+ BUSINESS Abstract This study presents a comprehensive literature review using a systematic approach to explore the rol…+ SCIENCE This study investigates the impact of a novel application of generative artificial intelligence (AI) in physi…− HEALTH The rapid integration of artificial intelligence (AI) into everyday life has created new intersections among…+ HEALTH Introduction Stereotactic Radiotherapy plays a main role in Brain Metastases treatment. Radiomics and Dosiomi…+ HEALTH Background Internet Gaming Disorder (IGD) poses significant psychological and social risks for adolescents. I…± HEALTH Background Major depressive disorder (MDD) is associated with high relapse rates, with around 20% of inpatien…± HEALTH Despite a decade in, immunotherapy (IO) treatment selection in non-small cell lung cancer (NSCLC) remains lar…+ HEALTH Rib fractures are a common type of chest injury, and the estimation of the fracture age mainly relies on clin…
TruaceTracing the truth around AITuesday, September 15, 2026
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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.

1,419 results
Show filters and sorting

AI gains · 788

71
GainCrime· Stable· Evidence: High (5 sources)

AI-based defense automates anomaly detection, data analysis and incident response to improve protection efficiency in cyberspace.

By April 2026, a peer-reviewed analysis described AI's growing dual role in cyberspace, where it automates anomaly detection, data analysis and incident response to enhance protection, while also enabling cybercriminals to build advanced phishing, deepfakes and hard-to-detect malware.

Impact 30%49
Evidence 25%100
Scale 20%35
Confidence 15%100
Recency 10%88

Updated Jul 13, 2026 · TRV-2026-0199

71
GainLabor· Stable· Evidence: High (5 sources)

Employees who use approach-oriented AI job crafting to expand job boundaries and enhance capabilities report higher career satisfaction and performance through increased work meaningfulness.

A peer-reviewed study published March 24, 2026 tested how employees proactively adapt to generative AI at work. Using surveys of 287 employee-leader dyads in China, the authors distinguished approach-oriented AI job crafting aimed at leveraging AI to expand job boundaries from avoidance-oriented crafting aimed at mitigating negative perceptions of AI.

Impact 30%49
Evidence 25%100
Scale 20%35
Confidence 15%100
Recency 10%88

Updated Jul 13, 2026 · TRV-2026-0177

71
GainClimate· Stable· Evidence: High (5 sources)

AI readiness was associated with improved national sustainability performance across G20 economies from 2015-2023, with the strongest effect among the three technologies studied.

A peer-reviewed study in Sustainability examined FinTech, AI, and Blockchain adoption across G20 countries between 2015 and 2023 to assess links to Sustainable Development Goal outcomes. Using panel methods and macro controls, it found each technology positively associated with national sustainability performance, with AI showing the strongest effect and coordinated use amplifying gains.

Impact 30%49
Evidence 25%100
Scale 20%35
Confidence 15%100
Recency 10%88

Updated Jul 13, 2026 · TRV-2026-0171

71
GainScience· Stable· Evidence: High (5 sources)

AI systems offer potential for greater efficiency when creating sustainable product designs.

By July 2026, researchers reported a series of studies showing that when products were described as designed by AI, consumers rated them as less sustainable than when the same products were described as designed by humans, despite AI's efficiency potential.

Impact 30%49
Evidence 25%100
Scale 20%35
Confidence 15%100
Recency 10%88

Updated Jul 13, 2026 · TRV-2026-0140

AI problems · 631

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

AI auto-contouring raises concerns that future radiation therapy practitioners may have reduced ability to critically evaluate auto-generated contours.

This peer-reviewed educational perspective from August 2026 examined how organ-at-risk contouring is taught in an Australian undergraduate radiation therapy program as AI auto-contouring enters clinical workflows. The authors reviewed curriculum scope and technologies and examined students' preferred methods, confidence across OARs, and perceived factors affecting quality.

Impact 30%49
Evidence 25%95
Scale 20%35
Confidence 15%87
Recency 10%96

Updated Aug 24, 2026 · TRV-2026-0863

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

The TyG-FI showed limited incremental predictive advantage over FI-Lab alone and reduced discrimination on external validation, with AUROCs dropping to 0.694 and 0.667 in eICU compared to 0.764 and 0.769 internally.

Researchers derived and tested the triglyceride-glucose frailty index in 2230 MIMIC-IV adults with KDIGO-defined AKI, examining associations with ICU, in-hospital, 28-day, 90-day and 365-day mortality, identifying two consensus phenotypes, and evaluating 12 prediction algorithms with SHAP and LIME interpretation and external validation in 1831 eICU patients.

Impact 30%49
Evidence 25%95
Scale 20%35
Confidence 15%87
Recency 10%96

Updated Aug 24, 2026 · TRV-2026-0862

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

Sentinel-2 and CART-based operational AGB mapping in Pinus brutia produced total estimates that differed by more than 700,000 Mg across the same 13,687 ha area depending solely on which allometric reference was used, making reference selection a dominant source of uncertainty.

On 2026-08-22, a peer-reviewed study reported testing how three different allometric reference datasets affect Sentinel-2-based aboveground biomass mapping in Pinus brutia. Using 112 field plots and CART as primary model with Random Forest as robustness check, authors mapped biomass over 13,687 ha and compared totals to forest management plan data.

Impact 30%49
Evidence 25%95
Scale 20%35
Confidence 15%87
Recency 10%96

Updated Aug 24, 2026 · TRV-2026-0861

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

Technostress mediated the relationship, such that when openness to change and positive AI attitudes were low, higher technostress was associated with reduced innovative work behavior among the same hospital staff.

A peer-reviewed study in Journal of Health Organization and Management examined how healthcare workers respond to AI-driven transformation. Using face-to-face surveys of 305 staff at a university hospital in Istanbul in early 2026, the authors tested whether openness to organizational change and attitudes toward AI affect innovative work behavior via technostress.

Impact 30%49
Evidence 25%95
Scale 20%35
Confidence 15%87
Recency 10%96

Updated Aug 24, 2026 · TRV-2026-0859

Recomputed live from the record · Sep 16, 2026, 2:31 AM