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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

753
EducationStableModerate evidence · 1 source

Three elementary students with dyslexia improved from low baseline reading comprehension to mastery and maintained gains after GenAI-based visual instruction using ChatGPT-generated visuals aligned to their Arabic coursebook.

In a 2026 single-case study in Yanbu, Saudi Arabia, three male elementary students aged 9-11 with dyslexia received GenAI-based visual instruction using ChatGPT-generated visual explanations aligned to their Grade 4 Arabic coursebook. After starting at 0%-10% on comprehension quizzes, they reached 80% or higher across three consecutive sessions and sustained that level in maintenance probes weeks later.

Impact 30%
49
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
83

Updated Jul 14, 2026 · TRV-2026-0220

67Index score
754
HealthStableModerate evidence · 1 source

Machine learning-derived metabolic age from urinary NMR metabolites tracks longitudinal aging trajectories and predicts incident diseases and mortality beyond chronological age.

Researchers developed a biological age score from urinary metabolites measured by high-resolution 1H NMR using machine learning in a large population cohort, then tracked its trajectory over more than a decade and tested its links to aging-related phenotypes and future health events.

Impact 30%
49
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
83

Updated Jul 14, 2026 · TRV-2026-0219

67Index score
755
HealthStableModerate evidence · 1 source

AI reduces unwanted variability in structured pattern recognition tasks such as imaging analysis, improving diagnostic consistency and mitigating noise-driven errors.

A 2026 narrative review and conceptual analysis in Diagnosis synthesized literature on noise in medical decision-making, AI applications in healthcare, and clinical reasoning, reviewing case studies in radiology and pathology and empirical data on AI performance.

Impact 30%
49
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
83

Updated Jul 14, 2026 · TRV-2026-0218

67Index score
756
ScienceStableModerate evidence · 1 source

Protecting weights important for previous tasks enables deep neural networks to be trained sequentially and achieve state-of-the-art results on multiple reinforcement learning problems experienced sequentially.

On March 14, 2017, authors in PNAS described a method to overcome catastrophic forgetting in deep neural networks. They noted that while deep networks were the most successful technique for translation, image classification and generation, they could not learn multiple tasks sequentially. Their solution protects weights important for previous tasks, inspired by synaptic consolidation.

Impact 30%
49
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
83

Updated Jul 13, 2026 · TRV-2026-0210

67Index score

AI problems · 770

753
Media & ArtsStableModerate evidence · 1 source

Routine on-set digital scanning that captures actors' likeness for future use enables AI systems to reuse their image without ongoing consent or control.

On 18 December 2025, The Guardian reported that UK actors in Equity voted 99% to refuse to be digitally scanned while on set, aiming to prevent their likeness being used by artificial intelligence. The union's general secretary Paul Fleming called artificial intelligence a generation-defining challenge for Equity's film members.

Impact 30%
49
Evidence 25%
62
Scale 20%
35
Confidence 15%
62
Recency 10%
83

Updated Jul 12, 2026 · TRV-2026-0080

55Index score
754
CrimeStableModerate evidence · 1 source

A Claude chatbot subscriber was billed $400 for two unauthorized $200 gift card purchases for the AI tool

David Duggan subscribed to the Claude chatbot for $20 a month to answer medical questions and organise family life. His wife later noticed two $200 charges on his credit card bill for gift cards to use the AI tool that he said he had not bought. When he contacted Anthropic his account was suspended and he received computer-generated responses that did not clarify what happened.

Impact 30%
49
Evidence 25%
62
Scale 20%
35
Confidence 15%
62
Recency 10%
83

Updated Jul 12, 2026 · TRV-2026-0074

55Index score
755
LaborStableModerate evidence · 1 source

University students in Great Britain expect AI to displace jobs so quickly that it could lead to civil unrest and a downturn worse than a normal recession

King's College London surveyed university students in Great Britain about AI use and economic expectations. The poll found heavy adoption among students and widespread pessimism about employment impacts, with one in three linking rapid job losses to potential civil unrest.

Impact 30%
49
Evidence 25%
62
Scale 20%
35
Confidence 15%
62
Recency 10%
83

Updated Jul 12, 2026 · TRV-2026-0073

55Index score
756
LaborStableModerate evidence · 1 source

US workers experienced layoffs in 2025 where employers attributed job cuts to artificial intelligence replacing human roles

In the past year US corporate leaders have explained workforce reductions by saying artificial intelligence made operations more efficient and eliminated the need for certain positions. A December report from Challenger, Gray & Christmas counted more than 54,000 layoffs in 2025 where AI was given as the reason, and the pattern was described as alleged AI-washing.

Impact 30%
49
Evidence 25%
62
Scale 20%
35
Confidence 15%
62
Recency 10%
83

Updated Jul 12, 2026 · TRV-2026-0071

55Index score

Recomputed live from the record · Oct 11, 2026, 11:29 AM