UK launches funding challenge for tackling AI bias

The first round of submissions to the Department for Science, Innovation, and Technology’s Fairness Innovation Challenge, delivered through the Centre for Data Ethics and Innovation (CDEI), will focus on the development of new approaches to making fairness central to the development of AI models.

The challenge will seek to support up to three UK businesses with projects centred on AI ethics, with successful bids receiving up to £130,000 each.

The government said it hoped the successful projects will help tackle the threats of bias and discrimination by building a wider social context into the development of their models.

The challenge will focus on two areas, including a new partnership with King’s College London to offer participants from across the UK’s AI sector the chance to work on potential bias in a generative AI model.

The model was developed with Health Data Research UK, with the support of NHS AI Lab, and is trained on the anonymised records of more than 10 million patients to predict health outcomes.

The second part of the challenge is a call for ‘open use cases’, where applicants can propose new solutions to tackle discrimination in their own AI models and areas of focus.

The CDEI is also working with the Information Commissioner’s Office (ICO) and the Equality and Human Rights Commission (EHRC) to deliver the challenge.

Fairness in AI systems is one of the government’s key principles for AI, as set out in the AI Regulation White Paper, and the UK is hosting an international AI safety summit later this year.

The Fairness Innovation Challenge closes for submissions at 11am on Wednesday 13th December, with successful applicants notified of their selection on 30th January 2024.

Minister for AI Viscount Camrose said: “The opportunities presented by AI are enormous, but to fully realise its benefits we need to tackle its risks.  

“This funding puts British talent at the forefront of making AI safer, fairer, and trustworthy. By making sure AI models do not reflect bias found in the world, we can not only make AI less potentially harmful, but ensure the AI developments of tomorrow reflect the diversity of the communities they will help to serve.”