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
1Unique collaborators
1/1OpenAlex citation coverage
Publication dates unavailable. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5139917970
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Alimzhan Yessenovabylov (openalex, provider refresh)
Topics and outcomes in this view
Assessment themes
- Governance: 1 paper
- Inequality: 1 paper
- Labor Markets: 1 paper
- Skills Training: 1 paper
Claim outcomes
- Automation Exposure: 1 paper
- Governance And Regulation: 1 paper
- Skill Obsolescence: 1 paper
- Employment: 1 paper
- Job Displacement: 1 paper
- Other: 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 |
|---|---|---|---|
| AI and generative AI may add 78 million jobs globally by 2030, but the boom masks intense disruption: over one in five jobs will be structurally transformed and nearly 40% of current skills risk obsolescence. Women—especially in high‑income countries—face disproportionately high automation risk, while Kazakhstan’s new AI law and Alem.AI highlight early state attempts to manage an emerging 'AI precariat'.semantic_scholar | Alimzhan Yessenovabylov provider id |
Fetched 2026-07-13 | 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.