Posts

The Cost of Free Basics in India: Does Facebook's 'walled garden' reduce or reinforce digital inequalities?

by Amrita Sengupta

• April 05, 2025

• Free Basics, Facebook, Internet Governance

In this essay—written in April 2016 soon after India's Telecom Regulatory Authority (TRAI) upheld net neutrality and effectively banned Free Basics in India— the author uses development theories to study the Free Basics programme. The author explored three key paradigms: 1) Construction of knowledge, power structures and virtual colonization in the Free Basics Programme, (2) A sub-internet of the marginalized and (3) the Capabilities Approach and explored how the programme reinforces levels of digital inequalities as opposed to reducing it. This essay was written in 2016 and there have been various shifts in the digital and tech landscape. Further a lot of numbers and statistics are from 2016 and not all ideas held here may be transferable today. This should be read as such. This is being published now, on account of 10 years since the Free Basics project was set to be implemented in India.

Emotional Contagion: Theorising the Role of Affect in COVID-19 Information Disorder

by Yesha Tshering Paul and Amrita Sengupta

• April 03, 2025

• Information Disorders, Fake News, Internet Governance, Covid19

In this paper, we investigate the underexplored emotional drivers of information disorder, with a particular focus on how it manifested in COVID-19 misinformation in India. While "fake news" has received considerable attention for its impact on elections, marginalized communities, and public health, mainstream information disorder research does not sufficiently prioritise the underlying psychological factors that influence information trust.

Education, Epistemologies and AI: Understanding the role of Generative AI in Education

by Aparna Bhatnagar and Amrita Sengupta

• March 21, 2025

• Responsible AI Integration, Critical Thinking, Knowledge Production, Education Policy, Internet Governance, Epistemic Trust, Algorithmic Bias, Artificial Intelligence

As generative AI becomes more deeply embedded in educational contexts, it raises critical questions about trust, epistemic reliability, and the nature of knowledge production. While AI offers significant opportunities for enhancing pedagogical methodologies, facilitating personalised learning, and augmenting research, it also raises concerns regarding cognitive offloading, the erosion of critical thinking skills, and the perpetuation of biases inherent in training data. This essay examines how higher education institutions navigate these complexities, focusing on institutional adaptation, ethical considerations, and policy responses. Central to this inquiry is an analysis of key theoretical frameworks in education and epistemology to understand how these impact the discourse around generative AI in the classroom. This essay looks at existing educational theory to understand the role of AI in the classroom. Furthermore, the study assesses existing institutional and national AI policies, evaluating their efficacy in addressing governance challenges, and offers future-looking questions and recommendations to guide the responsible integration of generative AI in education.

The Centre for Internet and Society’s comments and feedback to the: Digital Personal Data Protection Rules 2025

by Pallavi Bedi, Vipul Kharbanda, Shweta Mohandas, Anubha Sinha and Isha Suri

• March 06, 2025

• Privacy, Internet Governance, Data Governance, Data Protection, Data Management

The Centre for Internet & Society (CIS) submitted its comments and feedback to the Digital Personal Data Protection Rules 2025 initiated by the Indian government.

The Centre for Internet and Society’s comments and recommendations to the: Report on AI Governance Guidelines Development

by Shweta Mohandas, Amrita Sengupta and Anubha Sinha

• March 06, 2025

• Internet Governance, Artificial Intelligence

The Centre for Internet & Society (CIS) submitted its comments and recommendations on the Report on AI Governance Guidelines Development.

Do We Need a Separate Health Data Law in India?

by Pallavi Bedi and Shweta Mohandas

• February 07, 2025

This report discusses the current definitions of health data including international efforts, the report then proceeds to share some key themes that were discussed at three roundtables we conducted in May, August, and October 2024. Participants included experts from diverse stakeholder groups, including civil society organisations, lawyers, medical professionals, and academicians. In this report, we collate the various responses to two main aspects, which were the focus of the roundtables:

Digital Rights and ISP Accountability in India: An Analysis of Policies and Practices

by Anubha Sinha, Yesha Tshering Paul, and Sherina Poyyail

• January 23, 2025

• Telecom, internet governance, Internet Governance

This report presents a comprehensive evaluation of India's four largest Internet Service Providers (ISPs)—Reliance Jio, Bharti Airtel, Vodafone-Idea (Vi), and BSNL—examining their commitment to digital rights and transparency.

Privacy Policy Framework for Indian Mental Health Apps

by Chakshu Sang and Shweta Mohandas

• January 10, 2025

• Internet Governance, Data Protection, Privacy

This report analyses the privacy policies of mental health apps in India and provides recommendations for making the policies not only legally compliant but also user-centric

Technology-facilitated Gender-based Violence and Women’s Political Participation in India: A Position Paper

by Yesha Tshering Paul, Amrita Sengupta

• December 18, 2024

• Freedom of Speech and Expression, Gender, Internet Governance

AI for Healthcare: Understanding Data Supply Chain and Auditability in India

by Amrita Sengupta (PI), Shweta Mohandas (Co-PI), (In alphabetical order) Abhineet Nayyar, Chetna VM, Puthiya Purayil Sneha, Yatharth

• November 29, 2024

• Health Tech, RAW Publications, Researchers at Work, Featured, Healthcare, Homepage, Artificial Intelligence

This report aims to understand the prevalence and use of AI auditing practices in the healthcare sector. By mapping the data supply chain underlying AI technologies, the study aims to unpack i) how AI systems are developed and deployed to achieve healthcare outcomes and, ii) how AI audits are perceived and implemented by key stakeholders in the healthcare ecosystem.