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Economic Transformation through AI: Key pillar to a large Indian Economy in Global Top 3

In the rapidly evolving landscape of the AI economy, the choices made today will reverberate for generations. As custodians of India’s future, we must recognize the urgency of embracing AI as a lynchpin of economic growth. The time to act is now!

In an era characterized by relentless technological advancement, a nation’s economic growth trajectory hinges on its ability to harness the power of artificial intelligence (AI). Goldman Sachs reported that generative AI could raise global GDP by 7%. By 2030, this AI driven Intelligence Economy might add $15.7tn of new economic value as per PWC research.

With its burgeoning tech industry, diverse and large data pool and remarkable human capital, India stands at the precipice of an economic transformation that could either propel it to global leadership or condemn it to follow in the wake of other trailblazers. As political decision-makers, the imperative to recognize and seize this opportunity cannot be overstated in view of India’s bid to become one of the top 3 economies of the world. The availability of the DEPA Training Cycle and the DPDP Bill passage through the Parliament open the door to immediate and strategic action via the creation of a large AI economy.

I. The AI Imperative for Global Competitiveness:

India’s demographic dividend of 900mn+ people is no secret but must be coupled with technological prowess to ensure a multiplier effect for sustained growth. As global economies increasingly pivot towards AI-driven industries, overlooking this shift risks consigning India to a secondary role on the global stage. To maintain competitiveness, India must embrace AI not merely as a tool but as the very foundation of its economic strategy going forward. It must ensure that it is not just a consumer of AI but a critical creator of AI. In fact, it must aim to emerge as one of the 3 AI superpowers in the world.

II. Safe AI Leadership Depends on Data

India’s DEPA Training makes privacy-preserving collaboration between Training Dataset Providers and Modelers (called Training Dataset Consumers) possible at a large scale, which is a critical element in AI journey. The DEPA system does not rely on hard-to-implement enforcement of legal covenants around Anonymized Datasets, as is the case in countries like the US, where AI companies are fighting constant litigation. Instead, it depends on computational privacy guarantees in the use of aggregated datasets. This is core to enabling safe AI systems, built with reliable and traceable access to datasets. Then, it can be deployed quickly with human alignment that India can provide with its billion plus users. As India begins to unlock continental-scale datasets using this system, it will give rise to a vibrant ecosystem of AI Modelers. This dataset advantage in AI is not to be underestimated. By focusing on early Safe AI adoption, India can secure a foothold in these sectors, attracting global investment and cementing its position as an innovation hub whose AI innovations would be adopted by societies around the world.

III. Addressing Socioeconomic Disparities: Remote AI driven workflows & 5G

Harnessing AI’s potential can also serve as a powerful tool to address India’s socioeconomic disparities. AI-driven solutions can optimize resource allocation, improve public service delivery, reduce cost of access and create job opportunities across urban and rural areas. With massive 5G rollout, the possibility of digital global work aided by AI is here. It can dramatically bring income opportunity to rural and smaller cities, if we can bring in Indic language AI tools, which lower the bar for participating in the global workflows. By proactively leveraging AI to bridge gaps and enhance productivity, India’s leadership can demonstrate a commitment to inclusive growth and lay the foundation for a more equitable society. All the while reducing strains of growing urbanization, which might be disastrous for its overburdened large cities.

IV. The Gameplan for AI Leadership: Missing piece of compute clusters

DEPA Training will safely and responsibly unlock the collaboration between India Training Dataset Providers and Modelers. We have the talent already and the market scale to do Reinforcement Learning with Humans in the Loop. What we lack is tensor-scale computing enabled for Industry, startups, academia and Govt itself. The Government of India must address this by enabling the creation of many, not one, tensor-scale GPU cloud providers. There are many ways to do this: Challenge Grants, Viability-gap funding for cloud providers, and Matching-grants for Modelers. We favor the Matching Grants method for effectiveness, transparency, and competition. In addition, we must seek to create AI on the edge compute ecosystem for a strategic future.

V. Collaborative Diplomacy and Global Alliances:

AI does not recognize national borders, and collaboration is key to advancing the field. At the same time, we must recognize that Nvidia H100 boards are already on the US Export Control List for China. The US might leverage its muscle further at some time in the future. We must therefore have a strategic perspective in making our aggregate AI capability and datasets available to others based on a principle of reciprocity. We must build careful alliances with a broad set of players in US, EU and Asia that will accelerate India’s AI capabilities but also position the nation as a global AI thought leader.

VI. The Consequences of Inaction:

The consequences of neglecting AI’s potential are dire. India risks becoming a mere consumer of AI technologies, ceding economic leadership to countries that have embraced AI as a strategic priority. China, our neighbor, has famously vowed to be the sole AI superpower by 2030. This passivity could lead to missed opportunities, economic stagnation, and a loss of global influence. It may even result in India failing to breach the top 3 economies, , as we might have to buy both oil and artificial brains, draining our resources for welfare schemes for our large population. That could risk demographic disaster instead of demographic dividend.

