Analysis of Algorithmic Impact: A Case Study in Healthcare Services
The Alan Turing Institute has presented a groundbreaking proposal for an algorithmic impact assessment (AIA) system, designed to evaluate and govern the algorithmic uses of public-sector data in the healthcare context of the UK National Health Service (NHS). This system is planned to be introduced by the NHS's proposed National Medical Imaging Platform (NMIP) by 2023.
The AIA process for the NMIP is a novel approach, designed to be adaptable to various sectors and contexts. It extends beyond the healthcare context, and may serve as a model for AIAs in other sectors. The goal is to produce benefits for society, governments, public bodies, technology developers, and the people represented in the data.
The AIA process is intended to ensure that the technologies and their outcomes positively affect those affected by the data. It may help to mitigate potential risks and biases associated with AI technologies in healthcare. The process includes actionable steps, provisions for general considerations in AIAs, and is not limited to healthcare-specific considerations.
The NMIP's AIA is designed to promote transparency and accountability in the use of data and AI technologies in healthcare. It may lead to more equitable and effective use of data and AI technologies in healthcare, and may influence the development of AIAs in other public and private sectors.
The AIA process aims to evaluate and govern the algorithmic uses of public-sector data, and may help to ensure that the algorithmic uses of data are ethically and legally sound. The process for the NMIP includes provisions for AIAs outside the UK National Health Service (NHS). These actionable steps are applicable to the use of AIAs in other public and private-sector contexts.
In summary, the AIA process for the NMIP is a comprehensive approach to AIAs, designed to ensure that the algorithmic uses of data are beneficial, transparent, and accountable. The proposed system, if implemented, could revolutionize the way data and AI technologies are managed in the healthcare sector and potentially influence other sectors as well.
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