2018
Examines the government's national strategy document on artificial intelligence. The response evaluates proposals related to ethics, privacy, regulation, and innovation, highlighting gaps in governance mechanisms and the risks of positioning India as a testing ground for untested technologies without adequate legal safeguards.
Read more →2019
This policy brief (working draft) outlines a grounded approach to regulating artificial intelligence, arguing against uniform or abstract rule-making. Instead, it proposes that regulatory responses should be shaped by who is deploying AI, the nature and scale of potential harm, and the rights that may be affected. The framework spans a broad range of policy tools, from regulatory restraint and self-governance to mandatory oversight and outright prohibition where risks are high.
Read more →2017
A MediaNama conference report published on 18 October 2017 by Aroon Deep, documenting discussions from the #NAMAprivacy event in Bangalore on regulating artificial intelligence systems. The article examines algorithmic bias, fairness, transparency, and institutional accountability, featuring contributions from Sunil Abraham and Pranesh Prakash, alongside researchers and legal experts debating whether regulation should focus on inputs, processes, or outcomes.
Read more →2019
A report published in The Economic Times on 4 June 2019 by Anjali Venugopalan documenting how major Indian employers deploy AI-powered video assessment platforms to analyze candidates' facial expressions, voice tone and emotional states during recruitment. Features Sunil Abraham's critique of algorithmic homogenization alongside evidence of racial bias in facial recognition technology from MIT researcher Joy Buolamwini.
Read more →2024
A Varindia event report from the 6th Global AI Leadership Meet organised by ASSOCHAM, documenting Dr. Amar Patnaik's call for trust-based approaches to AI regulation. The discussion brings together policymakers and industry leaders to examine how governance frameworks can encourage innovation without overreach, with contributions on data access, open standards, and layered models of AI accountability.
Read more →2024
A report published in The Indian Express on 28 November 2024 by Karan Mahadik, covering a Software Freedom Law Centre panel discussion on open-source artificial intelligence. The article examines debates around licensing definitions, transparency claims, regulatory gaps, and risks associated with open-source AI models, with perspectives from technology policy experts and developers.
Read more →2025
A MediaNama report published on 16 April 2025 by Kamya Pandey, examining Meta's assessment of how India's Digital Personal Data Protection Act and copyright framework could shape the country's appeal as a location for AI model training and data centres. The article features remarks by Sunil Abraham at the Global Technology Summit on data scraping exemptions, copyright law, and emerging conflicts between data minimisation and intellectual property obligations.
Read more →2025
A Hindustan Times Genesis article published on 18 September 2025 examining how artificial intelligence can be deliberately designed to serve India's underserved communities. Draws on discussions from the Pragati: AI for Impact convening held in Delhi, exploring India's strategy of combining openness, affordability and inclusivity in AI development, with examples of grassroots AI applications transforming access to justice, healthcare and livelihoods.
Read more →Selected video recordings featuring Sunil Abraham as a speaker, panelist, or discussant on artificial intelligence, governance, and technology policy.
A curated selection of materials, tutorials, and educational content on Artificial Intelligence recommended by Sunil Abraham for deeper engagement with technical foundations, policy implications, and emerging developments in the field.
An accessible one-hour overview of Large Language Models, the foundational technology powering systems such as ChatGPT, Claude, and Bard. The presentation covers core technical principles, future trajectories, comparisons with contemporary operating systems, and emerging security considerations within this evolving computational framework.