Conclusion: We need to act now!

In the rapidly evolving landscape of the AI economy, the choices made today will reverberate for generations. As custodians of India’s future, we must recognize the urgency of embracing AI as a lynchpin of economic growth. The time to act is now! We must catalyze innovation, ensure global competitiveness, and create a prosperous future where India’s leadership is defined not by its past but by its capacity to shape the AI-powered future world decisively.

Sharad Sherma is co-founder of iSPIRT Foundation. Umankant Soni is the Chairman AI foundry, General Partner ART Venture Fund.

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Ready for India’s AI ambitions: We are now one step closer to having a modern regulation for and of AI

The passage of the Digital Personal Data Protection Bill 2023 (DPDP) by the Lok Sabha is significant in more ways than one. The Bill aims to enforce and promote lawful usage of digital personal data and stipulates how organisations and individuals should navigate privacy rights and handle personal data.

Creating effective mechanisms to enable data governance has become one of the top priorities for countries around the world. The challenge for policymakers is designing legal and regulatory frameworks that clearly lay down the rights of data principals and obligations for data fiduciaries.

The Digital Data Protection Bill is a much-needed step in this direction, taken after months of deliberations and discussions. Such normative frameworks are critical to secure regulatory certainty for enterprises. However, innovative technical measures are required to support their operationalisation.

In the past couple of years, India has made significant strides in adopting a techno-legal approach to data governance. Through this approach, India is building technical infrastructure for authorising access to datasets that embed privacy and security principles in its design.

Data also lies at the heart of AI innovations that can address significant global challenges. India’s unique techno-legal approach to data governance is applicable across the life cycle of machine learning systems.  It complements the country’s ambition of supporting its growing AI start-up ecosystem while providing privacy guarantees.

As part of India Stack, the Data Empowerment and Protection Architecture (DEPA) launch in 2017 was India’s paradigm-defining moment for the inference cycle of the machine learning life cycle. It proposed the setting up of Consent Managers (CMs), also known as Account Aggregators in the financial sector.

This approach, also mentioned in the current iteration of the DPDP (Chapter 2, [Sections 7-9]), ensures individuals can exercise control over their data and can provide revocable, granular, auditable, and secure consent for every piece of data using standard Application Programming Interface (APIs). The secured consent artefact records an individual’s consent for the stated purpose.
It allows users to transfer their data from those data businesses that hold it to those that have to use it to provide individuals certain services while ensuring purpose limitation. For instance, individuals can share their financial data residing within their banks with potential loan service providers to get the best loan package.

DEPA is India’s attempt at securing a consent-based data-sharing framework. It has facilitated the financial inclusion of millions of its citizens. Eight of India’s largest banks were early adopters of the framework starting in 2021. Currently, 415 entities, including CMs, Financial Information Providers, and Users, participate across various DEPA implementation stages.

However, the training cycle of an AI model demands substantially more data to make accurate predictions in the inference cycle. As such, there is a need for more of such robust technical solutions that disrupt data silos and connect data providers with model developers while providing privacy and security guarantees to individuals who are the real owners of their own data.

With DEPA 2.0, India is already experimenting with a solution inspired by confidential computing called the Confidential Computing Rooms, or CCRs. CCRs are hardware-protected secure computing environments where sensitive data can be accessed in an algorithmically controlled manner for model training.

These algorithms create an environment for data to be used while ensuring compliance with privacy and security guarantees for citizens are upheld and data does not exchange hands. Techniques like differential privacy introduce controlled noise or randomness into the training process to protect individuals’ privacy by making it harder to identify them or extract sensitive information.

To make CCR work, model certifications and e-contracts are essential elements. The model sent to CCR for training has to be certified to ensure it upholds privacy and security guidelines, and the e-contracts are required to facilitate authorized and auditable access to datasets. For example, loan providers can authorise access to a representative sample of the datasets residing with them to model developers via CCR for model training. This arrangement will be facilitated via e-contracts once the CCR verifies the validity of the model certification provided by the modeller.

India’s significant progress with technical measures that are aligned with domestic legal frameworks provides it with a head start in the AI innovation landscape. Countries all across the globe are struggling to find solutions to facilitate personal data sharing for model development that prioritises security and privacy. Multiple lawsuits have recently been filed against OpenAI across numerous jurisdictions for unlawfully using personal data to train their models.

India’s unique approach to data governance, where both technical and legal frameworks fit like a puzzle and balance the thin line of promoting AI innovation while providing privacy guarantees, is well-positioned to guide global approaches to data governance.

In a quiet and disciplined fashion, over the last six years, India has put the critical techno-legal pieces in place for becoming a significant AI player in the world alongside US and China. Like them, we have continental-scale data and the talent to shape our future. With the passage of the DPDP Bill, we are now one step closer to having modern regulatory tools for effective regulation of AI and regulation for AI.

Co-Authored by Antara Vats and Sharad Sharma
A version of this was published on Financial Express, August 9th, 2023.