India Revises Economic Data Base Year to Boost AI Accuracy, Policy Decisions

The Ministry of Statistics and Programme Implementation is revising the base year for key economic indicators like inflation and the Index of Industrial Production. Secretary Saurabh Garg stated this update is crucial as the economy's structure changes with digitalization and new data sources like GST. The revision will provide more accurate and contemporary data for policymakers and economic projections. Furthermore, harmonized and updated data is essential as a raw material for effective artificial intelligence and machine learning applications.

Key Points: India Revises Economic Data Base Year for AI & Policy Accuracy

  • Base year update for economic indicators
  • Improves data for AI/ML applications
  • Reflects digital economy & GST changes
  • Aids policymakers with accurate data
2 min read

Revision of base year to improve accuracy, support AI use: MoSPI Secretary Saurabh Garg

MoSPI Secretary Saurabh Garg announces base year revision for inflation & IIP to improve data quality for AI, ML, and policymaking.

"For AI and ML, data is the key raw material. - Saurabh Garg"

New Delhi, January 30

inflation and the Index of Industrial Production is expected to significantly improve the quality and usability of data for artificial intelligence and machine learning applications, Secretary of the Ministry of Statistics and Programme Implementation Saurabh Garg said on Friday.

While speaking with ANI, Garg said these indicators are critical inputs for institutions that project future economic growth, while the government continues to publish actual growth rates for current and past years.

"It is extremely important to update base years because the structure of the economy changes over time, new data sources become available, and methodologies of data collection also evolve," he said.

"The rapid digitalisation of the economy has significantly altered economic structures, particularly with the expansion of digital sectors. The introduction of the Goods and Services Tax (GST) and the availability of new digital data sources have further transformed the statistical landscape," he noted.

Garg said the base year revision will enable policymakers and decision-makers to rely on more accurate and contemporary data. "This updation gives a much more correct and robust picture of the economy, which can then be used effectively by policymakers going forward," he said.

Garg also underscored the growing importance of updated and harmonised data in the context of artificial intelligence and machine learning. "For AI and ML, data is the key raw material. It is therefore essential that data is harmonised so that it can be effectively used by AI systems," he said.

Internally, MoSPI is already using artificial intelligence to improve the accuracy of data enumeration and to speed up decision-making processes, Garg added.

- ANI

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Reader Comments

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Sarah B
As someone working in data analytics, I can't stress enough how important harmonised data is for AI models. Garbage in, garbage out. If the government's own data is outdated, how can we build reliable predictive systems for the Indian market? This revision is critical for our tech future.
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Priya S
Hope this leads to better inflation calculations that actually reflect what common people pay for vegetables, petrol, and rent! Sometimes the official numbers and ground reality feel worlds apart. 🤞
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Rohit P
While the intent is good, I have a respectful criticism. The focus seems heavily on AI and policymakers. What about making this data more accessible and understandable for the average citizen? We need simple dashboards and explanations, not just raw data for experts.
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Ananya R
Finally! The economy has changed so much since the last base year revision. The gig economy, digital services, startups... none of this was captured properly. This will help in better planning and resource allocation. Thumbs up!
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Karthik V
Using AI to improve data collection is a smart move. Can reduce human error and speed things up. But the key is transparency - we must know how these AI models work and what data they are trained on. Hope MoSPI will be open about their methodology.

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