TruaceTracing the truth around AIWednesday, August 26, 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.

1,155 results
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AI gains · 641

78
GainHealth· Stable· Evidence: Moderate (1 source)

LightGBM-based model predicted obesity versus normal weight in children aged 3-12 with prior RTIs with high accuracy and AUC, enabling early screening for targeted intervention.

In a study of 6509 children and adolescents aged 3-12 with prior respiratory tract infections in Beijing and Tangshan, researchers developed and compared 12 machine learning models to predict obesity risk, with LightGBM achieving the best reported performance and a deep learning sequence network used to verify the selected features.

Impact 30%49
Evidence 25%95
Scale 20%85
Confidence 15%87
Recency 10%96

Updated Aug 8, 2026 · TRV-2026-0690

78
GainHealth· Stable· Evidence: Moderate (1 source)

AI research is moving ADHD diagnosis away from subjective interviews toward objective, data-driven tools, with EEG emerging as preferred modality for recent models.

A bibliometric review of 722 Scopus-indexed papers from 2011 to 2024 tracked how artificial intelligence has been applied to ADHD prediction. Using Python and VOSviewer, the authors found exponential growth peaking in 2023, a concentration of output in the United States and China, and a technological shift from support vector machines to deep learning with EEG becoming the favored data modality.

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

Updated Aug 3, 2026 · TRV-2026-0630

78
GainMedia & Arts· Stable· Evidence: Moderate (1 source)

Adoption of text-to-image generative AI increased human creative productivity and the likelihood of peer favorites per view among artists in a large online art community.

By February 2024, researchers analyzing over 4 million artworks from more than 50,000 users found that text-to-image generative AI adoption was linked to a 25% rise in creative productivity and a 50% rise in favorites per view, alongside shifts in novelty metrics.

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

Updated Jul 31, 2026 · TRV-2026-0604

78
GainHealth· Stable· Evidence: Moderate (1 source)

Structural modeling tools such as AlphaFold and RoseTTAFold enable high-accuracy 3D prediction of proteins encoded by multidrug-resistant bacterial genomes, facilitating functional annotation and accelerating design of new antimicrobial compounds.

By July 30 2026, a narrative review in Journal of Computer-Aided Molecular Design described the use of structural modeling and artificial intelligence for functional prediction of proteins encoded by multidrug-resistant bacterial genomes. It reported that tools such as AlphaFold and RoseTTAFold have enabled high-accuracy three-dimensional structure prediction, facilitating annotation of hypothetical proteins and identification of conserved domains and catalytic sites.

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

Updated Jul 31, 2026 · TRV-2026-0599

AI problems · 514

78
ProblemClimate· Stable· Evidence: Moderate (1 source)

Large-scale deployment of AI servers across the United States is projected to create 731 to 1,125 million m3 of annual water use and 24 to 44 Mt CO2-equivalent of additional annual carbon emissions between 2024 and 2030, jeopardizing net-zero goals.

Published November 10 2025 in Nature Sustainability, the study models the sustainability implications of rapidly expanding generative AI server installations across the United States, projecting annual water and carbon footprints through 2030 and testing mitigation options.

Impact 30%49
Evidence 25%95
Scale 20%85
Confidence 15%87
Recency 10%93

Updated Jul 22, 2026 · TRV-2026-0474

78
ProblemScience· Rising· Evidence: Moderate (1 source)

Deepfake creation and dissemination is used as a form of online sexual violence to silence women in public spaces online, reflecting gendered systemic discrimination.

This November 2025 scoping review in Trauma, Violence, & Abuse synthesized literature on deepfakes in gender-based violence. The authors screened thousands of records from mid-2024 and analyzed 64 psychology and social science articles to map how deepfakes are understood as a form of online violence against women.

Impact 30%49
Evidence 25%95
Scale 20%85
Confidence 15%87
Recency 10%93

Updated Jul 20, 2026 · TRV-2026-0457

78
ProblemClimate· Stable· Evidence: Moderate (1 source)

AI workloads' environmental impact is growing rapidly but remains hard to quantify because data center operators do not separate AI and non-AI reporting, with AI alone projected to reach 32.6-79.7 million tons CO2 and 312.5-764.6 billion liters of water in 2025.

A December 2025 peer-reviewed article in Patterns examines how to estimate the carbon and water footprints of data centers and AI. It finds that lack of workload-specific reporting forces researchers to approximate AI impacts from general data center metrics, and that company disclosures often do not allow even total performance to be determined.

Impact 30%49
Evidence 25%95
Scale 20%85
Confidence 15%87
Recency 10%93

Updated Jul 20, 2026 · TRV-2026-0433

78
ProblemHealth· Stable· Evidence: Moderate (1 source)

AI marketing discourses for nursing homes depict older people as passive data sources and care staff as inefficient, reducing complex care to datafication and solutionism

Published December 15 2025, this peer-reviewed discourse study examined how AI for later life is framed by industry. The authors analyzed the websites of 33 AI companies selling robots to chatbots into care (nursing) homes, using concepts of breakdown and repair, delegation, and user representations to identify dominant narratives.

Impact 30%49
Evidence 25%95
Scale 20%85
Confidence 15%87
Recency 10%93

Updated Jul 20, 2026 · TRV-2026-0430

Recomputed live from the record · Aug 27, 2026, 12:42 AM