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
2Unique collaborators
1/1Semantic Scholar citation coverage
Publication span: 2025. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2419159038
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Ali Aijaz Shar (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Governance: 1 paper
- Human Ai Collab: 1 paper
- Labor Markets: 1 paper
- Org Design: 1 paper
Claim outcomes
- Ai Safety And Ethics: 1 paper
- Organizational Efficiency: 1 paper
- Decision Quality: 1 paper
- Governance And Regulation: 1 paper
- Other: 1 paper
- Worker Satisfaction: 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 |
|---|---|---|---|
| Organizations that adopt AI recruitment systems report faster, more consistent hiring and lower perceived bias, but candidate trust hinges on governance and explainability; the benefits shown are associative and depend on tool design and oversight.openalex | Ali Aijaz Shar provider id |
2025-12-27 | 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.