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The Index recomputed live from the record

What the evidence says.What the public feels.

The record holds 933 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.

933 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.

1,703 results
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AI gains · 933

181
ClimateStableModerate evidence · 1 source

Respondents reported that AI can lower municipal waste management costs and improve sorting, recycling, and collection routing.

A peer-reviewed study published October 4, 2025 examined AI for municipal waste management in Industry 4.0. Based on a 2024 online survey of 78 respondents mainly from Europe with experience or interest in AI, logistics, and ecology, authors reported that 78% saw AI reducing waste management costs, 59% saw greatest benefits in sorting and recycling, and 51% saw effectiveness in optimizing collection routes.

Impact 30%
49
Evidence 25%
95
Scale 20%
60
Confidence 15%
87
Recency 10%
86

Updated Jul 29, 2026 · TRV-2026-0585

72Index score
182
HealthStableModerate evidence · 1 source

Federated learning allows hospitals and health systems to train shared models without centralizing patient data, supporting real-time IoT and wearable monitoring for predictive analytics and personalized care.

This peer-reviewed review from December 2024 examines federated learning as a decentralized approach for smart healthcare, where institutions collaborate on machine learning without sharing raw patient data, integrated with IoT devices, wearables, and remote monitoring for real-time predictive analytics.

Impact 30%
49
Evidence 25%
95
Scale 20%
60
Confidence 15%
87
Recency 10%
85

Updated Jul 24, 2026 · TRV-2026-0550

72Index score
183
PolicyStableModerate evidence · 1 source

AI is being applied to support development and assimilation of financial regulation under China's new supervisory structure led by the NFRA.

Published April 28, 2025, the peer-reviewed article describes China's recent overhaul of financial supervision, centered on the new National Financial Regulatory Administration covering all financial sectors except securities and expanded PBOC oversight of financial holding corporations, alongside new rules for generative AI, deep synthesis, and algorithm recommendations.

Impact 30%
49
Evidence 25%
95
Scale 20%
60
Confidence 15%
87
Recency 10%
85

Updated Jul 24, 2026 · TRV-2026-0535

72Index score
184
BusinessStableModerate evidence · 1 source

Integration of AI, big data, blockchain, VR and IoT into digital tourism platforms can improve personalized travel experiences, operational efficiency, and eco-conscious travel options.

This peer-reviewed paper from April 2025 analyzes how digital tourism platforms integrate Industry 4.0 technologies including AI, big data, blockchain, VR and IoT. It builds a five-dimension conceptual framework covering market power, AI-driven automation and workforce change, innovation and inclusion, sustainability innovations, and data security and governance, linking these to SDGs.

Impact 30%
49
Evidence 25%
95
Scale 20%
60
Confidence 15%
87
Recency 10%
85

Updated Jul 24, 2026 · TRV-2026-0531

72Index score

AI problems · 770

181
ScienceNewly addedModerate evidence · 1 source

Current AI synthesis tools face limits from poor data quality, laboratory variability, underreported negative results, and black-box failure modes that require calibrated reliance and plausibility checks.

By September 2026, this peer-reviewed synthesis review found AI in organic chemistry shifting from isolated demonstrations to a deployable toolkit covering design, retrosynthesis planning, condition optimization, and spectroscopic verification, organized as assistant, analyst, and emerging researcher levels.

Impact 30%
49
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
98

Updated Sep 30, 2026 · TRV-2026-1216

68Index score
182
HealthNewly addedModerate evidence · 1 source

Standard evaluation that counts error frequencies fails to reflect differing clinical severity of error types, leaving regulatory risk requirements incompletely implemented and real-world clinical impact inadequately assessed.

Researchers propose weighted balanced accuracy (WBAn) to evaluate multiclass machine learning models used in medical devices, aiming to align model assessment with regulatory risk management. They demonstrate the metric using X-ray based detection of lung diseases as a reference scenario.

Impact 30%
49
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
98

Updated Sep 30, 2026 · TRV-2026-1215

68Index score
183
EducationNewly addedModerate evidence · 1 source

In the same student sample, AI was also perceived as hindering originality, with concerns about over-reliance, declining critical thinking, and reduced authenticity and credibility.

A peer-reviewed study published October 16, 2025 surveyed 94 university-level art and design students across Pakistan about AI adoption. It found growing use of Midjourney, Adobe Firefly, and ChatGPT primarily for idea generation and style exploration, with 89.36% perceiving AI as enhancing originality and 79.79% viewing AI use in design education positively.

Impact 30%
49
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
97

Updated Sep 28, 2026 · TRV-2026-1208

68Index score
184
HealthStableModerate evidence · 1 source

ChatGPT-5 unnecessarily expanded prophylactic indications in 4 scenarios and disagreed with guidelines in 3 scenarios involving immunocompromised patients, creating educational risk for inappropriate antibiotic prescribing.

A descriptive study from September 2026 evaluated ChatGPT-5 on 17 endodontic antibiotic prophylaxis scenarios based on AHA, AAE, and ADA guidelines. An experienced endodontist rated each response, finding full agreement in 10 cases, partial agreement in 4, and disagreement in 3, with stronger performance on infective endocarditis prophylaxis and antibiotic selection, dosage, and timing.

Impact 30%
49
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
97

Updated Sep 27, 2026 · TRV-2026-1200

68Index score

Recomputed live from the record · Oct 11, 2026, 10:40 PM