In the past two decades, Artificial Intelligence (AI) has become a ubiquitous part of our society. Its growing use has led to societal and economic shifts towards increased automation and data-driven decision-making across sectors, including healthcare, education, law enforcement, banking, and energy. Its rampant development and use have prompted questions about its ethical implications, risks, and long-term impacts, leading to emerging debates about governing these technologies through policies and regulations. Most of these discussions revolve around ‘Responsible AI’ (RAI), an umbrella term for principles and practices that promote safe and ethical development and use of AI.
Efforts to inculcate RAI principles are underway worldwide. To map different countries’ progress in developing and implementing RAI frameworks, the Global Center on AI Governance led the creation of a multidimensional index called the Global Index on Responsible AI (hereon, “Index”). It measures government commitments and country capacities, through a social, technical and political lens, through localised data collection in 138 countries. Supported by the International Development Research Centre (IDRC), the Government of Canada and USAID, its 1st edition was released in June 2024.
Digital Futures Lab served as the Regional Hub for South Asia, coordinating efforts with data collectors across eight countries. In addition, we also acted as the primary data collector for India. In this post, we highlight the key findings from India, specifically focusing on its government frameworks for Responsible AI.
As seen in the table, the Index measures RAI efforts across 19 thematic areas, clustered into 3 dimensions: (i) Human Rights and AI, (ii) Responsible AI Governance, and (iii) Responsible AI Capacities.
Each thematic area is assessed across 3 different pillars of the responsible AI ecosystem: (a) Government Frameworks, (b) Government Actions, and (c) Non-state Actor Initiatives. The different components of the Index have been depicted in the table below - highlighting key thematic areas covered by government frameworks in India.
The data used in the 1st edition of the Index covers the period between November 2021 and November 2023.
Table: Responsible AI Themes within Government Frameworks in India
[Thematic areas highlighted in red represent issues not represented within existing government frameworks]
Findings under the pillar of government frameworks reveal a lack of legal and policy frameworks pertaining to RAI. Although there is some activity in specific thematic areas, the frameworks and principles are primarily outlined in white papers and strategy documents, and as such, are not legally enforceable. Further, most of the activity is very sector-specific such as the Indian Council for Medical Research's ethical guidelines for the application of artificial intelligence in biomedical research and healthcare 2023, the Ministry of Housing and Urban Affairs' AI playbook for cities, and the National Education Policy, 2020.
Human Rights & AI: This dimension measures the extent to which countries are taking steps to protect, promote, and respect key human rights implicated by AI. Findings under this dimension reveal that governments at the central and state levels are yet to take any action in the form of frameworks such as laws, policies, regulations, and guiding documents on issues such as Children’s Rights, Gender Equality, Public Participation and Awareness.
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Note: There are some recent developments under labour protection which could not be included in this edition of the Index as they fell outside the stipulated timeline for data collection. These include legislations aimed at regulating gig work in Rajasthan, Karnataka, and Jharkhand.
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Responsible AI Governance: This dimension measures the degree to which country-level governance regimes uphold effective and rights-preserving practices in RAI. Findings under this dimension reveal that governments are yet to develop frameworks that cover algorithmic decision-making and provide access to remedy and redress to those affected by algorithmic decision-making.
The lack of specific regulation for mitigating algorithmic risks has resulted in provisions from other laws, such as criminal laws in the country, being used to regulate AI harms. For example, the individual responsible for creating deepfake videos of an Indian actor was arrested under sections 465 and 469 of the Indian Penal Code (IPC) for forgery and maligning the reputation of a person. Although Section 66C (identity theft) and Section 66E (privacy violation) of the Information Technology Act, 2000 were applied, there is no AI-specific legal framework available to indict the individual responsible.