UK to unveil ‘Humphrey’ assistant for civil servants with another AI plan to cut bureaucracy

A week after the UK government announced sweeping plans to make huge investments into AI, it sheds more light on how this will play out in the public sector. On the agenda: AI assistants to speed up public services; data sharing transactions between siled departments; and a new AI tool – dubbed “Humphrey” after a character in an old British TV political sitcom – to speed up the work of civil servants. The plan will be officially announced at a press conference on Tuesday led by the Department of Science, Innovation and Technology (DSIT), along with two other departments, Work and Pensions and Health/Social Care. If you navigate to the UK government’s AI site to check the progress of some projects, you will see that most of the efforts so far appear to be in very early stages, either in limited trials or testing phase; others are even more recent. For example, the plan to bring other AI services to the customer-facing side in the NHS is only at the stage of “charter” doing for the concept. Some include links to Github repositories to check out some of the work so far. It is unclear how many people are working on the project, or what third-party tools (such as LLM) are being used. (We’ve asked this question and will update it as we learn more.) At heart, the project is all about efficiency. The government, says DSIT, currently spends some £23 billion a year on technology, and the idea is to deploy that money in a more modern way. “Slow technology has hindered public services for too long, and it costs us all time and money…form,” said Peter Kyle, Secretary of State for DSIT, in a statement. “My department will create AI … We will use technology to overcome the nonsensical approach taken by the public sector to share information and work together to help the people we serve.” The plan includes a new team at DSIT to lead the project, similar to DOGE in the US but organized and managed by the government instead of tech moguls. DSIT focuses on three areas at the beginning: 1. The work of government employees. Humphrey, named after Wry, the smart assistant played by the late Nigel Hawthorne in “Yes, Minister” and then “Yes, Prime Minister,” is a set of applications that aim to reduce the daily workload of civil servants, especially around large areas. the amount of data that must be read and processed as part of their work. “Consultation” is designed to read and summarize “thousands” of responses to the consultation over several hours (responses, which can be long and numerous, are a central part of how the government takes feedback from stakeholders and the public). “Parlex” will allow them to ask questions and read conversations in Parliament relevant to bills or other policy documents in progress. “Minutes” is a secure transcription service for taking notes from hours of meetings. “Redbox” helps them prepare briefings and policy documents. And “Lex” allows them to consult relevant legal data. 2. Another thread of the efficiency push will be to speed up public-facing services. The idea here is to address the legacy bureaucracy, which is too much in the UK, such as the 100,000 calls that the tax authorities make every day, or the need for people to appear in person to register a death, or (oddly. ) place an advertisement in the local newspaper as part of the process of taking license to drive a truck. DSIT’s thinking is that this kind of overhauling process with AI fuel automation could save £45 billion a year. (It is not clear if the estimate is before or after reducing the cost of building and running AI services.) 3. The last area will focus on other collaborations between departments to help share data to speed up how to get services, and then how they can. Taken together, these various projects are a signal that the government seems to have business on its new AI push. But they also raise some questions. For example, in the case of data sharing, DSIT now says that the operating idea here will be a “common sense approach to information sharing.” Central government departments, such as HMRC (revenue and customs) and the Department of Business and Trade, can for example share data with each other and local councils in fraud investigations, or to better understand how businesses are doing and what programs can help. But what happens to data protection for individuals when data is shared in ways they don’t want? Another question that may surround Humphrey: now, DSIT says that some initial applications are only in the testing phase, but the big question is, to what extent will the government trust some AI conclusions? There are also other human challenges. As one former civil servant (who now works for an AI company) notes, past attempts to create programs that cross departments have not always worked. Collaboration, money and authority are ultimately the levers that will make or break the plan.

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