Recently during the ongoing budget session on parliament, Congress leader Rahul Gandhi highlighted the critical role of data in the AI landscape, stating, “People talk about AI, but it’s important to understand that AI on its own is absolutely meaningless, because AI operates on top of data.” He noted that without access to data, AI cannot function effectively. Pointing out a significant challenge for India, he added, “Most of the Indian data is stored abroad,” which compromises the nation’s ability to harness AI’s potential independently.
Gandhi went further, stating that global data control is a major issue, with China owning production-related data and the United States controlling consumption data. “Every single piece of data that comes out of the production system in the world… is owned by China, and the consumption data is owned by the United States,” he said, underscoring the need for India to address these imbalances if it hopes to compete in the global AI race. This statement contrasts sharply with the more rhetorical approach seen in speeches by Prime Minister Narendra Modi, and particularly on the same day when he made his ‘Double AI’ statement.
In this data driven world, India is entering an era where technological advancement will shape the fabric of society. With youth on the front lines of this transformation, it is essential for the political class to speak clearly, critically, and with constructive foresight about the implications of AI. The political discourse on AI cannot remain vague when the technological, economic, social and geopolitical implications are deeply entwined with it.
Realities and Rahul Gandhi
In this wake, Rahul Gandhi’s approach on AI is fresh and offers an example of what a scientific temper in political leadership looks like. He did not merely endorse AI as a tool for progress but instead engaged with its geopolitical and political-economic dimensions. Gandhi highlighted that AI cannot exist in isolation and it is entirely dependent on data as an essential fuel for AI systems to function.
Gandhi’s reference to the fact that much of the country’s digital data is stored and processed abroad, controlled by foreign tech giants such as Google, Facebook, and Amazon, reflects the geopolitical reality where global powers like the United States and China have consolidated their dominance over AI technologies due to their control over vast amounts of data. In the United States, OpenAI and companies like Microsoft use the data of millions of users to advance AI systems, creating technological monopolies. Similarly, China uses state control over data to fuel its AI ambitions, using data for everything from economic strategy to social surveillance.
In this critical global juncture, Gandhi is correct in not simply treating AI as a tool of progress but in underscoring the structural realities that will influence AI’s development in India. His critical engagement with these geopolitical realities adds value to our modern political discourse not only through an argument for technological growth, but also for India’s autonomy in the AI landscape. In fact, his advocacy for data sovereignty and infrastructure development has the potential to become an important directive for policy makers too. As China and the United States lead the global AI race, India has to move beyond mere rhetoric on AI by taking Rahul Gandhi’s realist criticism seriously.
Being in the the realpolitik of AI, restructuring AI and data policies in the larger context of national sovereignty and data control is certainly the need of an hour. Today, ’We the people’ of India seek a vision of technological sovereignty, where data sovereignty is priced and human dignity is valued.
Disparities
In his speech, Rahul Gandhi also emphasised the transformative potential of AI in its application to the caste census, claiming it as an opportunity for a “social revolution” in the country. He said, “Imagine the power of AI when we apply it to the caste census. Imagine what we will do with AI and what we will do with the social revolution in this country when we start to apply AI to the data that we get from the caste census.” This vision underscores his belief that AI has the potential of “revolutionising the participation of Dalits, OBC and Adivasis in the running of this country, in the institutions of this country, in the distribution of wealth of this country and on the other side, “challenge the Chinese and participate in the revolution, defeat the Chinese in electric motors, batteries, solar panels and wind.”
Despite all the talk of “Amritkaal” and Viksit Bharat, social exclusion and discrimination remain deeply entrenched. Among SCs, the share of school children drops from 81% in the 6-14 years age group to 60% in the 15-19 age group. The condition of STs is perhaps more deplorable.
