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Global Cooperation Essential to Tackle AI Bias and Risks

Modi emphasizes responsible AI use and diverse datasets to safeguard India's pluralism and counter inherent biases.
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Gopi
••7 mins read
AI for All: Human-Centric Innovation Driving India’s Development and Global Leadership
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1. AI as a Civilisational Turning Point

Artificial Intelligence (AI) is being positioned as a transformative technological force capable of expanding human capability across sectors such as healthcare, education, agriculture, and governance. However, its scale and speed also pose systemic risks to social stability, employment patterns, and democratic accountability if left unguided.

The framing of AI at the India AI Impact Summit 2026 around the motto “Sarvajan Hitay, Sarvajan Sukhaye” reflects an attempt to anchor technological progress within India’s civilisational ethos of welfare and collective well-being. This shifts the discourse from innovation-centric growth to impact-centric governance.

By hosting the first global AI summit in the Global South, India seeks to shape global AI governance narratives from a development-first perspective. This is significant because AI systems rely on global data flows but disproportionately benefit early adopters in advanced economies.

“Technology exists to serve humanity, not replace it.” — PM Narendra Modi

If AI is pursued solely as an innovation race without embedding equity and welfare considerations, it may widen global and domestic inequalities, erode trust in institutions, and weaken social cohesion.

GS Linkages:

  • GS3: Science & Technology
  • GS2: Governance
  • IR: Global digital governance

2. AI and India’s Developmental Transformation (Viksit Bharat 2047)

AI is being integrated into India’s long-term development vision, particularly in bridging structural deficits in health, education, agriculture, and rural inclusion. Rather than being viewed as a future opportunity, AI is framed as a present development instrument.

In healthcare, AI-enabled early detection systems are assisting in screening for tuberculosis, diabetic retinopathy, epilepsy, and other conditions at primary and district health centres. In education, personalised learning platforms in Indian languages aim to improve outcomes in rural and government schools.

Agriculture and allied sectors are witnessing AI integration through initiatives like Bharat Vistaar (crop advisory, soil analytics, weather intelligence) and private sector adoption, such as Amul using AI to support 36 lakh women dairy farmers with real-time cattle health guidance in Gujarati.

This approach attempts to dissolve divides—urban-rural, linguistic, and socio-economic—by embedding AI within grassroots service delivery systems.

If AI remains confined to urban enterprises and high-income users, it risks deepening the digital divide; however, when integrated into public service systems, it becomes a tool of distributive justice.

Key Sectors Impacted:

  • Healthcare diagnostics
  • Education personalisation
  • Agricultural advisories
  • Women-led dairy cooperatives
  • Heritage digitisation

GS Linkages:

  • GS2: Social sector schemes
  • GS3: Agriculture, S&T
  • GS1: Culture (heritage digitisation)

3. AI Bias, Diversity and Inclusive Data Governance

AI systems can perpetuate biases related to gender, language, and socio-economic background. In a country as diverse as India, bias risks are amplified because datasets skewed toward English-speaking or urban populations may exclude rural and regional language users.

India’s diversity—linguistic, cultural, regional—requires AI systems trained on plural datasets. The emphasis on regional language AI development and research on fairness reflects a structural response to contextual bias.

Globally, AI governance requires cooperation because cross-border data and algorithms shape local outcomes. India’s participation in multilateral forums indicates a preference for collective rule-setting rather than unilateral regulation.

Unchecked bias in AI can institutionalise discrimination at scale, undermining constitutional principles of equality and social justice.

Emerging Corrective Measures:

  • Creation of diverse datasets
  • AI development in regional languages
  • Academic research on fairness and bias
  • Global awareness through AI Impact Summit

GS Linkages:

  • GS2: Rights, equality
  • GS3: Technology ethics
  • Essay: Technology and social justice

4. Convergence of Digital Public Infrastructure (DPI) and AI

India’s Digital Public Infrastructure (DPI)—Aadhaar, UPI, and other digital public goods—was built on open, interoperable, and scalable architecture. Designed to serve 1.4 billion people, it offers a foundational layer upon which AI can be integrated.

The convergence of AI and DPI can improve welfare targeting, fraud detection, predictive infrastructure maintenance, and urban planning. However, scaling AI atop DPI requires strong data protection and regulatory safeguards.

India positions its DPI model as a scalable template for the Global South, demonstrating how digital public goods can enable inclusive AI adoption rather than proprietary monopolisation.

If AI is layered over weak digital systems without privacy safeguards, it risks surveillance excesses and governance failures; conversely, when anchored in interoperable public goods, it enhances state capacity and transparency.

Replicable DPI Principles:

  • Open architecture
  • Interoperability
  • Scale and inclusion by design
  • Strong regulatory frameworks

GS Linkages:

  • GS2: E-governance
  • GS3: Digital economy
  • IR: South-South cooperation

5. AI and the Transformation of India’s IT Sector

India’s IT sector, a major driver of services exports, is projected to reach $400 billion by 2030, supported by AI-enabled outsourcing and automation.

