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
0Unique collaborators
1/1OpenAlex citation coverage
Publication dates unavailable. Corpus fetch span: 2026.
Identity provenance
Provider IDs
No provider ID is stored.
ORCID evidence
Observed aliases (1)
- Satyadhar Joshi (openalex, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Governance: 1 paper
- Inequality: 1 paper
- Org Design: 1 paper
- Productivity: 1 paper
Claim outcomes
- Ai Safety And Ethics: 1 paper
- Organizational Efficiency: 1 paper
- Firm Productivity: 1 paper
- Inequality: 1 paper
- Adoption Rate: 1 paper
- Governance And Regulation: 1 paper
- Market Structure: 1 paper
- Output Quality: 1 paper
- Regulatory Compliance: 1 paper
Papers in the OpenAlex view
Latest stored OpenAlex 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 |
|---|---|---|---|
| Open-source AI offers transparency, customization and privacy advantages while proprietary systems dominate on reliability and vendor support; policymakers should adopt a hybrid, tiered governance and certification regime to capture complementary benefits without entrenching inequities or market concentration.semantic_scholar | Satyadhar Joshi orcid |
Fetched 2026-03-12 | 2 |
Citation observation summary
OpenAlex supplied counts for 1 of 1 papers in this view; 0 are missing. The observed paper counts sum to 2 cumulative citations. This is a coverage summary, not an author score or h-index.