RBI Governor Shaktikanta Das highlighted efforts by the RBI to harness digital footprints and computing power to analyze expectations, sentiment indicators, and policy credibility from alternative data sources. The exponential growth in digital data and storage capacity presents both new challenges and opportunities
Mumbai: RBI Governor Shaktikanta Das on Friday underscored the critical need to eliminate biases in algorithms as artificial intelligence (AI) and machine learning (ML) continue to advance.
Speaking at the 18th Statistics Day Conference, hosted by the Reserve Bank of India (RBI), Das pointed out the ever-growing use of statistics as a tool for inference across diverse fields. He stated that the discipline has evolved from mere data collection to focusing on interpretation and inference, considering the inherent uncertainties involved.
This evolution, as per Das, has helped embed statistics into various other significant disciplines. Increased computational power is now being leveraged alongside statistical methods to boost decision-making efficiency and enhance user experiences in many sectors.
Das remarked on the crucial year 2025, tagging it as pivotal for global standards in macroeconomic statistics compilation, especially for national accounts and balance of payments. He assured that RBI is closely monitoring these developments as part of its strategic initiatives.
He also highlighted efforts by the RBI to harness digital footprints and computing power to analyze expectations, sentiment indicators, and policy credibility from alternative data sources. The exponential growth in digital data and storage capacity presents both new challenges and opportunities, Das noted.
Addressing future challenges, he emphasized the central bank’s focus on enhancing AI and ML techniques and analyzing unstructured textual data, while also stressing the elimination of biases in algorithms. As part of its RBI@100 aspirational goals, the Reserve Bank aims to develop cutting-edge systems for high-frequency and real-time data monitoring and analysis.