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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

529
Media & ArtsStableModerate evidence · 1 source

AI autonomy feasibility increases when defined cognitive rules combine with novel rule creation, supporting a predominantly hybrid human-AI configuration across creative tasks.

Researchers analyzed 593 tasks across 126 occupations in the cultural and creative industries using GPT-4 generated synthetic annotations of Australian Skills Classification descriptions. They measured cognitive and behavioural rules and estimated AI autonomy feasibility and efficiency potential to map where human, AI, or hybrid carriers fit.

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

Updated Aug 8, 2026 · TRV-2026-0693

67Index score
530
HealthStableModerate evidence · 1 source

A CatBoost model trained on 1,858 non-dialysis CKD patients predicted 5-year all-cause mortality with AUC 0.813, outperforming logistic regression, and a simplified 5-feature version maintained AUC 0.795 in external validation.

Researchers developed and validated an interpretable machine learning model to predict 5-year all-cause mortality in non-dialysis chronic kidney disease using data from 1,858 patients in the KNOW-CKD prospective cohort, with 94 deaths observed. The CatBoost model achieved AUC 0.813 versus 0.747 for logistic regression, and a simplified version using age, eGFR, albumin, urine protein-to-creatinine ratio, and total calcium retained AUC 0.795 in an external cohort of 348 patients.

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

Updated Aug 8, 2026 · TRV-2026-0688

67Index score
531
PolicyRisingModerate evidence · 1 source

AI-augmented implementation could help execute Medicaid work requirement processes and facilitate enrollment among eligible individuals, limiting unintended coverage loss.

On August 7, 2026, JAMA Health Forum published a Special Communication proposing that artificial intelligence tools could support implementation of health care policies, using Medicaid work requirements under the Budget Reconciliation Act of 2025 as an example. The authors describe AI executing processes like generating eligibility screening tools, reviewing documentation, and linking data for compliance indicators, plus identifying at-risk individuals and monitoring implementation.

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

Updated Aug 8, 2026 · TRV-2026-0685

67Index score
532
ScienceStableModerate evidence · 1 source

Generative AI tools, especially ChatGPT chatbots, were associated with enhanced institutional performance and work productivity across sectors including academia, research, technology, communications, agriculture, government, and business as of early 2024.

By January 30, 2024, a peer-reviewed review in Sustainability synthesized 159 studies using PRISMA to assess generative AI use across seven professional sectors. It reported that tools like ChatGPT chatbots were dominant and linked to gains in institutional performance and work productivity.

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

Updated Aug 7, 2026 · TRV-2026-0682

67Index score

AI problems · 772

529
EducationStableModerate evidence · 1 source

Practitioners reported tensions that AI assistance could erode professional judgment, reflective value of writing, and create deskilling risk and ethical complexity.

Researchers analyzed baseline evaluation data from the rollout of Magic Note, an AI-assisted recording tool, in a Scottish Local Authority social work department, involving surveys, focus groups and free-text responses from practitioners.

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

Updated Jul 13, 2026 · TRV-2026-0172

67Index score
530
PolicyStableModerate evidence · 1 source

Mixed musical works that blend human and generative AI elements fall into a copyright 'Dead Man's Land' where the U.S. Copyright Office must inspect works case-by-case, creating an inefficient and ineffective process.

A May 2026 law review article examines mixed musical works that contain a blend of human and generative AI elements, arguing they occupy a copyright 'Dead Man's Land' in the United States. It describes a landscape where federal guidance is non-binding and circuit courts issue contradictory fair-use rulings, forcing the U.S. Copyright Office to inspect mixed works on a case-by-case basis.

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

Updated Jul 13, 2026 · TRV-2026-0170

67Index score
531
HealthStableModerate evidence · 1 source

Most agentic AI studies in healthcare were exploratory, limited in scope, lacked robust clinical validation, and lacked conceptual clarity, with only one trial involving patients.

A March 2026 scoping review in npj Digital Medicine examined agentic AI in healthcare, defined as systems capable of operating autonomously to achieve defined clinical goals. Across five databases, seven studies met criteria, spanning emergency medicine, oncology, radiology, and rehabilitation, with features including autonomous operation, goal-directed behavior, action initiation, and multi-agent collaboration.

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

Updated Jul 13, 2026 · TRV-2026-0166

67Index score
532
BusinessStableModerate evidence · 1 source

High religiosity marginally weakens the positive link between digitalization and MSME labor productivity, reflecting transitional adaptation frictions in highly normative environments.

A peer-reviewed study of Indonesian provinces from 2020 to 2023 examined how digitalization and AI adoption relate to MSME labor productivity, using fixed-effects panel estimation and machine learning methods and framing results with Ibn Khaldun's institutional ideas.

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

Updated Jul 13, 2026 · TRV-2026-0165

67Index score

Recomputed live from the record · Oct 13, 2026, 5:29 PM