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The Index recomputed live from the record

What the evidence says.What the public feels.

The record holds 939 sourced gains and 772 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.

939 gains
772 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.

1,711 results
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AI gains · 939

545
HealthStableModerate evidence · 1 source

General-purpose AI tool ChatGPT-4o achieved near-certified translation equivalence for English-to-Spanish oncology informed consent forms.

On August 5, 2026, a peer-reviewed study in JCO Oncology Practice evaluated AI translation of three oncology clinical trial informed consent forms from English to Spanish, comparing DeepL Pro, ChatGPT-4o, and a medically trained model Med_English2Spanish against certified translations using five equivalence domains scored by two bilingual physicians.

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

Updated Aug 6, 2026 · TRV-2026-0663

67Index score
546
HealthStableModerate evidence · 1 source

AI companion agents used for emotional support can ease loneliness and produce real symptom reduction for users with mental health concerns.

On August 5, 2026, a viewpoint in the Journal of Participatory Medicine described how large language model chatbots and purpose-built companion agents are being used by millions for emotional support, distress processing, and relationship-like interaction, with 48.7% of people with self-reported mental health concerns reporting use for mental health support.

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

Updated Aug 6, 2026 · TRV-2026-0662

67Index score
547
HealthStableModerate evidence · 1 source

In a cross-sectional analysis of 5 leading chatbots, AI responses to 12 tracheostomy care questions were rated accurate and comprehensive, with Gemini 2.0 scoring higher on completeness than a senior laryngologist, indicating potential to support patient education where guidance is critical for safety.

On 2026-08-04, a peer-reviewed cross-sectional study reported testing ChatGPT4, Gemini 2.0, Copilot, DeepSeek V3, and Grok 3 on 12 tracheostomy care questions, with three blinded laryngologists rating responses for accuracy, completeness, clarity, and sourcing, and readability measured with nine metrics.

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

Updated Aug 5, 2026 · TRV-2026-0657

67Index score
548
HealthStableModerate evidence · 1 source

A multimodal deep learning model using first-24-hour ICU data predicted subsequent in-hospital mortality with high discrimination, and adding clinical notes and chest X-ray images further improved performance.

By August 2026, researchers had developed and externally validated a multimodal deep learning model that uses structured data, clinical notes, and chest X-ray images from the first 24 hours of ICU admission to predict subsequent in-hospital mortality. Trained on MIMIC datasets and tested on more than 200 hospitals including eICU and HiRID, the model achieved high discrimination and calibration.

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

Updated Aug 5, 2026 · TRV-2026-0656

67Index score

AI problems · 772

545
EducationStableModerate evidence · 1 source

Japanese university students using GenAI experience ethical anxiety and heightened awareness of power and risk that complicates agency and moral responsibility.

By July 2026, researchers had surveyed 69 Japanese university students about everyday GenAI use and analyzed responses with systematic grounded theory. They found students moved through an iterative moral trajectory from recognizing power and risk to feeling ethical anxiety, then to reflexive evaluation and conditional trust, captured in the NECoAI model.

Impact 30%
49
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
82

Updated Jul 13, 2026 · TRV-2026-0129

67Index score
546
HealthStableModerate evidence · 1 source

When AI voice and video recording is used in pediatric emergency care, the absence of clinicians, parents, and child patients from design and governance undermines legitimacy and effectiveness, with unresolved issues around consent, emotional impact, and surveillance.

A 2026 position paper examines AI systems that record voice and video during pediatric emergencies, noting they are emerging as HCI technologies with implications for clinical work and are promoted for documentation, team performance, and debriefing. The authors argue that clinicians, parents, and child patients have been largely absent from design and governance.

Impact 30%
49
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
82

Updated Jul 13, 2026 · TRV-2026-0128

67Index score
547
LaborStableModerate evidence · 1 source

STARA adoption can displace routine tasks and roles, leading to involuntary career transitions including job loss due to automation.

What happened is that by 2026-06-03 scholars observed that smart technology, AI, robotics and algorithms were changing work design, with reviews noting varied effects on performance and wellbeing and primary emphasis on displacement of routine tasks and the need to upskill and reskill workers.

Impact 30%
49
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
82

Updated Jul 13, 2026 · TRV-2026-0126

67Index score
548
Media & ArtsStableModerate evidence · 1 source

Singers who contribute singing data face significant harms from downstream non-consensual use including vocal deepfakes and voice cloning.

By July 2026, researchers examined singing data collection as AI voice synthesis advanced, analyzing three singing datasets with the Ethically Aligned Stakeholder Elicitation framework. They found data-contributors have event-centric roles with minimal authority over licensing and access, while data-collectors retain control.

Impact 30%
49
Evidence 25%
95
Scale 20%
35
Confidence 15%
87
Recency 10%
82

Updated Jul 13, 2026 · TRV-2026-0125

67Index score

Recomputed live from the record · Oct 13, 2026, 7:01 PM