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While addressing the needs of 150 crore citizens, technology serves as a powerful tool with unprecedented impact. Take education, a key driver of progress, which often faces complex challenges. For example, in Himachal Pradesh a few years ago, the problem seemed simple: too many schools and not enough teachers. But the real issue was more complex – schools were clustered too closely, and some had more teachers than they needed, while others faced shortages. Enter the optimization algorithm, which streamlined the number of schools and teachers, merged 400 schools and significantly increased teaching quality.
Consider the challenge of managing the transfer of nearly one lakh teachers in Haryana’s government schools. How do you effectively coordinate such a large movement? Similarly, in agriculture, how do you allocate 3000 rural agricultural workers across 30 districts of Odisha to ensure balanced workload for farmers and efficient delivery to the last mile?
Machine learning algorithms have tackled these issues with precision. Today, Haryana handles transfers of teachers through a completely automated system, while Odisha uses advanced optimization algorithms to distribute the workload of village agricultural workers, ensuring fair and effective service delivery.
Building on these successes, recent advances in Artificial Intelligence (AI) have shown remarkable potential to increase individual productivity. But have you ever wondered how the potential of AI can be unleashed at a population scale in the context of governance to transform the citizen experience?
We can divide it into three parts depending on the type of AI model being deployed: First, there is interpretable AI – this involves the AI’s ability to understand and process human input. For example, this includes techniques such as Convolutional Neural Networks (CNNs) for reading handwritten homework, or analyzing and interpreting video content. It can provide students with personalized, real-time feedback and adjust their learning trajectory based on their individual needs. Second, there is cognitive AI – these are machine learning algorithms that are being used to perform advanced problem-solving and decision-making by mimicking human cognitive processes. For example, by analyzing trends in historical data, tools like TimeGPT or TemporAI can forecast future demand for health services, plan resource allocation and manage staff schedules at a given district hospital more effectively. Can manage from. Finally, there is Generative AI – this involves generating new content or data based on patterns and information from existing data. For example, in the state of Odisha, through Ama CrushAI chatbot, village agricultural workers and farmers today have access to personalized advisory services in Odia, Hindi and English on best agricultural practices, government schemes, loan products and more at their fingertips. Is. ,
This offers just a glimpse of the transformative potential of AI when applied to real, complex, on-the-ground governance challenges that impact the lives of millions of people. As India moves forward on its ambitious goal of becoming the AI usage capital of the world, five key pillars will shape its future trajectory:
- Perspective: AI should ‘augment’, not ‘replace’ human capabilities in governance, complementing rather than replacing human judgment, especially in critical life-impacting tasks.
- Building capability and capacity: Just as foundational literacy and numeracy form the foundation for education, India needs a comprehensive approach to AI literacy that spans grades, trades and professions. Establishing state-of-the-art (ISRO-like) institutes in each domain working on strategic use cases of AI will foster collaboration between academia and industry, thereby maximizing value for all stakeholders.
- Cost: Cost efficiency is important in scaling AI technologies. Estimated costs on graphics processing units (GPUs) The costs associated with running a trained AI model can be both high and inefficient. Thus, it is important to maintain an approach of frugal innovation when creating solutions at population scale. One way to achieve this is to use smaller models that can work directly on mobile devices, eliminating the need for expensive cloud-based GPUs.
- GPU availability: AI scalability, especially when training AI models, is hindered by limited GPU availability. Thus there is a need to democratize GPU production. It is important to adopt specialized chips for specific tasks, such as Language Processing Units (LPU) or Tensor Processing Units (TPU). By designing and manufacturing these chips in India, ideally by developing them in an open-source manner like RISC-V, we can strengthen our domestic technology capabilities.
- Responsible use of data: Consent is paramount to ensuring ethical AI development and protecting sensitive data. We need to effectively use the Digital Empowerment Architecture (DEPA) framework established by MeitY, which underpins the consent mechanisms in platforms like DigiLocker and Ayushman Bharat, to build and maintain public trust.
Once we secure these fundamental aspects, we open the door to the full spectrum of AI’s transformative potential. Imagine an AI-powered society where healthcare is revolutionized: portable diagnostic tools in apps instantly capture body images, monitor activities and perform preliminary health checks. An AI co-pilot assesses results, provides advice, or refers urgent cases to nearby hospitals. At the hospital, you get quick, accurate care without long waits or repeated explanations. Meanwhile, public health organizations analyze patterns to identify at-risk populations and early detection of endemics to enable proactive service delivery. Similarly, in an AI-driven society where agriculture has been revolutionized: farmers use satellite imagery and drones to monitor crop growth and soil health in real time at the farm level, on irrigation and pest management. Receive accurate and timely advice, thereby increasing the productivity of their farm. Similarly, in the field of education, teachers are equipped with tools to measure the learning levels of their students in real-time, made possible through spot assessments in their local language. The possibilities are endless and immeasurable, as AI has the potential to change the world more than anything we have seen before.
This article is written by Gaurav Goyal, Founder and CEO and Rahul Kulkarni, Chief Technologist, Samagra.
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