On February 15 the Heilongjiang provincial government published a detailed "AI+" plan to fold artificial intelligence into everyday public services. The programme lays out new livelihood scenarios — spanning employment services, medical imaging and dynamic oversight of social assistance — and signals a step up in the use of automated decision tools at the local level.
In the employment domain, the province will upgrade a centrally managed, cross‑agency employment information repository that is designed to synchronize data in real time. The objective is to build an end‑to‑end service chain for priority jobseekers, using AI to improve matching, case management and cross‑program coordination for groups whose employment is most vulnerable during economic restructuring.
For healthcare, Heilongjiang plans to leverage a provincial imaging cloud to aggregate large volumes of high‑quality, unstructured medical images and to deploy AI to assist with diagnosis, auto‑generate reports and suggest treatment options. The policy explicitly targets support for secondary and higher‑tier public hospitals and envisages a pilot ‘‘provincial AI demonstration hospital’’ that would expand intelligent imaging from single‑disease applications to multi‑disease coverage.
On social assistance, the province intends to stitch together 18 datasets and API interfaces — covering low‑income support, severe hardship, disability, household registration, motor vehicles, business entities and other administrative records — and to deploy an "intelligent audit + dynamic supervision" system. That system is intended to perform continuous eligibility reviews and strengthen end‑to‑end oversight to reduce erroneous or fraudulent disbursements.
This rollout fits into Beijing’s broader drive to embed AI across governance functions: provinces are being encouraged to pilot applications that boost administrative efficiency and reduce fiscal leakage. Heilongjiang’s plan is pragmatic in scope, mixing operational upgrades with concrete technical infrastructure — a cloud for medical imaging, an integrated employment data pool, and interoperable APIs for welfare verification.
But operational and ethical trade‑offs are immediate. Integrating sensitive data across multiple administrative silos presents technical hurdles in interoperability, and concentrates risk around cybersecurity and privacy. Medical AI tools will require rigorous clinical validation, liability rules and continued clinician oversight to prevent over‑reliance on automated outputs.
The success of Heilongjiang’s initiative will hinge on implementation: the quality of underlying data, the governance of algorithms, transparency about automated decisions, and mechanisms for appeal. If the province gets these elements right, the programme could serve as a replicable model for other regions; if not, it will illustrate the hazards of rapid digital centralization without commensurate safeguards.