India is on the path to becoming the third-largest economy around 2027 as estimated by many. The GDP estimates based on an outdated base would not adequately capture new activities being undertaken in the economy.
India's Economic Growth and GDP Measurement
A five Trillion economy: India aims to become a 5 trillion dollar economy by 2025, though COVID-19 has created hurdles.
Future predictions: Projected to be the third-largest economy by 2027.
Goals defined: Achieving this goal requires accurate GDP measurement and collaboration among stakeholders.
Urgent Need for Base Year Revision
Base issue: Current GDP calculation uses an outdated base year (2011-12).
Lack of accurate representation: Delays in base year revision hinder accurate representation of new economic activities.
Factors to be considered: Recent government investments and foreign capital inflow require proper inclusion in GDP estimates.
Improving GDP Compilation and Validation
Need of revised base: Revision of the base year is complex, requiring assessment of data sources and new data sets.
Steps forward: Initiatives like Supply Use Tables (SUTs) should be validated before GDP release to reduce discrepancies.
An Agency must be responsible: Suggests forming advisory committees and working groups for the base year revision process.
One of the prominent geopolitical risks of AI is its capacity to produce deepfakes, which can be any audio-visual content that depicts real individuals in fictitious situations. This can poses a geopolitical risk across nations.
Risks of Deepfakes in Geopolitics
Geopolitical Threat of Deepfakes: Deepfakes, realistic fake videos, pose a significant geopolitical risk.
Global Recognition of Deepfake Risks: G20 nations and organizations like Europol recognize deepfake threats.
Disruption and Vulnerabilities: Deepfakes can disrupt institutions, jeopardize elections, and impact financial markets.
Challenges in Detecting Deepfakes
Technological glitch: Detecting deepfakes is challenging due to evolving technology.
Detection methods have limitations, including vulnerability to compression and distortion.
Process and identification: Deepfake creation involves an iterative process, making detection more difficult.
Combating Deepfakes
Cross-border issues: Banning deepfakes is ineffective due to cross-border content
Agencies involved: The US NSA suggests using a combination of detection and provenance methods.
Funding mechanism: G20 nations should consider financing deepfake detection, similar to funding energy transitions, to safeguard digital truth.