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The Index recomputed live from the record

What the evidence says.What the public feels.

The record holds 932 sourced gains and 770 sourced problems, averaging 68 and 66 on the index score. Readers have logged 22 public signals on the Pulse, which is kept apart and never counted as evidence.

932 gains
770 problems
Every sourced claim in the Index, one square each, shaded by the strength of its evidence. High Moderate Emerging

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

1,702 results
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AI gains · 932

783
ClimateStableModerate evidence · 1 source

Expert-guided and LLM-augmented feature selection improved generalizability of data-driven models for nitrous oxide emission prediction at a full-scale wastewater plant, maintaining temporal dynamics under out-of-distribution high-flow conditions where attention-based deep learning failed.

By the publication date of 2026-07-12, researchers tested a knowledge-driven feature selection framework for data-driven wastewater modeling, comparing classic attention-based deep learning against expert-guided and LLM-augmented selection. In the reported case study of N2O emissions at a full-scale plant, expert-guided selection achieved mean R2 0.723 and MAE 0.033, slightly above the best attention model at R2 0.712, while LLM-augmented reached R2 0.596 and MAE 0.041.

Impact 30%
49
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
83

Updated Jul 13, 2026 · TRV-2026-0120

67Index score
784
OtherStableModerate evidence · 1 source

AIGC lowers prior constraints on user innovation and drives innovative behavior through external technical and content factors and internal user factors.

As of the July 10 2026 publication date, researchers reported a grounded theory study of 1,502 public articles and more than 120,000 words of interviews to examine how AIGC influences user innovation. They built a TCEU framework where technical factors and content factors act as external drivers and user factors act as internal drivers, with technology popularity and platform convenience as moderators.

Impact 30%
49
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
83

Updated Jul 13, 2026 · TRV-2026-0112

67Index score
785
ScienceStableModerate evidence · 1 source

SparksMatter autonomously executed the full in-silico discovery cycle from ideation to iterative refinement and proposed novel stable inorganic candidates meeting target objectives in thermoelectrics, semiconductors, and perovskite oxides, with blinded evaluation showing higher relevance and novelty than frontier basel

Researchers introduced SparksMatter, a multi-agent physics-aware model that autonomously carries out the full in-silico inorganic materials discovery cycle from ideation and planning to experimentation and iterative refinement, then proposes candidates meeting target objectives and produces a structured report with self-critique and suggested validation steps.

Impact 30%
49
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
83

Updated Jul 13, 2026 · TRV-2026-0110

67Index score
786
PolicyStableModerate evidence · 1 source

Minor parties adopted visual generative AI at higher rates than major parties during the 2025 German federal election, gaining broader access to professional campaign visual production.

During the four weeks before the 2025 German federal election, 37 parties' Facebook and Instagram accounts published nearly 1,000 VGenAI images and videos. Minor parties used VGenAI at higher rates than major parties, consistent with lower-cost access to professional visuals, while mainstream major parties disclosed AI origins more frequently than minor parties and the AfD, which used more photorealistic, citizen, criminal, and negative-tone imagery.

Impact 30%
49
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
83

Updated Jul 13, 2026 · TRV-2026-0109

67Index score
787
LifestyleStableModerate evidence · 1 source

Young immigrant men aged 21-35 in Helsinki used generative AI tools like ChatGPT and Gemini to lower language and knowledge barriers while searching recipes, adapting dishes to cultural or religious preferences, and learning cooking techniques.

What happened: In Helsinki, young immigrant men aged 21-35 described routing everyday eating through digital platforms, using apps and chats to find recipes, adapt dishes, and learn techniques, with generative AI tools lowering language and knowledge barriers while also creating frictions like advice overload and cultural mismatch.

Impact 30%
49
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
83

Updated Jul 13, 2026 · TRV-2026-0108

67Index score
788
HealthStableModerate evidence · 1 source

In a survey of 241 people with MS, respondents reported higher comfort with AI when used for low-risk supportive roles like chronic management and symptom screening, with most preferring a joint model where clinicians retain final responsibility.

By July 1 2026, researchers had surveyed 241 people with MS via a web-based questionnaire to measure comfort with AI across eight clinical domains. They found moderate overall acceptance (mean 3.39 ± 0.78) that varied by task, with 54.4% comfortable with chronic management and 50.2% with symptom screening, compared to 38.6% for treatment selection and 35.3% for diagnosis. Frequent general AI use was the strongest predictor of acceptance.

Impact 30%
49
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
83

Updated Jul 13, 2026 · TRV-2026-0107

67Index score
789
EducationStableModerate evidence · 1 source

ChatGPT can enhance productivity and deliver significant gains for organizations in banking, hospitality and tourism, and information technology.

This opinion paper compiles 43 expert contributions to examine transformative tools such as ChatGPT. Contributors describe systems that generate sophisticated human-like text and discuss their applicability across many organizational settings, with particular attention to productivity effects.

Impact 30%
49
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
83

Updated Jul 12, 2026 · TRV-2026-0050

67Index score
790
PolicyNewly addedModerate evidence · 1 source

The UK's upcoming G20 presidency could be used to secure agreement on a process toward a global treaty regulating artificial intelligence.

On 5 October 2026 The Guardian published a comment piece arguing that Andy Burnham's government must decide priorities for the UK's G20 presidency next year. The author proposes that the first priority should be securing agreement on the need for and a process towards a global treaty on AI regulation, following recent alarm over existential risks.

Impact 30%
49
Evidence 25%
62
Scale 20%
85
Confidence 15%
62
Recency 10%
99

Updated Oct 8, 2026 · TRV-2026-1308

66Index score

AI problems · 770

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Recomputed live from the record · Oct 11, 2026, 8:43 AM