The Department for Science, Innovation, and Technology (DSIT) has launched a competition offering £400,000 for investment in projects to tackle bias and discrimination in AI.
It said companies can apply for shares of the money, at a maximum of £130,000 each, under the Fairness Innovation Challenge.
The move reflects significant concerns over the potential for bias as public and private sector organisations increase their use of AI solutions.
DSIT said the challenge will encourage participants to build a wider social context into the development of their models from the off.
It will focus on two areas. The first involves a partnership between DSIT and King’s College London that will offer participants the change to work on potential bias in a generative AI model, developed by Health Data Research UK, trained on anonymised records of patients to predict health outcomes.
The second is a call for open use cases under which applicants can propose new solutions in their unique models and areas of focus, including tackling fraud, building law enforcement AI tools and helping employers develop fairer recruitment systems.
This follows the publication of the AI Regulation White Paper earlier this year.
Opportunities and risks
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.
“While there are a number of technical bias audit tools on the market, many of these are developed in the US, and although companies can use these tools to check for potential biases in their systems, they often fail to fit alongside UK laws and regulations.
“The challenge will promote a new UK led approach which puts the social and cultural context at the heart of how AI systems are developed, alongside wider technical considerations.”
