Theme: Responsible and Trustworthy AI

In this blog, we trace the emerging contours of India’s domestic approach to governing AI in finance and identify the priorities that should shape the next phase of policy thinking, in light of alarm bells triggered by Mythos, and OpenAI’s cybersecurity initiative, Daybreak.

The growing prominence of Responsible and Trustworthy AI (RTAI) frameworks reflects increasing recognition of these harms. Contemporary RTAI approaches recommend safeguards across the lifecycle of AI systems to ensure explainability, transparency, contestability, auditability, and human oversight, while reducing the potential for bias and discrimination.

The paper explores what RTAI means in the context of digital lending. The first section compiles principles of RTAI along with its essential components. The next section maps relevant tools for each principle. These tool recommendations can help lenders implement RTAI practices in their operations.

The Consultation Paper sets out the landscape of use cases of AI prevalent in the Indian Securities Market.

Fairness, explainability and human-in-the-loop principle are vital elements of Responsible AI

This Whitepaper unpacks what RTAI would mean in the context of digital lending. While the term Responsible AI has been adequately conceptualized in academia and elsewhere, it still needs to be coherently contextualized to specific domains.

The response presents our thinking on the governance of artificial intelligence (AI). It is divided into two parts. Part A summarises our key inputs which are also presented below in the form of this write-up. Part B provides a section-by-section paragraph-wise detailed feedback as per the Ministry’s Consultation Form requirements.

Establishing principle-level guidance on operationalising Responsible AI would induce clarity and confidence