AI is not seen as replacing the IT sector but transforming it—from service delivery to AI product development and platform creation. Enterprise-grade AI adoption still depends heavily on incumbent IT firms solving complex business problems.

Government interventions under the IndiaAI Mission include expanding GPU access, establishing four Centres of Excellence (Healthcare, Agriculture, Education, Sustainable Cities), and five National Centres of Excellence for Skilling.

Failure to upgrade from service-led growth to AI product leadership could trap India in a lower value-added segment of the digital economy.

Policy Measures:

  • IndiaAI Mission
  • Expanded compute infrastructure
  • Semiconductor push
  • Electronics PLI
  • AI skilling initiatives

GS Linkages:

  • GS3: Industry, innovation
  • Economy: Services exports

6. AI Safety, Regulation and Ethical Governance

AI misuse—deepfakes, cybercrime, manipulation—poses risks to national security, democratic processes, and vulnerable groups. Therefore, governance must balance innovation with safety.

India has initiated structured regulatory mechanisms, including the IndiaAI Safety Institute (January 2025) and rules mandating watermarking of AI-generated content. The Digital Personal Data Protection Act strengthens user rights in the digital ecosystem.

The emerging framework emphasises:

  • Human oversight
  • Safety-by-design
  • Transparency
  • Prohibition of AI misuse for crime or terrorism

Without proactive safeguards, AI misuse can erode trust in digital systems, destabilise democratic discourse, and disproportionately harm women, children, and the elderly.

GS Linkages:

  • GS3: Internal security
  • GS2: Regulatory institutions
  • Ethics (GS4): Accountability in technology

7. Employment, Skilling and Demographic Dividend

Concerns among youth about job displacement are acknowledged. However, the policy stance emphasises technological transformation rather than job elimination.

India ranked 3rd in the Stanford Global AI Vibrancy Index 2025, reflecting growth in AI R&D, talent, and economic integration. Skilling and re-skilling initiatives are central to adapting the workforce to AI-driven changes.

Historical experience suggests technological revolutions alter job structures rather than eliminate work entirely. However, transitions require institutional preparedness.

If skilling lags technological adoption, demographic advantage could convert into unemployment stress; conversely, proactive skilling can turn AI disruption into demographic opportunity.

Strategic Responses:

  • Large-scale skilling initiatives
  • AI-focused training institutions
  • Industry-academia collaboration

GS Linkages:

  • GS3: Human resource development
  • Economy: Employment trends

8. AI and Aatmanirbhar Bharat

The vision for AI within Aatmanirbhar Bharat rests on three pillars: sovereignty, inclusivity, and innovation. The goal is not only AI consumption but AI model creation and global deployment.

This includes strengthening domestic compute capacity, semiconductor manufacturing, and AI startups. The long-term objective is positioning India among the top three global AI powers.

Strategically, technological sovereignty reduces dependence on external platforms while ensuring that AI systems reflect national values and developmental priorities.

Without technological sovereignty, India risks digital dependence and strategic vulnerability in a data-driven global order.

GS Linkages:

  • GS3: Science & Technology
  • IR: Strategic autonomy
  • Economy: Innovation ecosystem

Conclusion

India’s AI strategy reflects an attempt to integrate technological ambition with developmental inclusion and ethical governance. By aligning AI with Digital Public Infrastructure, skilling, safety regulation, and strategic autonomy, India seeks to shape not only domestic outcomes but global AI governance norms.

The long-term success of this approach will depend on balancing innovation with safeguards, and growth with equity—ensuring that AI strengthens institutional capacity and advances the goal of a developed India by 2047.

Quick Q&A

Everything you need to know

Describing AI as a “civilisational inflection point” implies that artificial intelligence is not merely another technological upgrade but a transformative shift comparable to the Industrial Revolution or the advent of the internet. It expands human capability in areas such as healthcare diagnostics, predictive agriculture, and personalised education. However, if left unguided, it can destabilise labour markets, amplify misinformation, and entrench social biases. Thus, AI represents both unprecedented opportunity and systemic risk.

India’s approach, as articulated in the AI Impact Summit, emphasises human-centric and ethical deployment. The motto “Sarvajan Hitay, Sarvajan Sukhaye” reflects a civilisational philosophy where technology must serve collective welfare rather than narrow corporate or geopolitical interests. This framing shifts the debate from mere innovation metrics to impact metrics—focusing on people, planet, and progress.

Institutionally, this approach is reflected in initiatives like the IndiaAI Mission and the IndiaAI Safety Institute. By combining infrastructure expansion with regulatory safeguards and inclusive datasets, India seeks to balance innovation with accountability. Thus, calling AI a civilisational inflection point underscores the need for moral, legal, and institutional frameworks alongside technological advancement.

