As the NHS begins to test different ways of looking at the ethical use of AI in healthcare, potential prejudice in the systems will hopefully be removed altogether for the first time.

AIAs developed by the Ada Lovelace Institute will be used to assess the dangers and prejudice present in AI operations prior to looking at NHS statistics.

“The NHS aims to remove potential prejudice in AI healthcare systems for the first time“

Parliamentary Under-Secretary of State for Innovation, Lord Kamall, explained that “We must tackle biases which have the potential to do further harm to some populations as part of our mission to eradicate health disparities. The UK is at the forefront of adopting new technologies in a way that is ethical and patient-centred. By proactively addressing risks and biases, we are ensuring we create a system of healthcare which works for everyone.”

The NHS will help academics and designers in working with both patients and healthcare industry experts in the initial phases of the programs' development, it is at this stage where modifications can be made to adapt to feedback. This will have a positive impact on the individuals' interaction with AI and its clinical amalgamation.

Leader of the AI ethics initiative, Brhmie Balaram, expressed that “the algorithmic impact assessment will prompt developers to explore and address the implications of AI systems as a condition of accessing NHS data. Following a commission from the NHS AI Ethics Lab, the Ada Lovelace Institute maps out a detailed process for using AIAs in the real-world. It is designed to help developers and researchers consider and account for the potential impacts of proposed technologies on people, society and the environment.”

Interim lead at Ada Lovelace Institute, Octavia Reeve, also stated that “algorithmic impact assessments have the potential to create greater accountability for the design and deployment of AI systems in healthcare, which can in turn build public trust in the use of these systems, mitigate risks of harm to people and groups, and maximise their potential for benefit.”

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