The power of AI lies in its ability to learn patterns from large amounts of data, in a way that exceeds human abilities. However, this also means the reliability of AI algorithms is closely linked to the data it is trained upon, and may perform poorly when confronted by new data examples – a failure of ‘AI generalisability’. To be sure that algorithms work for everybody, we need to test them on datasets that represent the diverse range of people it is intended to be used in.
Want to find out more?
Here's a video with Dr Joe Alderman talking about the STANDING Together Project
Health Data Research Midlands Inequalities and Diversity Webinar, October 2023
Defining best practice for dataset curation and use
Mapping dataset deficiencies in priority disease areas
Identifying and overcoming barriers for implementation
Conduct semi-structured interviews with dataset curators/users about implementing the recommendations
Funding and Support