UPSC MainsGeneral Studies Paper IIIScience and TechnologyPractice question

Socio-Economic and Ethical Challenges of Generative AI

Examine the socio-economic and ethical challenges posed by the rapid adoption of Generative Artificial Intelligence (GenAI) in India. Suggest measures to ensure its inclusive and responsible development.

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The answer should introduce Generative AI highlighting its transformative potential alongside associated risks. It must examine the socio-economic and ethical challenges specifically in the Indian context, followed by concrete governance and policy measures to foster responsible, inclusive growth.

Model answer

406 words

Introduction

Generative Artificial Intelligence (GenAI) holds the potential to add 1.2 to 1.5 trillion dollars to India's GDP by 2030, transforming knowledge work, governance, and productivity. However, its rapid proliferation introduces profound socio-economic disruptions and ethical concerns that necessitate proactive governance to safeguard democratic and constitutional values.

Socio-Economic Challenges

  • Labour Disruption and Job Displacement: GenAI automates routine cognitive tasks, directly threatening entry-level IT coding, content creation, and Business Process Outsourcing (BPO) customer operations. Studies project that GenAI could transform tens of millions of jobs, automating nearly a quarter of routine service tasks.
  • Linguistic and Digital Divide: Western and English-dominated training datasets risk marginalising India's vast non-English speaking population across 22 scheduled languages, reinforcing digital exclusion for rural and vernacular users.
  • Sovereign Compute Dependency: Heavy reliance on imported GPUs and proprietary foreign foundation models creates technological lock-in, pricing out domestic micro, small, and medium enterprises (MSMEs) and compromising technological sovereignty.
  • Environmental and Resource Footprint: The exponential expansion of high-density AI data centres places severe strains on power grids and depletes freshwater reserves required for cooling in resource-stressed urban corridors.

Ethical Challenges

  • Misinformation, Synthetic Media, and Privacy Violations: Malicious deepfakes threaten electoral integrity, social cohesion, and individual dignity, directly impinging upon the right to privacy guaranteed under Article 21 through non-consensual synthetic media.
  • Algorithmic Bias and Discrimination: Training models on historical or unrepresentative datasets entrenches and amplifies entrenched caste, religious, and gender biases in automated hiring, policing, and credit evaluation systems.
  • Intellectual Property and Copyright Infringement: Unlicensed web scraping of creative works, indigenous cultural expressions, and regional literature deprives content creators of fair attribution and economic compensation.

Measures for Inclusive and Responsible Development

  • Strengthening Sovereign Infrastructure: Scale the IndiaAI Mission to democratise high-performance compute access for startups and researchers, alongside accelerating indigenous foundation models such as BharatGen.
  • Democratising Vernacular Data Commons: Leverage Mission Bhashini and the National Data Governance Framework Policy to curate high-quality, open-access datasets in regional Indian languages.
  • Enacting Risk-Based Regulatory Frameworks: Implement graded compliance through the proposed Digital India Act, mandate provenance protocols like C2PA cryptographic watermarking for synthetic media, and strictly enforce data consent under the Digital Personal Data Protection (DPDP) Act, 2023.
  • Large-Scale Workforce Reskilling: Expand initiatives like FutureSkills Prime to transition workers from task replacement to AI-augmented roles, preparing the workforce for collaborative human-AI ecosystems.

Conclusion

India must ground its artificial intelligence policy in NITI Aayog's 'AI for All' doctrine, ensuring that technological advances harmonize with constitutional morality, fundamental rights, and inclusive socio-economic progress.

Key facts to remember

statistic

Generative AI is projected to transform approximately 38 million Indian jobs by automating nearly 24% of tasks, predominantly impacting entry-level IT and BPO sectors.

EY (2025)
scheme
IndiaAI Mission (2024)

A national initiative with an outlay of Rs 10,372 crore aimed at establishing sovereign AI compute capacity, funding homegrown foundation models like BharatGen, and developing indigenous AI talent.

scheme
Mission Bhashini

A national public digital platform that leverages AI and natural language processing to break language barriers by developing open-source datasets and translation tools across 22 scheduled Indian languages.

Frequently asked questions

What is C2PA watermarking in the context of Generative AI?

The Coalition for Content Provenance and Authenticity (C2PA) framework provides open technical standards to embed cryptographic metadata and digital watermarks into synthetic media, verifying its origin and identifying manipulated content.