievement from 68% to 82% and achieved health data accuracy exceeding 95% for chronic disease patients.

Researchers assessed an AI-driven hierarchical medical system for chronic disease management in China using 2024 National Health Commission monitoring data and 12,468 patient follow-up records from three provinces, structured around data collection, decision intervention, resource scheduling, and outcome feedback.

Impact 30%
69
Evidence 25%
100
Scale 20%
35
Confidence 15%
100
Recency 10%
84

Updated Jul 20, 2026 · TRV-2026-0328

76Index score

AI problems · 770

73
HealthNewly addedModerate evidence · 1 source

AI implementation in pharmaceutical industry functions introduces important risks and practical implementation challenges requiring human oversight.

Published October 1, 2026, this ACCP commentary surveys how artificial intelligence is being applied across the pharmaceutical life cycle and what that means for industry-based clinical pharmacists in development, regulatory, medical affairs, HEOR, and pharmacovigilance.

Impact 30%
49
Evidence 25%
95
Scale 20%
60
Confidence 15%
87
Recency 10%
98

Updated Oct 2, 2026 · TRV-2026-1246

73Index score
74
Media & ArtsNewly addedModerate evidence · 1 source

AI developers training large language models on copyrighted works without permission or compensation risks exploiting creative labor and privileging Big Tech profit over creator rights.

A peer-reviewed paper published 18 September 2025 examines whether developers of large language models should be allowed to train on copyrighted works without permission and compensation to rightsholders, focusing on the UK. It frames the issue as a contest between an imaginary centered on market-driven growth of generative AI and one centered on equity.

Impact 30%
49
Evidence 25%
95
Scale 20%
60
Confidence 15%
87
Recency 10%
98

Updated Oct 1, 2026 · TRV-2026-1240

73Index score
75
PolicyNewly addedModerate evidence · 1 source

Same hydro-climatic models failed to capture multi-year effective capacity loss from sedimentation when benchmarked against bathymetric surveys, producing relative errors up to 292% and systematic bias in droughts.

By September 2026, a peer-reviewed study tested monthly hydro-climatic machine learning forecasts of effective storage at Mingde and Shihmen reservoirs in Taiwan, comparing linear regularized regression and a nonlinear tree-based model against observed storage and multi-year bathymetric capacity changes.

Impact 30%
63
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
98

Updated Sep 30, 2026 · TRV-2026-1217

73Index score
76
Media & ArtsNewly addedModerate evidence · 1 source

Use of GenAI for automated news in journalism creates ethical problems including lack of verification of automated news and embedded biases.

A peer-reviewed study published October 24, 2025 examined GenAI in journalism through a survey of 324 journalists and interviews with AI-ethics leads at ten Spanish media outlets, focusing on problems, challenges, and measures for responsible use in newsrooms.

Impact 30%
49
Evidence 25%
95
Scale 20%
60
Confidence 15%
87
Recency 10%
97

Updated Sep 27, 2026 · TRV-2026-1204

73Index score

Recomputed live from the record · Oct 11, 2026, 7:57 AM