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
1/1Semantic Scholar citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2397322726
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Naveed Ahmad (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Governance: 1 paper
- Human Ai Collab: 1 paper
- Productivity: 1 paper
Claim outcomes
- Governance And Regulation: 1 paper
- Organizational Efficiency: 1 paper
- Task Completion Time: 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 |
|---|---|---|---|
| A practical risk-based playbook for government AI: classify systems by impact and require accountability, human oversight, impact assessments, fairness testing, secure audit trails and enforceable procurement clauses for high-risk uses; a phased roadmap helps resource-constrained administrations deploy beneficial AI while protecting rights and trust.openalex | Naveed Ahmad provider id |
2026-01-10 | 10 |
Citation observation summary
Semantic Scholar supplied counts for 1 of 1 papers in this view; 0 are missing. The observed paper counts sum to 10 cumulative citations. This is a coverage summary, not an author score or h-index.