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 →
2Distinct papers
52Unique collaborators
2/2Semantic Scholar citation coverage
Publication span: 2025–2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2299380010
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Zhi-Xuan Tan (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Governance: 2 papers
- Human Ai Collab: 2 papers
- Org Design: 2 papers
- Adoption: 1 paper
- Innovation: 1 paper
- Labor Markets: 1 paper
- Productivity: 1 paper
- Skills Training: 1 paper
Claim outcomes
- Governance And Regulation: 2 papers
- Ai Safety And Ethics: 1 paper
- Task Allocation: 1 paper
- Adoption Rate: 1 paper
- Automation Exposure: 1 paper
- Decision Quality: 1 paper
- Firm Productivity: 1 paper
- Hiring: 1 paper
- Market Structure: 1 paper
- Organizational Efficiency: 1 paper
- Skill Acquisition: 1 paper
- Skill Obsolescence: 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 |
|---|---|---|---|
| AI only augments work when entire workflows—not just isolated tasks—are redesigned to deliver durable net value, preserve meaningful human control and accountability, and sustain learning and career pathways; otherwise short-term productivity gains risk eroding oversight, skills, and job quality.arxiv | Zhi-Xuan Tan provider id |
2026-09-11 | 0 |
| Aligning an AI to its operator’s wishes is not enough: without institutions that embody shared values, even 'perfectly aligned' systems can produce harmful societal outcomes. The authors propose 'full‑stack alignment'—thick, structured models of value embedded in institutions and systems—to enable normatively competent agents, stewardship, win‑win negotiation, meaning‑preserving economic mechanisms, and democratic regulation.openalex | Zhi-Xuan Tan provider id |
2025-12-03 | 10 |
Citation observation summary
Semantic Scholar supplied counts for 2 of 2 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.