Local councils are picking up the AI mantle to help unleash this revolutionary technology across the UK – to turbocharge the Plan for Change and deliver a decade of national renewal.
The latest transparency data – published by the Department for Science, Innovation and Technology (DSIT) –shows that councils are wasting no time in putting the weight of the public sector behind AI and finding new and innovative ways to make it work for working people.
It shows that AI is being used to identify when a pensioner has had a fall, to stop people fall into rent arrears, to map which houses need loft insulation, to give people bigger bins, and – instead of taking people’s jobs – to help them find work in social care.
The publication of records follows the Technology Secretary setting out a blueprint for how his department will help the public sector use technology to transform public services, targeting £45 billion in potential productivity savings.
The plan will see a new team, housed in the Department for Science, Innovation and Technology (DSIT), cut across barriers to join up public services, including those provided by local councils, so people do not have to tell dozens of organisations the same thing.
The team will first start by looking at services used by people with long term health conditions across organisations like the NHS, Department for Work and Pensions, local councils and more.
As the digital centre of government, the Department for Science, Innovation and Technology (DSIT) will champion innovation, like that shown by the London Borough of Sutton, and help to spread it around the country so it can be used to improve public services and drive the Government’s Plan for Change.
Speaking from a trip to see the Tech Enabled Care solution in Sutton, AI and Digital Government Minister Feryal Clark said:
AI has immense potential to make our lives easier and improve public service. The technology we are together sharing with the public today includes shining examples of innovation that does everything from speeding up crucial applications for bigger bins, to helping people live independently.
Being transparent with the detail of how we are putting AI to work in public services is crucial to our plans to use technology to improve public services, which is a key part of our Plan for Change. Other initiatives include AI-enabled fridge sensors and connected kettles are being used to detect changes in the daily routines of vulnerable people that could indicate a decline in health and ultimately lead to a fall, thanks to technology used by the London Borough of Sutton.
Helping people who would otherwise need additional care, the technology uses sensors to spot changes in behaviour, like missed meals, a skipped cup of tea or whether a door has been left open for too long, before AI analysis is used to detect whether something might be wrong. An alert is then sent to close family members or carers so they can stop by to check on how they are and offer additional support if needed.
Details of the technology, which was developed by Loughborough tech company The Access Group and Medequip Connect, have been released today alongside nine other public sector organisations setting out how they use AI and algorithmic tools.
Councillor Marian James, Lead Member for People Services at the London Borough of Sutton said:
Research shows that people live well for longer when they can maintain their sense of independence and dignity by remaining in their own home. That’s why we are using the latest digital technology to enable our residents to continue living their lives independently within the comfort of their own home, but with the peace of mind that support is available when they need it.
The pressures facing our adult social care services show no sign of easing, so I’m proud the Council is taking this forward-thinking approach to find solutions that will reduce the pressure on the system, as well as being beneficial for our residents.
Among the records published today, West Berkshire Council also shared how it is using technology to help residents get a bigger black bin more quickly, if they are eligible.
A tool, built entirely in-house by the council, takes in information from an online application form, like the number of people living in a home, and the number of children in nappies, to automatically rule out people who might not be eligible for a bigger bin.
Though, people whose applications are declined can still appeal the crucial decision, and have a human quickly look at their request. By speeding up the processing of requests, it makes sure families with newborns can get a bigger bin to handle the increased waste much more quickly.
Other records published today detail chatbots used to help people apply for social care qualifications in Wales, and algorithmic tools to help councils more accurately predict the cost of adult care, so they can better manage their budgets.
Minister of State for Care, Stephen Kinnock said:
Around a third of adults over 65 will have at least one fall a year. This can be devastating and doesn’t just risk broken bones, but a loss of confidence and independence in older people. I am determined that we harness cutting-edge technology to protect them – and this groundbreaking AI will help to stop accidents before they happen and cut down on hospital visits.
Our Plan for Change will drive forward this kind of innovation, transform the NHS, and ensure people can live safely and independently.
Andy Sparkes, Managing Director, Local Government, The Access Group, said:
We’re delighted to support Sutton Council’s ambitious approach to AI and technology-enabled care, which offers a personalised service that enables individuals to live independently for longer. AI and machine learning have the potential to enable all local authorities to shift their approach to care from the traditional reactive model to a more proactive approach that allows for early intervention. By scaling these proven examples of success, councils can reduce the pressure on current services and empower residents to remain in their homes for as long as possible.