The British government recently announced an ambitious artificial intelligence investment plan, aiming to use AI technology to improve the efficiency of the public sector, and held a press conference on Tuesday to announce the implementation plan in detail. The core of the plan is an AI assistant named "Humphrey", which will help civil servants handle daily affairs more efficiently and cover multiple application scenarios, such as policy document preparation, meeting minutes transcription, etc. The initiative is expected to save up to £45 billion a year by optimizing processes and promoting cross-departmental data sharing and collaboration. However, programs also face challenges with data privacy and cross-sector collaboration.
Recently, the British government announced a comprehensive artificial intelligence investment plan aimed at improving the efficiency of the public sector. The specific implementation plan will be officially announced at a press conference held by the Department of Science, Innovation and Technology (DSIT) on Tuesday. The plan includes the launch of an artificial intelligence assistant called "Humphrey" designed to help civil servants handle their daily work more efficiently.
The projects are still in their preliminary stages, according to the government website. For example, plans to introduce artificial intelligence services into the National Health Service (NHS) are still in their infancy, with only a preliminary “charter” in place. In addition, the government will also share project progress through platforms such as Github, but it has not yet been made clear how many people will participate and whether third-party tools will be used.
DSIT said the government currently spends £23 billion a year on technology, so the plan hopes to reallocate these funds in a modern way. DSIT Minister Peter Kyle said: "Dull technology has been hampering our public services, costing us time and money. We hope to improve information sharing and collaboration through artificial intelligence technology."
The plan mainly focuses on three aspects:
1. Work for civil servants: Humphrey Assistant includes a series of applications designed to reduce the daily workload of civil servants. For example, “Consult” can summarize thousands of consultation feedback in a few hours; “Parlex” can help employees query policy-related parliamentary conversations; “Minute” is a secure meeting transcript transcription service; “Redbox” helps prepare policy documents ; "Lex" is used to find relevant legal information.
2. Improve the efficiency of public services: The government hopes to use artificial intelligence to simplify cumbersome processes, such as the 100,000 calls the tax office receives every year, or the need to register a death in person. DSIT estimates that optimizing these processes could result in annual savings of up to £45 billion.
3. *Cross-department collaboration: Finally, DSIT hopes to speed up the efficiency of service procurement and implementation by enhancing data sharing between departments.
These projects convey the British government's determination to promote artificial intelligence, but also raise some questions, such as the privacy protection of data sharing, and the government's trust in the conclusions of artificial intelligence. Civil servants have said that past cross-departmental cooperation has not always been successful, and that the use of funds, collaboration and authority will be the key factors in determining the success or failure of these plans.
Highlight:
**Launch of "Humphrey" Assistant**: designed to improve the work efficiency of civil servants, including a variety of dedicated applications.
** Optimizing public services **: Reducing red tape through artificial intelligence is expected to save an estimated £45 billion per year.
** Strengthen cross-departmental cooperation**: Promote data sharing and improve the efficiency of service procurement and implementation.
The British government's artificial intelligence investment plan is ambitious and aims to improve the efficiency of public services through technological means. However, its success ultimately depends on the effective allocation of funds, close collaboration between departments, and effective management and control of potential risks. Future implementation progress deserves continued attention.