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
3Unique collaborators
1/1OpenAlex citation coverage
Publication dates unavailable. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5067071953
ORCID evidence
Observed aliases (1)
- Tingli Liu (openalex, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Human Ai Collab: 1 paper
- Inequality: 1 paper
- Productivity: 1 paper
Claim outcomes
- Task Allocation: 1 paper
- Inequality: 1 paper
- Adoption Rate: 1 paper
- Consumer Welfare: 1 paper
- Worker Satisfaction: 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 |
|---|---|---|---|
| Creators hide their use of generative AI to preserve authenticity, turning 'efficiency' gains into downstream repair and performance work; those with more education, money, or team support are better able to pass, widening trust-based inequality.semantic_scholar | Tingli Liu orcid |
Fetched 2026-05-01 | 0 |
Citation observation summary
OpenAlex 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.