RBI Governor Urges For Removal Of Biases In Algorithms

The volume of digital data stored as well as the storage capacity are growing at an exponential pace, bringing forth new challenges along with new opportunities, Shaktikanta Das says.

RBI Governor Shaktikanta Das. (Source: RBI/X)

Reserve Bank of India Governor Shaktikanta Das has highlighted the importance of removing biases in algorithms due to the increasing utilisation of artificial intelligence and machine learning.

At the 18th Statistics Day Conference, Das also underscored the expanding use of statistics as a primary method for making conclusions in various sectors. He said the field evolved from simply gathering data to concentrating on analysis and drawing conclusions while considering uncertainties.

"Looking ahead, the year 2025 has a special significance for compilation of official statistics the world over. Global efforts are expected to culminate in new global standards for compilation of macroeconomic statistics, especially for national accounts and balance of payments," he said, adding that the team in the RBI is closely tracking these developments.

He said the RBI is making efforts to harness the availability of huge computing power and growing digital footprints to analyse measures of expectations, sentiment indicators and policy credibility measures from alternative data sources.

The governor emphasised that the volume of digital data stored as well as the storage capacity are growing at an exponential pace, bringing forth new challenges along with new opportunities.

"The focus now is naturally on enhancing capacity in artificial intelligence and machine learning techniques and analysing unstructured textual data. While doing so, ethical considerations need to be addressed and biases in algorithms need to be eliminated," he said.

The RBI has ventured into AI/ML analytics in multiple areas. Under the RBI's aspirational goals for RBI@100, he said the central bank is aiming to develop cutting-edge systems for high-frequency and real-time data monitoring and analysis.

(With inputs from PTI.)

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