India’s Digital Public Infrastructure—comprising Aadhaar, UPI, and other open digital platforms—has created a scalable, interoperable backbone for service delivery. When AI is layered onto this architecture, governance can become more predictive, targeted, and efficient. For instance, AI-driven analytics can improve welfare targeting, detect fraud in subsidy transfers, and enable predictive maintenance of public infrastructure.

The open and inclusive design of India’s DPI is critical. Built as a public good rather than a proprietary system, it allows startups and innovators to develop AI applications atop a shared digital layer. This has implications for the Global South, where replicable models of inclusive digital governance are urgently needed. AI-enabled DPI can help governments in developing countries leapfrog legacy systems.

However, convergence also requires safeguards. Strong data protection through the Digital Personal Data Protection Act, transparency in algorithmic decision-making, and AI literacy among citizens are essential. Without these, automation may compromise privacy or exacerbate exclusion. Therefore, the DPI-AI convergence is transformative but must remain rooted in democratic accountability.

AI systems often inherit biases from training datasets, which can disadvantage certain genders, languages, or socio-economic groups. In a country as diverse as India, bias can manifest uniquely—for example, systems trained predominantly on English or urban data may marginalise rural or regional-language users. Recognising this, India has prioritised the creation of diverse and representative datasets and promoted AI development in regional languages.

Academic institutions and technology firms are increasingly researching fairness and algorithmic accountability. The establishment of the IndiaAI Safety Institute signals an institutional commitment to ethical AI deployment. Furthermore, regulatory steps such as watermarking AI-generated content and prohibiting harmful synthetic media address misuse concerns like deepfakes targeting women and vulnerable groups.

However, challenges remain. Building comprehensive datasets across India’s linguistic and cultural diversity is resource-intensive. Balancing innovation with regulation requires agility to avoid stifling startups. Thus, while India’s strategy is proactive and context-sensitive, sustained investment in research, capacity-building, and global cooperation will determine its long-term effectiveness.

In healthcare, AI-powered tools are being deployed for early detection of diseases such as tuberculosis, diabetic retinopathy, and epilepsy at primary and district health centres. These solutions enhance diagnostic reach in underserved regions, reducing dependence on specialist doctors. Such applications demonstrate how AI can strengthen public health systems rather than replace human professionals.

In agriculture, initiatives like Bharat Vistaar integrate AI into crop advisory services, soil analytics, and weather intelligence. Farmers receive localised recommendations, enabling data-driven decision-making. Additionally, Amul’s AI initiative supports 36 lakh women dairy farmers by providing real-time guidance in Gujarati on cattle health and productivity, illustrating grassroots empowerment.

In education, AI-based personalised learning platforms in Indian languages help bridge the urban-rural divide. By tailoring content to students’ pace and context, these systems enhance learning outcomes in government schools. Collectively, these examples show AI as a force multiplier for inclusive growth when aligned with developmental priorities.

India’s demographic dividend presents both opportunity and vulnerability in the AI era. While automation may redefine certain white-collar and IT roles, history suggests that technological revolutions create new categories of employment. The Prime Minister’s assertion that AI is transforming—not replacing—the IT sector reflects this understanding.

To harness this transformation, India has launched large-scale skilling initiatives and established AI Centres of Excellence in healthcare, agriculture, education, and sustainable cities. Budgetary support for data centres, semiconductor manufacturing, and high-performance computing infrastructure strengthens the ecosystem for AI innovation. These steps ensure that India moves from being a consumer of AI tools to a creator of AI models and platforms.

Preparation mitigates fear. By equipping youth with AI-relevant skills, India seeks to convert disruption into opportunity. Ranking third in the Stanford Global AI Vibrancy Index 2025 underscores India’s growing capacity. Thus, workforce transformation is not peripheral but foundational to achieving Viksit Bharat 2047 in an AI-driven world.

Achieving AI superpower status requires a multi-dimensional strategy built on sovereignty, inclusivity, and innovation. Sovereignty involves strengthening domestic compute capacity, semiconductor manufacturing, and cloud infrastructure to reduce technological dependence. The IndiaAI Mission’s support for startups and research institutions through GPU access is a step in this direction.

Inclusivity ensures that AI development benefits all citizens. Public services powered by AI—such as welfare targeting or multilingual education platforms—must become global benchmarks. Regulatory mechanisms like the IndiaAI Safety Institute, watermarking rules for AI-generated content, and the Digital Personal Data Protection Act provide governance scaffolding to maintain trust.

Finally, innovation requires fostering a vibrant startup ecosystem and global partnerships. Participation in international forums like GPAI and advocacy for a global AI compact position India as a norm-shaper rather than rule-taker. If these elements converge effectively, India can transition from participating in the AI revolution to actively shaping its trajectory.

Attribution

Original content sources and authors

TH
The Hindu Bureau
TH
The Hindu
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