± HEALTH Large language models (LLMs) are artificial intelligence (AI) tools specifically trained to process and gener…+ HEALTH Background Discharge letters are essential for continuity of care, yet patients often misunderstand their con…± HEALTH Hematoxylin and Eosin (H&E) glass slide preparation is fundamental to histopathology. Pathologists' expertise…+ CLIMATE Traditional soil heavy metal risk assessments suffer from fragmented indices and poor logical integration. Co…± HEALTH Background Neonatal pneumothorax can progress rapidly, yet detection on supine chest radiographs remains chal…+ HEALTH T cell exhaustion has widespread implications for the progression and treatment of chronic diseases including…+ HEALTH Background Standard pulmonary arterial hypertension (PAH) risk models may not fully apply to PAH associated w…+ HEALTH Objectives To map and synthesize the scientific evidence regarding the use of Augmented Reality (AR) and Mixe…
TruaceTracing the truth around AIMonday, September 14, 2026
Subscribe
The Index

What the evidence says.What the public feels.

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

1,404 results
Show filters and sorting

AI gains · 779

67
GainEducation· Stable· Evidence: Moderate (1 source)

Den-SOFA predicted pass/fail on restorative dentistry exit exams with AUC-ROC 0.906 and accuracy 0.86 using 26 academic and demographic variables from 96 students.

On 2026-07-16, a peer-reviewed study described Den-SOFA, an explainable machine learning framework tested as a proof-of-concept to forecast restorative dentistry exit examination outcomes from 26 academic and demographic variables for 96 dental students across five models.

Impact 30%49
Evidence 25%95
Scale 20%35
Confidence 15%87
Recency 10%89

Updated Jul 18, 2026 · TRV-2026-0259

67
GainHealth· Stable· Evidence: Moderate (1 source)

AI-assisted caries annotation increased dental students' diagnostic accuracy, sensitivity, and confidence while reducing interpretation time on panoramic radiographs.

In a study published July 16, 2026, 40 fourth-year dental students interpreted 40 panoramic radiographs first without assistance and then one month later with AI-assisted caries annotation. The radiographs contained multistage lesions verified by bite-wing radiographs, and students recorded lesion location, depth, time, and confidence.

Impact 30%49
Evidence 25%95
Scale 20%35
Confidence 15%87
Recency 10%89

Updated Jul 18, 2026 · TRV-2026-0258

67
GainHealth· Stable· Evidence: Moderate (1 source)

ML and DL analysis of imaging, genetics, and behavioral data can improve early identification and diagnostic accuracy for conditions like depression, bipolar disorder, and schizophrenia.

A June 2026 review in Journal of Affective Disorders Reports surveyed ML and DL methods for early identification, diagnosis, and treatment of mental health illnesses, covering medical imaging, genetic and biomarker analysis, behavioral assessments, and longitudinal risk prediction models.

Impact 30%49
Evidence 25%95
Scale 20%35
Confidence 15%87
Recency 10%89

Updated Jul 17, 2026 · TRV-2026-0255

67
GainPolicy· Stable· Evidence: Moderate (1 source)

VSCS framework enables community members to act as co-researchers and translate local values into technical requirements for AI systems.

On 2026-07-02, a peer-reviewed paper in AI & SOCIETY introduced Value-Sensitive Citizen Science (VSCS), a framework that combines Value-Sensitive Design with citizen science to involve community members as co-researchers in AI development. It uses the Participatory Value-Cognition Taxonomy and extended scenario reasoning to translate local values into technical requirements and embeds governance for lifecycle oversight.

Impact 30%49
Evidence 25%95
Scale 20%35
Confidence 15%87
Recency 10%89

Updated Jul 17, 2026 · TRV-2026-0253

AI problems · 625

55
ProblemSports· Stable· Evidence: Moderate (1 source)

At Wimbledon 2025, the new AI electronic line-judging system failed to spot an out ball hit long by Sonay Kartal.

At Wimbledon in July 2025, organizers replaced 300 human line judges with an artificial intelligence electronic line-judging system. Shortly after deployment, the new system failed to detect that player Sonay Kartal had hit a ball long during a match.

Impact 30%49
Evidence 25%62
Scale 20%35
Confidence 15%62
Recency 10%88

Updated Jul 12, 2026 · TRV-2026-0083

55
ProblemCrime· Stable· Evidence: Moderate (1 source)

Criminals exploiting AI technology to take over mobile, banking and online shopping accounts contributed to a record 444,000 fraud reports to the UK national fraud database last year.

Cifas, the UK's fraud prevention organisation, reported 444,000 fraud cases from its members last year, a 6% rise on 2024 and a record for its national fraud database. The body said criminals are increasingly exploiting AI technology to take over mobile, banking and online shopping accounts, using stolen data to make unauthorised transactions and enabling deception on industrialised levels.

Impact 30%49
Evidence 25%62
Scale 20%35
Confidence 15%62
Recency 10%88

Updated Jul 12, 2026 · TRV-2026-0081

55
ProblemMedia & Arts· Stable· Evidence: Moderate (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%88

Updated Jul 12, 2026 · TRV-2026-0080

55
ProblemMedia & Arts· Stable· Evidence: Moderate (1 source)

Game studios attempting to replace human writers with AI large language models risks losing human storytelling in games.

What happened: the co-creator and lead writer of Zombies, Run! bought back the studio behind the game, transferring funds via phone to a Singapore company, motivated by a belief that human storytelling must be protected as AI tools spread.

Impact 30%49
Evidence 25%62
Scale 20%35
Confidence 15%62
Recency 10%88

Updated Jul 12, 2026 · TRV-2026-0076

Recomputed live from the record · Sep 14, 2026, 4:16 PM