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
1/1Semantic Scholar citation coverage
Publication dates unavailable. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2258379885
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Jonathan Haskel (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Innovation: 1 paper
- Productivity: 1 paper
Claim outcomes
- Firm Productivity: 1 paper
- Other: 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 |
|---|---|---|---|
| Software and software R&D—linked to AI—explain half of U.S. nonfarm business labor productivity growth between 2017 and 2024, and half of the 1.2 percentage-point acceleration versus the prior five years, implying AI is already materially affecting official productivity measures.semantic_scholar | Jonathan Haskel provider id |
Fetched 2026-05-20 | 1 |
Citation observation summary
Semantic Scholar supplied counts for 1 of 1 papers in this view; 0 are missing. The observed paper counts sum to 1 cumulative citations. This is a coverage summary, not an author score or h-index.