RBI Governor Stresses on Removal of Biases in AI and Machine Learning

Shaktikanta Das highlighted the growing use of statistics as a preferred tool for making inferences in various fields

Update: 2024-06-28 16:20 GMT
Reserve Bank of India.( DC File Photo)

Mumbai:  The Reserve Bank of India (RBI) Governor Shaktikanta Das on Friday called for addressing ethical considerations and eliminating biases in algorithms while enhancing capacity in artificial intelligence (AI) and machine learning (ML).

Speaking at the 18th Statistics Day Conference organised by the RBI on Friday, Das said, “Under the Reserve Bank’s aspirational goals for RBI@100, we aim to develop cutting edge systems for high frequency and real-time data monitoring and analysis.”

“The focus now is naturally on enhancing capacity in artificial intelligence (AI) and machine learning (ML) techniques and analysing unstructured textual data. While doing so, ethical considerations need to be addressed and biases in algorithms need to be eliminated,” said Das.

He highlighted the growing use of statistics as a preferred tool for making inferences in various fields. He further noted that the discipline has evolved from simply collecting facts to focusing more on interpreting data and drawing conclusions, especially considering the level of uncertainty involved.

He said the central bank 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 use of alternative and unconventional data sources proved to be invaluable during the most severe phases of the COVID-19 related lockdowns and restrictions.

“In fact, their utility extends beyond periods of crisis. Data management systems need to keep pace with the use of unconventional data sources as policy inputs. While doing so, we have to be mindful of the importance of eliminating noise and capturing the signals from high frequency indicators,” he said.


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