aceArtificial Intelligence Development and Worker Employment Quality: Evidence from China
With the continuous development of new technologies, these new technologies have a profound impact on the labor market. This paper uses micro-individual data from the China Family Panel Studies (CFPS) from 2016 to 2022 and provincial-level macro-data on artificial intelligence (AI), employing a two-way fixed-effects model to systematically examine the actual impact and underlying mechanisms of AI development on the employment quality of workers. The study shows a significant positive correlation between the leve…
Provinces with higher AI development show better employment quality among local workers, mainly via industrial structure upgrading and more intelligent working modes.
The regional-level result cannot directly prove the individual-level effect of enterprises or employees using AI.
Evidence
- Peer-reviewedSustainability2026-10-16
How should this claim be treated?
Truvace Impact Record TRV-2026-1719, v1: “Artificial Intelligence Development and Worker Employment Quality: Evidence from China.” Truvace, 2026-10-17. /record/TRV-2026-1719 (accessed at citation time). sha256 cb345f16099195ec…
Calibration history
Every change to this record since certification, in the open. None yet — the reading has held since it entered the record.
Certified into the record
How to verify without trusting this page
Fetch the canonical text of any version from /api/record/TRV-2026-1719 and hash it yourself — for example shasum -a 256 on the saved canonical field. The result must equal content_hash, and each version’s text ends with prev:followed by the prior version’s hash (version 1 chains to 64 zeros). If a single character of any version had been altered since certification, the chain would not reproduce.