About the NHS AI Lab
£140 million investment in innovative pilots
NHSX’s NHS AI Lab is supporting the testing, evaluation and scale of promising AI-driven technologies through the £140 million AI in Health and Care Award. This includes automating early lung cancer detection and developing deep learning software that could improve the NHS Breast Cancer Screening Programme.
Accelerating the safe adoption of artificial intelligence in health and care
Artificial intelligence (AI) has the potential to make a significant difference to health and care. Through its ability to analyse large quantities of complex information, AI presents opportunities to improve care and productivity in health and care settings. We’re already seeing some great applications of AI, but more needs to be done to fully harness the benefits of these technologies so they can be used safely and ethically at scale.
To address the challenge, the NHS Artificial Intelligence Laboratory (AI Lab) was created to bring together government, health and care providers, academics and technology companies to help tackle some of the toughest challenges in health and care.
The role of the NHS Artificial Intelligence Lab
The NHS AI Lab believes in creating a sustainable health and care system which achieves better outcomes, equality and fairness for all. We want to support AI technologies that have potential to improve the quality of health and care services, while building a robust ethical and regulatory framework to ensure patient and citizen safety.
The Artificial Intelligence: How to get it right report brought together rich insight into how AI is being developed in the NHS. It looked at the greatest opportunities and risks, what challenges developers in this field face, and gave some guidance for the development and deployment of AI in health and care.
Building on the findings of the report, the AI Lab will help address the challenges faced by those developing, commissioning and adopting AI technologies. The lab will:
- support the development and scaling of the most promising AI solutions to the most challenging issues in health and care
- Identify the specific health and care problems that could benefit most from practical applications of AI, but are not currently being supported by these technologies
- provide guidance and evidence of good practice to industry and commissioners
- create environments to test AI technologies and evaluate the algorithms used by the NHS and care providers to ensure they meet required standards - reassuring patients and clinicians that AI technology is safe and effective
- clarify the regulatory and ethical frameworks for innovators so they can reach the market quickly, without compromising on safety
- build in-house expertise within the system to prototype and develop ideas
- use data and AI to support research into the early detection of disease and disease clusters
Understanding there are ethical and safety concerns associated with the use of AI in health and care, the Lab will follow the core founding principles of the NHS; addressing transparency, safety, privacy, explicability and bias. By building on existing foundations, such as our Guide to Good Practice, frameworks and best practice, we will ensure programmes maintain the support of the public, and position the NHS as a world leader in the development of safe and effective AI.
A broad range of techniques can be used to create Artificially Intelligent Systems (AIS) to carry out or augment health and care tasks that have until now been completed by humans, or have not been possible. These techniques include:
- inductive logic programming
- robotic process automation
- natural language processing
- computer vision
- neural networks
- distributed artificial intelligence
They present significant opportunities for keeping people healthy, improving care, saving lives and saving money. For example, they could help personalised NHS screening and treatments for cancer, eye disease and a range of other conditions. It’s not just patients who can benefit. AI can also support those working for health and care organisations, enabling them to make the best use of their expertise, informing their decisions and saving them time.