Rapid adoption of Artificial Intelligence (AI) across sectors like healthcare, education, agriculture, and governance is ongoing in India. Estimates project the contribution of AI up to $15.7 trillion to the global economy by 2030. But, without any formal national strategy or legal framework, there are a few issues regarding its ethical deployment, accountability, and inclusive growth.
AI governance in the world
Today, countries are not only concerned about protecting human rights but also promoting innovation and boosting the economy by bringing their focus on AI governance.
(a) Legislative Frameworks: Countries like the European Union (EU), China, Canada, the United States, etc, have done their bit by tabling formal laws to regulate AI.
(b) Draft Legislation: Nations such as the United Kingdom, Japan, Brazil, Pakistan, etc, have proposed AI bills awaiting approval.
(c) Strategic Documents: More than 80 countries and the African Union have released national AI strategy documents outlining policy goals, ethical principles, budget allocations, as well as sectoral priorities.
Need For Regulating AI
(a) Preventing Misinformation: Chances are very high of manipulations by deepfakes and misinformation created by AI.
(b) Protecting Privacy: Civil liberties will be in danger when surveillance technologies without regulation work. (c) Preventing Algorithmic Bias: Also, marginalised groups can become the target of the AI due to the reproduction of discriminatory attitudes towards them.
(d) Preventing Job & Labour Displacement: Traditional industries will take a blow due to job automation by AI shortly.
(e) Preventing Concentration of Power: A handful of companies with AI pose a monopolistic risk and social imbalance.
(f) Protecting from Existential Risk: Advanced Artificial Intelligence might become superior to human control if left uncontrolled.
(g) Ethical Concerns: Unethical, improper, and unregulated usage of AI systems could hinder the achievement of the Sustainable Development Goals (SDGs) – 2030. And this will happen due to the weakening of ongoing efforts and strategies across social, environmental, and economic spheres.
India’s Ongoing Approach
(i) Lack of Formal Strategy: As of now, India has no national AI strategy or proper legislation. The only document available is a discussion paper released by NITI Aayog, which was not officially adopted.
(ii) The IT Act (2000) and Digital Personal Data Protection Act, 2023: These kinds of acts and laws ensure indirect AI governance, mainly through data protection.
(iii) IndiaAI Mission: In the absence of a formal law, the government has launched the IndiaAI Mission. The mission, built upon seven pillars, aims to foster a responsible and innovation-driven AI ecosystem.
(iv) Expert Advisory Group: An expert group was established to give recommendations for AI governance. However, no clarity on its adoption timeline or certainty is given.
Key Initiatives and steps taken
(i) National Strategy for Artificial Intelligence (NSAI): NITI Aayog to guide the responsible development of AI across key sectors, released it in 2018. These sectors include healthcare, agri and allied sectors, education, and smart cities. However, it is non-binding and not followed up with enforceable regulations. (ii) AI Task Force (2018): The Ministry of Commerce and Industry set up this to suggest frameworks to leverage AI in India’s economic transformation. However, recommendations were acknowledged but not formally codified.
(iii) Responsible AI for Social Empowerment (RAISE 2020): MeitY and NITI Aayog collectively organised it. Its main focus is on AI governance, inclusivity, ethics, PPP (public-private partnership) models, and many more.
(iv) Parliamentary Standing Committee on IT (2021 & 2023 Reports): A dedicated and full-fledged AI regulatory framework is recommended by the committee.
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Way Forward
(a) Draft a National AI Policy: A comprehensive policy should be there that outlines India’s vision for AI. It should recognise priority sectors and jot down ethical principles, and specify the responsibilities of the institutions.
(b) Encourage Public Consultation and Awareness: Open and clear dialogues with academia, industry, as well as civil society are essential to enhance transparency and ensure accountability in AI deployment.
(c) Pilot Regulatory Mechanisms: India should implement pilot-level regulatory tools, such as algorithmic audits or risk classification systems, before enacting a full-fledged AI law.
(d) Invest in Institutional Capacity: It simply means patronage to AI research labs, open datasets, and skill development initiatives. Also, ethics committees and sectoral monitoring bodies will also be there.
Conclusion
When it comes to AI regulations, India focuses on development and adoption over strict frameworks. While this allows flexibility, it also leaves gaps in transparency, accountability, and ethical AI deployment. As AI adoption in India is getting its track, India should ensure an organised and structured governance model to ensure responsible and inclusive AI growth.