TruaceTracing the truth around AITuesday, September 15, 2026
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
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AI gains · 779

68
GainHealth· Stable· Evidence: Moderate (1 source)

Young people with mental health difficulties developed platform literacy, including data and algorithm literacies, to critically examine platforms and take anticipatory and remedial action against risky features.

By June 2025, a qualitative study reported that young people with mental health difficulties experienced extreme online risks amplified by platforms promoting trending and viral content and by personalised recommendations that could trigger individual vulnerabilities, prompting hypervigilant coping efforts.

Impact 30%49
Evidence 25%95
Scale 20%35
Confidence 15%87
Recency 10%90

Updated Jul 22, 2026 · TRV-2026-0512

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

A supervised fine-tuned Baichuan2-7B-Chat model trained on 45,338 prostate cancer lifestyle QA samples outperformed its base model and performed comparably or better than GPT-3.5-Turbo across diet, activity, weight, adherence, and psychological support scenarios in dual-round blinded LLM referee evaluation.

Researchers developed PCaPLMM_SFT, a Baichuan2-7B-Chat model fine-tuned for prostate cancer lifestyle management, using a knowledge base built from 2211 PubMed articles and over 150,000 knowledge slices covering diet, physical activity, weight, medication adherence, and psychological support. They generated 42,330 single-turn and 3008 multiturn QA pairs and evaluated the model against GPT-3.5-Turbo and the base model.

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

Updated Jul 22, 2026 · TRV-2026-0509

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

Final-year medical students using an AI virtual patient with nine emergency medicine scenarios showed significant improvement in overall OSCE outcomes in the small MEET cohort and reported higher confidence in history-taking, differential diagnosis, and management planning.

In a 2026 proof-of-concept pilot, final-year medical students used an AI virtual patient offering nine emergency medicine scenarios with AI-driven dialogue, speech recognition, and avatar interaction plus immediate feedback. Two cohorts completed pre- and postintervention OSCEs scored on communication, history and examination, management, and overall outcome, with surveys and focus groups for qualitative insight.

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

Updated Jul 22, 2026 · TRV-2026-0507

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

AI and large language models have matured to improve clinicians' diagnostic decision-making during bedside and clinic consultations and help institutions increase diagnostic safety, addressing preventable diagnostic errors.

A July 2026 narrative review in Diagnosis examined whether artificial intelligence and large language models can reduce diagnostic error in bedside and clinic consultations. It summarized evidence that diagnostic errors affect 5-10% of admissions and visits and contribute to patient harm and hospital mortality.

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

Updated Jul 22, 2026 · TRV-2026-0506

AI problems · 625

61
ProblemHealth· Stable· Evidence: Moderate (1 source)

An FDA malfunction report described the Linq II insertable cardiac monitor's AI algorithm rejecting true pause episodes and generating false ventricular tachycardia detections, with no complications reported to date.

The FDA received a malfunction report for the Linq ii insertable cardiac monitor made by Medtronic singapore operations. According to the report, the device's AI algorithm rejected true pause episodes as false and detected false ventricular tachycardia episodes. The monitor remains implanted and in use, and the report states no patient complications have been reported as a result of this event.

Impact 30%49
Evidence 25%85
Scale 20%35
Confidence 15%62
Recency 10%88

Updated Jul 12, 2026 · TRV-2026-0039

60
ProblemLabor· Stable· Evidence: Moderate (1 source)

Women represent only 26% of AI hires, indicating a systemic design flaw in how AI roles are filled and retained, with little compensation-linked accountability for closing the gap.

In August 2026, Forbes reported on new LinkedIn data showing women account for just 26% of AI hires. The article characterizes the disparity as a design flaw in hiring and retention systems rather than a simple talent shortage.

Impact 30%63
Evidence 25%62
Scale 20%35
Confidence 15%62
Recency 10%96

Updated Aug 27, 2026 · TRV-2026-0901

60
ProblemLabor· Stable· Evidence: Moderate (1 source)

Companies began citing AI in layoffs and recent graduates faced 5.6% unemployment, with AI identified as a possible contributing factor.

A year after predictions that AI would wipe out half of entry-level white-collar jobs, a Guardian report on 12 August 2026 cites a Stanford Institute for Economic Policy Research analysis finding no major displacement since 2022, with the most AI-exposed workers seeing a 0.77 point unemployment rise versus 0.85 for the least-exposed.

Impact 30%63
Evidence 25%62
Scale 20%35
Confidence 15%62
Recency 10%94

Updated Aug 13, 2026 · TRV-2026-0740

60
ProblemMedia & Arts· Stable· Evidence: Moderate (1 source)

Sony's second lawsuit alleges AI music generator Udio infringed 30,117 recordings and seeks to defeat a fair-use defence by pointing to licensing deals struck by rival AI firms.

On 2026-07-21, Sony filed a second lawsuit against AI music generator Udio, alleging infringement of 30,117 recordings. The complaint reportedly leverages licensing deals obtained by rival AI music companies to argue against Udio's fair-use defence.

Impact 30%49
Evidence 25%62
Scale 20%60
Confidence 15%62
Recency 10%89

Updated Jul 22, 2026 · TRV-2026-0504

Recomputed live from the record · Sep 15, 2026, 4:07 AM