In institutions like IIM Indore, over 97% of faculty positions are held by individuals from the General category, leaving no representation for Scheduled Castes (SC) or Scheduled Tribes (ST). Similarly, IIM Udaipur and IIM Lucknow report over 90% of faculty from the General category. The situation is similarly stark in IITs, with over 90% of faculty at IIT Bombay and IIT Kharagpur belonging to the General category, while IITs in Mandi, Gandhinagar, Kanpur, Guwahati, and Delhi report 80-90% General category faculty. These trends highlight a significant disproportion in faculty composition despite reservation policies. Of course, this is just a part of the pan Indian picture of inequality, excluding the larger set of private institutions.
This disparity reveals that in spite of technological advances, the social inequities that define caste hierarchies and systemic oppression remain pervasive.
Caste and other issues
While India celebrates technological achievements like space missions, there is a glaring neglect of the basic infrastructure needed for a truly scientific outlook such as providing proper education and resources for the marginalised. Moreover such a paradox is starkly visible in the paradox of millions being invested in religious gold-plated symbolism while the most basic needs of government schools, including proper infrastructure and qualified teachers, remain unmet.
This paradox highlights a deeper issue in the reach of digital democracy and scientific temper in India. Despite the promise of digital platforms like social media and AI tools such as ChatGPT democratising access to information, the real material and cultural benefits are largely biased towards the socially and economically privileged. For marginalised communities, the rising cost of digital learning resources further compounds their exclusion, leaving them unable to leverage these platforms for upward mobility.
In this light, Rahul Gandhi’s call for a ‘Caste Census’ is an articulation emanating from scientific temper. It recognises AI’s potential to benefit the marginalised masses by measuring/analysing the complex information regarding the causes of their exclusion, marginalisation and underrepresentation in institutions. It shall certainly make the benefits and welfare accessible to this class of India. “Social revolution” through AI, therefore, is not only about technological advancement but also about addressing the systemic inequalities that undermine the fundamental rights provided in articles 14, 15 and 16 of the Constitution.
Gandhi’s emphasis on data localisation and AI-driven social justice is not just a call for technological independence but for national autonomy, integration as well as social revolution. This approach is deeply grounded in the reality of India’s diverse population, ensuring that AI policies ensure holistic and inclusive empowerment for all the sections of society – particularly the historically marginalised ones. Gandhi’s call for a caste census as a foundation for AI policy can’t be faulted: “If we don’t have a caste census, AI policies will not be able to accurately address the needs of India’s diverse population.”
Infrastructure
Moreover, AI’s application in sectors like education, employment, and healthcare can revolutionise them. Gandhi’s critical realist approach – rooted in both scientific temper and social equity – arguably makes him more aligned with the needs of modern India.
On the other hand, Prime Minister Narendra Modi’s speeches on AI often remain on the level of aspirational rhetoric, positioning India as a global leader in AI without engaging with the practical issues that need to be addressed. His recent remarks about “Double AI” – one AI as Artificial Intelligence and the other as an “Aspirational India” – underline the gap between vision and substance. Although his assertions often emphasise optimistic narratives of technological progress, there is a noticeable absence of clear, actionable plans to solve issues like data sovereignty, digital infrastructure, and AI literacy. Needless to say, there is hardly any constructive idea in favour of caste census from PM’s end. Moreover, he criticised Rahul Gandhi’s invocation of it as just a mere “fashion” of speaking on caste.
It’s high time that the political discourse surrounding AI in India transcend rhetoric and engage with critical issues of data sovereignty, infrastructure, and social justice. There’s a dire need for India’s political leadership to redesign and adopt a more scientifically informed and realistic approach. Only through such a vision can India reclaim its rightful position in the global AI race. The onus is on political leaders to engage constructively with not only the vision but also with responsibility to build a future where technology empowers every citizen and strengthens the fabric of the nation.
Vruttant Manwatkar is an Assistant Professor of Political Science, KC College, Mumbai.
This piece was first published on The India Cable – a premium newsletter from The Wire & Galileo Ideas – and has been updated and republished here. To subscribe to The India Cable, click here.
