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The Index recomputed live from the record

What the evidence says.What the public feels.

The record holds 939 sourced gains and 772 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.

939 gains
772 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.

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AI gains · 939

581
HealthStableModerate evidence · 1 source

A preoperative model using Evans index, tumor-fourth ventricle relationship, and preoperative CSF diversion status achieved good external discrimination for postoperative hydrocephalus after posterior fossa tumor resection.

Investigators developed and externally validated a machine learning model to stratify risk of postoperative hydrocephalus after posterior fossa tumor resection using data from 1,073 patients treated at five tertiary centers from 2013 to 2024. After screening 30 variables, they built a three-variable preoperative model using Evans index, tumor-fourth ventricle relationship, and preoperative CSF diversion status, with SVM showing AUC 0.877 in the external cohort.

Impact 30%
49
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
86

Updated Jul 31, 2026 · TRV-2026-0600

67Index score
582
HealthStableModerate evidence · 1 source

Survey-weighted Explainable Boosting Machine achieved strong temporal stability for severe tooth loss prediction on US BRFSS cohorts, supporting transparent population-level risk stratification.

Researchers developed a TRIPOD+AI-compliant, survey-weighted MICE-EBM framework to predict severe tooth loss defined as six or more missing teeth using US representative data. The model was derived on BRFSS 2022 with 433,772 adults, temporally validated on BRFSS 2024 with 448,213 adults, and tested for cross-survey generalizability on NHANES 2015-2018 with 10,775 adults.

Impact 30%
49
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
86

Updated Jul 31, 2026 · TRV-2026-0597

67Index score
583
HealthStableModerate evidence · 1 source

A two-stage CNN pipeline using Faster R-CNN with EfficientNet-B7 detected dental implants on panoramic radiographs and classified brand and prosthetic platform size with high accuracy, supporting faster and more standardized clinical workflows when records are missing.

Researchers developed and validated a two-stage convolutional neural network pipeline to detect dental implants on panoramic radiographs and classify them by brand and prosthetic platform size. Using 387 radiographs with 1004 implants, the Faster R-CNN with EfficientNet-B7 backbone achieved 99.45% detection accuracy and 85.60% combined brand-and-platform accuracy across 25 partitions.

Impact 30%
49
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
85

Updated Jul 30, 2026 · TRV-2026-0595

67Index score
584
HealthStableModerate evidence · 1 source

A machine learning-derived methionine metabolism-related risk score stratified colorectal cancer patients into high- and low-risk groups with significantly different overall survival in training and external validation cohorts.

By July 28, 2026, researchers reported a systematic machine learning analysis of methionine metabolism in colorectal cancer, using TCGA-COAD for training and two GEO cohorts for external validation. Unsupervised clustering defined metabolism-high and metabolism-low subtypes, and a StepCox plus plsRcox model termed MMRS was built from 41 subtype-associated prognostic genes to stratify patients by risk.

Impact 30%
49
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
85

Updated Jul 30, 2026 · TRV-2026-0593

67Index score

AI problems · 772

581
PolicyNewly addedModerate evidence · 1 source

AI image generators were used to create and widely circulate a fake compromising image of an elected mayor, contributing to election disinformation and reinforcing gendered stereotypes about women in leadership.

On September 30, 2026, The Guardian reported a viral AI-generated fake image depicting College Park, Georgia mayor Bianca Motley Broom kissing a man who was not her husband in a bar, which spread widely on Facebook before being identified as false. The piece connects the incident to other recent political image manipulations and cites polling showing broad public worry about AI deepfakes influencing elections.

Impact 30%
49
Evidence 25%
62
Scale 20%
60
Confidence 15%
62
Recency 10%
98

Updated Oct 1, 2026 · TRV-2026-1225

61Index score
582
Media & ArtsStableModerate evidence · 1 source

Jeffrey Katzenberg is optimistic about artificial intelligence transforming the film industry and enhancing storytelling techniques.

Jeffrey Katzenberg is optimistic about artificial intelligence transforming the film industry and enhancing storytelling techniques. He points out that AI can help lower production costs and break down obstacles in filmmaking, potentially leading to a surge in film production and more creativity in narratives.

Impact 30%
49
Evidence 25%
62
Scale 20%
60
Confidence 15%
62
Recency 10%
96

Updated Sep 24, 2026 · TRV-2026-1181

61Index score
583
Media & ArtsStableModerate evidence · 1 source

We’ve compiled an essential reading list of smart books that explain and critique the AI industry; books that, while flawed, illustrate key viewpoints in the AI debates; and a few books that provide deeper political and social context, including some works of speculative fiction.

Have you been feeling trapped in an endless cycle of artificial intelligence hype and panic? It’s a chaotic time to make sense of the industry that’s reshaping our lives, whether or not we like it.

Impact 30%
49
Evidence 25%
62
Scale 20%
60
Confidence 15%
62
Recency 10%
95

Updated Sep 19, 2026 · TRV-2026-1136

61Index score
584
CrimeStableModerate evidence · 1 source

AI models described as a potent cyber weapon are raising cybersecurity concerns that are feeding calls to slow frontier AI development.

On September 14, 2026, CNBC reported on comments from Cohere's CEO calling AI models the most potent cyber weapon ever created, with the supplied text noting cybersecurity concerns feeding a broader AI safety debate and calls to slow frontier development.

Impact 30%
49
Evidence 25%
62
Scale 20%
60
Confidence 15%
62
Recency 10%
95

Updated Sep 18, 2026 · TRV-2026-1126

61Index score

Recomputed live from the record · Oct 13, 2026, 11:30 PM