UK-India Cooperation Towards a Fair AI Horizon- Comprehensive Workshop

Problem statement Bias Detection Hackathon

The Central Banks of India and the UK are dedicated to ensuring that all financial institutions adhere to principles of fairness, transparency, and equality in their lending practices. Despite stringent regulations, biases—whether conscious, unconscious, or algorithmic—can still result in discriminatory lending practices. These biases may disproportionately impact certain demographic groups or regions, leading to unequal access to credit and perpetuating financial exclusion and economic inequality. To address this issue, the UK has been actively working on enhancing financial inclusivity, particularly in underserved communities and regions, through key initiatives like the Financial Services and Markets Bill. Similarly, microfinance institutions (MFIs) play a crucial role in India’s socio-economic landscape by providing financial services to underserved and low-income populations. For both the countries, biases can exacerbate socio-economic disparities. To ensure consistent enforcement of fair lending regulations and safeguard the principles of equality and transparency in the financial sector, the Central Bank requires a regulatory oversight platform powered by advanced algorithms. This platform would audit and monitor lending practices across all financial institutions, automatically identifying deviations from fair and unbiased practices.

Develop innovative solutions to equip the central bank with tools that ensure consistent enforcement of fair lending regulations, safeguarding the principles of equality and transparency in the financial sector.

Problem statement Fairness Assessment Challenge

Problem statement for fairness assessment: India’s healthcare sector faces significant challenges, including inadequate services, staff shortages, and insufficient infrastructure. In contrast, the UK's National Health Service (NHS) has extensive experience in providing comprehensive healthcare but is also grappling with biases, particularly in the realm of AI-driven telemedicine. To address these challenges, both countries are exploring the potential of telemedicine as a tool to provide equitable healthcare services. However, biases such as algorithmic bias, access disparities, and cultural/language barriers still exist. The Indian Medical Association (IMA) and the NHS are interested in developing an algorithm that can identify, track, and mitigate biases in telemedicine platforms used in both countries. This algorithm should analyze data from telemedicine interactions to detect patterns of bias and provide actionable insights to healthcare providers, ensuring fair and effective telemedicine services for all, regardless of geographical location or cultural background.