Direction, evidence grade, and study type are AI-generated labels (gpt-5-mini), not human-verified. Syntheses are LLM-written. "Tensions" are machine-detected candidates, not confirmed contradictions. A research-acceleration tool, not peer review.
How this is built →
1Distinct papers
1Unique collaborators
1/1Semantic Scholar citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2216443661
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Aarya Parekh (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Governance: 1 paper
- Innovation: 1 paper
Claim outcomes
- Organizational Efficiency: 1 paper
- Governance And Regulation: 1 paper
- Adoption Rate: 1 paper
- Fiscal And Macroeconomic: 1 paper
- Market Structure: 1 paper
Papers in the Semantic Scholar view
Latest stored Semantic Scholar author observations only. Citation counts below are from the same provider and are not combined with other services.
Scroll the table horizontally to see every column.
| Paper | Author evidence | Date | Provider citations |
|---|---|---|---|
| Divergent national laws on contracts, data and taxation are raising legal costs and risks for cross‑border AI business, deterring investment and complicating data flows; coordinated international rules and stronger arbitration could materially lower those frictions and accelerate global AI deployment.openalex | Aarya Parekh provider id |
2026-08-29 | 0 |
Citation observation summary
Semantic Scholar supplied counts for 1 of 1 papers in this view; 0 are missing. The observed paper counts sum to 0 cumulative citations. This is a coverage summary, not an author score or h-index.