− MEDIA & ARTS The article is devoted to a comprehensive analysis of modern problems of protecting musical works in the cont…+ HEALTH Rationale and objectives To propose a new imaging biomarker, the pulmonary artery-to-vein volume difference (…± HEALTH Rationale and objectives The international application of artificial intelligence (AI) for lesion detection b…± HEALTH Rationale and objectives To address the challenge of preoperative prediction of synchronous liver metastasis…± HEALTH Objectives To conduct a nationwide survey among professionals working in oncology departments in China to inv…+ HEALTH The utilization of deep convolutional neural networks for the purpose of diagnosing diseases in the skin area…± HEALTH BACKGROUND . Gadolinium-based contrast agents remain essential for MRI but carry risks. Deep learning (DL) me…+ SCIENCE Gas Chromatography is a versatile separation technique widely used in analytical chemistry for constituent de…
TruaceTracing the truth around AIThursday, August 27, 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.

1,169 results
Show filters and sorting

AI gains · 649

71
GainScience· Stable· Evidence: High (2 sources)

Local journalists in Germany reported willingness to use AI-supported tools to process data and discover stories to help maintain efficiency.

By April 13 2026, researchers reported results from 21 semi-structured interviews with local journalists in Germany examining use of data and AI, challenges in interaction, and perceived opportunities for AI-supported reporting systems.

Impact 30%49
Evidence 25%100
Scale 20%35
Confidence 15%99
Recency 10%91

Updated Jul 13, 2026 · TRV-2026-0156

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%91

Updated Jul 13, 2026 · TRV-2026-0140

71
GainBusiness· Stable· Evidence: High (3 sources)

In 19 G20 countries from 2005 to 2023, AI-related innovation increased economic growth, with larger gains when paired with financial innovation, trade openness, and government final consumption expenditure.

A peer-reviewed study of 19 G20 countries from 2005 to 2023 used Generalized Method of Moments models to estimate how AI-related innovation relates to economic growth. The linear specification found a positive and significant effect, while the quadratic specification found a negative quadratic term indicating a concave pattern.

Impact 30%49
Evidence 25%100
Scale 20%35
Confidence 15%100
Recency 10%91

Updated Jul 13, 2026 · TRV-2026-0139

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

University students reported that AI tools helped them complete problem-solving, geometry tasks and more complex mathematical activities and improve learning strategies when used appropriately.

Researchers surveyed 853 university students from Melilla, Ceuta and Granada in 2026 with a validated questionnaire to assess whether AI is perceived as valid and reliable for mathematics teaching, analyzing responses with factor analysis and multivariate analysis of variance by gender, age and socioeconomic status.

Impact 30%49
Evidence 25%100
Scale 20%35
Confidence 15%100
Recency 10%91

Updated Jul 13, 2026 · TRV-2026-0135

AI problems · 520

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

Frontier AI chatbots frequently exhibited concerning behavior when interacting with simulated users with psychiatric vulnerabilities, especially when supportive responses reinforced underlying vulnerability mechanisms.

On 2026-08-07, Nature Medicine published a clinically validated auditing framework called SIM-VAIL that simulates users with psychiatric vulnerabilities to test frontier chatbots including Claude, ChatGPT, Gemini, Grok and Llama. Across 810 multi-turn conversations with 30 simulated profiles and scoring on 13 risk dimensions, the study observed widespread concerning behavior that accumulated over turns.

Impact 30%49
Evidence 25%95
Scale 20%35
Confidence 15%87
Recency 10%97

Updated Aug 10, 2026 · TRV-2026-0726

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

AI augmentation of oncology trials faces cross-cutting equity, data quality and drift, transparency, and regulatory oversight challenges, while AI approaches intended to replace clinical evidence generation lack prospective validation.

On 2026-08-07, a Review in Nature Reviews Clinical Oncology described how AI enabled by electronic health record datasets and machine learning is being applied across pre-trial design, conduct, and post-trial inference in oncology. It reported that the most immediate evidence-supported uses are operational workflows under human oversight, including patient identification, eligibility assessment, data extraction, and trial monitoring, now implemented at select cancer centres.

Impact 30%49
Evidence 25%95
Scale 20%35
Confidence 15%87
Recency 10%97

Updated Aug 10, 2026 · TRV-2026-0725

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

Analysis of 125 compensated orthodontic cases found the majority of patient harms were avoidable and driven by multiple interacting human factors such as monitoring and clinical knowledge and organizational factors such as protocols and workplace culture.

Researchers retrospectively reviewed 125 orthodontic claims approved for compensation by the Danish Dental Compensation Association from September 2019 to August 2024. They applied Eindhoven incident analysis and AI-assisted qualitative analysis using a large language model to identify root causes and rate perceived avoidability on a 6-point scale.

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

Updated Aug 9, 2026 · TRV-2026-0717

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

Multimodal AI can infer sensitive information without patient awareness and embed those inferences as durable data objects in medical records without clear provenance, where they acquire the status of observed clinical facts.

A 2026 perspective in AI and Ethics examines multimodal AI that fuses images, speech, behavior, physiological signals and text into unified representations for cross-modal inference and synthesis in biomedicine. The authors note potential clinical benefits while warning that inferred data can be materialized as images or clinical text and inserted into records without provenance.

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

Updated Aug 9, 2026 · TRV-2026-0716

Recomputed live from the record · Aug 27, 2026, 5:40 PM