AI can be the backbone of India’s Governance through Tech
The Union Minister of State for Electronics and Information Technology, Rajeev Chandrasekhar, highlighted how the government uses technology in governance. Technology has helped plug leakages in subsidy programmes, and artificial intelligence (AI) could materially improve efficiency in e-governance. The Union Budget had announced the establishment of three “centres of excellence” for AI. These are to be connected with academia, industry, and start-ups. Working groups have already been set up for designing India dataset platforms and the centres of excellence. The government is considering a ‘Hub & Spoke’ network model to safeguard “guardrails for ethical use without disrupting innovation”.
The government will spend around 1,635 crores to develop this AI ecosystem and make e-governance platforms more intelligent. The priorities for deployment include the following:
a. Governance applications of the India Stack
b. Powering up the large language model for Digital India Bhashini
c. Building Smarter health care Services
The re-launched Skill India programme will also focus on AI, since this will be essential for future workforces. In analogy to the US and China, where governments and government agencies funded early forays into AI, the policy thrust could spark the private sector into developing new use cases and trigger new investments into AI-related start-ups. This secondary effect would be vital in generating higher productivity across the economy.
The India Stack is a large basket of open-source software application programming interfaces (APIs) of government-backed services such as Aadhaar, United Payments Interface, e-Sign, and Digi-Locker. The open-source nature allows anybody to connect. This has inspired many apps with varying architectures, APIs, libraries, and user interfaces. The Stack generates vast data across its various use cases. If AI-driven algorithms are applied to study that data, it could provide granular, deep insights into consumer behaviour and consumption patterns. While such AI induction may be laudable in intent, tight oversight will be required to maintain privacy and avoid data leakage.
Moreover, if India uses AI at scale to power digital inclusion and skilling, in that case, it will need to develop robust filters to root out algorithmic biases and to ensure AI doesn’t perpetuate existing biases against castes and communities. This involves creating audit systems to understand how AI ‘thinks’ since it can be a black box even for programmers. AI deployment in Indian datasets could be very powerful because of the sheer size and diversity of the country and, therefore, of the datasets. When it comes to large language models (ChatGPTfor example), India again has an inbuilt advantage in that there is data from a plethora of languages to work with. If it pushes ahead with this policy, it could become a world leader in AI. The government could consider developing guidelines for protecting and mitigating potential harm to citizens.
