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 span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5148662245
ORCID evidence
No valid ORCID is stored.
Observed aliases (2)
- Michael Anderson (openalex, provider refresh)
- Michael Anderson (openalex, source metadata)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Governance: 1 paper
- Inequality: 1 paper
- Innovation: 1 paper
- Labor Markets: 1 paper
- Productivity: 1 paper
- Skills Training: 1 paper
Claim outcomes
- Firm Productivity: 1 paper
- Employment: 1 paper
- Fiscal And Macroeconomic: 1 paper
- Governance And Regulation: 1 paper
- Inequality: 1 paper
- Innovation Output: 1 paper
- Job Displacement: 1 paper
- Organizational Efficiency: 1 paper
- Skill Acquisition: 1 paper
- Social Protection: 1 paper
- Task Allocation: 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 promises substantial productivity and growth gains by automating tasks and enabling new products, but benefits are uneven: without investments in skills, infrastructure and policy safeguards, gains will concentrate among tech firms and skilled workers and could widen inequality.openalex | Michael Anderson provider id |
2026-08-30 | 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.