1.5 AI and Machine Learning 63.
Used responsibly, data-driven artificial intelligence (AI) systems have the potential to bring incredible benefits to our lives.
Case study: Using AI technology to improve patient care Researchers from Moorfields Eye Hospital and the University College London Institute of Ophthalmology recently made a breakthrough in patient care using AI technology. The researchers successfully trained machine learning technology on thousands of historic depersonalised eye scans to identify signs of eye disease and recommend how patients should be referred for care. This AI system can recommend the correct referral decision for over 50 eye diseases with 94% accuracy, matching world-leading eye experts. This innovation has the potential to revolutionise the way that professionals carry out eye tests, allowing them to spot conditions earlier and prioritise patients with the most serious eye diseases before irreversible damage sets in.
64.
The development of AI and machine learning applications is contingent on data, and places specific demands on its collection, curation and use. A National AI Strategy will be published later this year to set out how the government plans to build on the UK’s leadership in AI. Whereas the National AI Strategy will address a wide range of issues arising from the emergence of AI technologies, this consultation focuses on the interplay of AI technologies with the UK's data protection regime.
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The right reforms to the UK’s data protection framework can help organisations building or deploying AI tools to innovate responsibly, manage data-related risks at every stage of the AI lifecycle, and ensure that individuals can trust that their personal data is used responsibly. Reforms should aim to help organisations building or deploying AI tools to interpret existing data regulation. Reforms should also simplify legislation, where appropriate, so potential new entrants to data-driven markets are not deterred and beneficial, responsible data use is not impeded.
66.
There are multiple, sometimes conflicting, definitions of artificial intelligence. For the purpose of this document, the following terminology is in use: a. Artificial intelligence: the use of digital technology to create systems capable of performing tasks commonly thought to require intelligence. AI is constantly evolving, but generally it involves machines using statistics to find patterns in large amounts of data, and the ability to perform repetitive tasks with data without the need for constant human guidance 14 b. Machine learning: a subset of AI referring to the development of digital systems that improve their performance on a given task over time through experience. Machine
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Government Digital Service, Office for Artificial Intelligence , ‘A guide to using artificial intelligence in the public sector’, 2019
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