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A week after the British government announced a garbage plan to make large investments in AI, is laying out more details on how it will take shape in the public sector. On the agenda: AI assistants to speed up public services; data sharing matters in siled departments; and a new set of AI tools – named “Humphrey” after a character in an old UK TV political sitcom – to speed up the work of civil servants.
The plans will be formally unveiled 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 The UK Government’s AI site to check the progress of some of the projects, you will see that most of the efforts so far seem to be in very early stages, either in limited trials or in a testing phase; others are still nascent. For example, a plan to bring more AI services into the client side of the NHS is only at the stage of a “charter” committed to the concept.
Some include links to Github repositories to check out some of the work to date. It is not clear how many people in total are working on these projects, nor what third-party tools (such as LLMs) are used. (We’ve asked these questions and will update when we know more.)
At their heart, the projects are all about efficiency. The government, DSIT said, currently spends around £23 billion a year on technology, and the idea will be to redistribute that money in a more modern way.
“Slow technology has hampered our public services for far too long, costing us all a fortune in time and money… Not to mention the headaches and stress we’re left with after being put on hold or forced to make a trip to fill out a form,” said Peter Kyle, the Secretary of State for DSIT, in a statement. “My Department will put AI to work… We will use the technology to challenge the no-nonsense approach the public sector takes to sharing information and working together to help the people it serves.”
Plans include a new team at DSIT to lead the projects, sort of DOGE in the United States, but designed and run by government people rather than tech tycoons.
DSIT develops initially in three areas:
1. The work of government employees. Humphrey, named after the ironic and intelligent assistant played by the late Nigel Hawthorne in “Yes, Minister” and later “Yes, Prime Minister”, is a set of applications aimed at reducing the typical daily workload of civil servants, especially around the vast amount of data that are required to be read. and process as part of their work.
“Consult” is designed to read and summarize “thousands” of responses to consultations in hours (the responses, which can be long and numerous, are a central part of how the government takes into account the feedback of stakeholders and the public). “Parlex” will allow them to question and read the conversations in the Parliament related to the projects or other policy documents they are working on. “Minute” is a secure transcription service to take notes from your many hours of meetings. “Redbox” helps them prepare briefings and policy documents. And “Lex” allows you to consult the relevant legal data.
2. Another thread of the drive for efficiency will be around speeding up public services. The idea here is to take aim at red tape, of which there is a lot in the UK, such as the 100,000 calls that the tax authorities receive every day, or the need for people to appear in person to register a death, or (oddly. ) run ads in local newspapers as part of the process of getting a license to drive a truck.
DSIT’s thinking is that review processes like these with more AI-powered automation could save £45 billion a year. (It is not clear if that estimate is before or after deducting the cost of building and running AI services).
3. A final area will be focused on more collaboration between departments in the aid of data sharing to speed up how the services proceed, and then how they work.
Together, the various projects are a sign that the government seems to mean business on its new AI push. But they also raise a number of questions.
For example, in the case of data sharing, DSIT for now says that the operative idea here will be “a common sense approach to sharing information”. Central government departments, such as HMRC (revenue and customs) and the Department for Business and Trade, may for example share data with others and local councils in fraud investigations, or to understand better how businesses are doing and what programs might help. But what happens to data protection for individuals when data is shared in ways you didn’t think it would be?
Another possible question is around Humphrey: now, DSIT said that some of the first apps are only in the testing phase, but the big question will be, how far the government will trust some of the conclusions of the AI?
There will be even more human challenges. As a former civil servant (who now works for an AI company) notespast efforts to create programs that cut across departments have not always worked. Collaboration, money and authority are ultimately the levers that will make or break any of these plans.
