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Fairness Innovation Challenge: Tackling Bias in AI Systems

Opens:
16/10/2023
Closes:
13/12/2023
Sectors:
General & Misc
Project Size:
Up to £130,000

Quick Overview:

• Eligibility: Exclusively open to UK-registered organisations.

• Objective: To drive the development of innovative solutions addressing bias and discrimination in artificial intelligence (AI) systems.

• Key Dates:

• Competition Opens: 16 October 2023

• Competition Closes: 13 December 2023, at 11:00am UK time

Innovate UK, in collaboration with the Centre for Data Ethics and Innovation (CDEI), is investing up to £400,000 in projects aimed at mitigating bias and discrimination within AI technologies. The focus is on encouraging socio-technical approaches to fairness and exploring how strategies can comply with relevant UK laws including the Equality Act 2010, the UK GDPR, and the Data Protection Act 2018.

Funding and Project Size:

• Funding Type: Grant

• Project's Total Costs: Up to £130,000

What They Are Looking For:

• Proposals must detail socio-technical interventions for detecting and mitigating bias in selected use cases.

• The approach should align with UK ethical and legal standards for fairness.

• Clarity on the chosen methodology, whether it’s a specific fairness metric or socio-technical interventions, is essential.

Key Criteria:

• Proposals must address bias and discrimination in either provided healthcare use cases or open use cases.

• At least two stages in the process of addressing bias and discrimination must be covered: data access for bias detection, bias detection, bias mitigation, and ongoing monitoring.

• Diverse socio-technical interventions like participatory data collection, governance interventions, and more are encouraged.

Research Categories:

• The challenge seeks proposals with a socio-technical focus that considers broader historical, social, and cultural contexts.

What They Will Not Fund:

• Projects that do not adopt a socio-technical approach to fairness.

• Proposals that don't address at least two stages in the process of mitigating bias and discrimination.

• Projects that do not show the potential for positive economic or societal impact.

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