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: 2025. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2398907212
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Haocheng Lin (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Governance: 1 paper
- Labor Markets: 1 paper
Claim outcomes
- Adoption Rate: 1 paper
- Creativity: 1 paper
- Governance And Regulation: 1 paper
- Inequality: 1 paper
- Innovation Output: 1 paper
- Other: 1 paper
- Social Protection: 1 paper
- Task Allocation: 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 |
|---|---|---|---|
| Generative AI is altering jobs and creativity unevenly and risks eroding human evaluative authority; the authors propose an Inclusive AI Governance Framework built around a new 'Level 1.5' autonomy and recommend embedding UBI within skills, regulation and creativity-preserving measures.arxiv | Haocheng Lin provider id |
2025-12-09 | 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.