#FactCheck - "Viral Video Misleadingly Claims Surrender to Indian Army, Actually Shows Bangladesh Army”

Introduction 

The Data Protection Data Privacy Act 2023 is the most essential step towards protecting, prioritising, and promoting the users’ privacy and data protection. The Act is designed to prioritize user consent in data processing while assuring uninterrupted services like online shopping, intermediaries, etc. The Act specifies that once a user provides consent to the following intermediary platforms, the platforms can process the data until the user withdraws the rights of it. This policy assures that the user has the entire control over their data and is accountable for its usage.

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A keen Outlook 

The Following Act also provides highlights for user-specific purpose, which is limited to data processing. This step prevents the misuse of data and also ensures that the processed data is being for the purpose for which it was obtained at the initial stage from the user.

1. Data Fudiary and Processing of Online Shopping Platforms: The Act Emphasises More on Users’ Consent. Once provided, the Data Fudiary can constantly process the data until it is specifically withdrawn by the Data Principal.

• Detailed Analysis

• Consent as a Foundation: The Act places the user's consent as a backbone to the data processing. It sets clear boundaries for data processing. It can be Collecting, Processing, and Storing, and must comply with users’ consent before being used.
• Uninterrupted Data processing: With the given user consent, the intermediaries are not time-restrained. As long as the user does not obligate their consent, the process will be ongoing.

2. Consent and Order Fulfillment: Consent, once provided, encloses all the activities related to the specific purpose for which it was meant to the data it was given for subsequent actions such as order fulfilment. 

• Detailed Analysis

• Purpose-Limited Consent: The consent given is purpose-limited. The platform cannot misuse the obtained data for its personal use.
• Seamless User Experience: By ensuring that the user consent covers the full transactions, spared from the unwanted annoyance of repeated consent requests from the actual ongoing activities. 

3. Data Retention and Rub Out on Online Platforms: Platforms must ensure data minimisation post its utilisation period. This extends to any kind of third-party processors they might take on.

• Detailed Analysis

• Minimization and Security Assurance: By compulsory data removal on post ultization,This step helps to reduce the volume of data platforms hold, which leads to minimizing the risk to data.
• Third-Party Accountability, User Privacy Protection. 

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Influence from Global frameworks

The impactful changes based on global trends and similar legislation( European Union’s GDPR) here are some fruitful changes in intermediaries and social media platforms experienced after the implementation of the DPDP Act 2023.

1. Solidified Consent Mechanism: Platforms and intermediatries need to ensure the users’ consent is categorically given, and informed, and should be specific to which the data is obtained. This step may lead to user-friendly consent forms activities and prompts. 
2. Data Minimizations: Platforms that tend to need to collect the only data necessary for the specific purpose mentioned and not retain information beyond its utility.
3. Transparency and Accountability: Data collecting Platforms need to ensure transparency in data collecting, data processing, and sharing practices. This involves more detailed policy and regular audits.
4. Data Portability: Users have the right to request for a copy of their own data used in format, allowing them to switch platforms effectively.
5. Right to Obligation: Users can have the request right to deletion of their data, also referred to as the “Right to be forgotten”.
6. Prescribed Reporting: Under circumstances of data breaches, intermediary platforms are required to report the issues and instability to the regulatory authorities within a specific timeline.
7. Data Protection Authorities: Due to the increase in data breaches, Large platforms indeed appoint data protection officers, which are responsible for the right compliance with data protection guidelines.
8. Disciplined Policies: Non-compliance might lead to a huge amount of fines, making it indispensable to invest in data protection measures.
9. Third-Party Audits: Intermediaries have to undergo security audits by external auditors to ensure they are meeting the expeditions of the following compliances.
10. Third-Party Information Sharing Restrictions: Sharing personal information and users’ data with third parties (such as advertisers) come with more detailed and disciplined guideline and user consent.

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Conclusion 

The Data Protection Data Privacy Act 2023 prioritises user consent, ensuring uninterrupted services and purpose-limited data processing. It aims to prevent data misuse, emphasising seamless user experiences and data minimisation. Drawing inspiration from global frameworks like the EU's GDPR, it introduces solidified consent mechanisms, transparency, and accountability. Users gain rights such as data portability and data deletion requests. Non-compliance results in significant fines. This legislation sets a new standard for user privacy and data protection, empowering users and holding platforms accountable. In an evolving digital landscape, it plays a crucial role in ensuring data security and responsible data handling.

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References:

• https://www.meity.gov.in/writereaddata/files/Digital%20Personal%20Data%20Protection%20Act%202023.pdf
• https://www.mondaq.com/india/privacy-protection/1355068/data-protection-law-in-india-analysis-of-dpdp-act-2023-for-businesses--part-i
• https://www.hindustantimes.com/technology/explained-indias-new-digital-personal-data-protection-framework-101691912775654.html

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In a recent ruling, a U.S. federal judge sided with Meta in a copyright lawsuit brought by a group of prominent authors who alleged that their works were illegally used to train Meta’s LLaMA language model. While this seems like a significant legal victory for the tech giant, it may not be so. Rather, this is a good case study for creators in the USA to refine their legal strategies and for policymakers worldwide to act quickly to shape the rules of engagement between AI and intellectual property.

The Case: Meta vs. Authors

In Kadrey v. Meta, the plaintiffs alleged that Meta trained its LLaMA models on pirated copies of their books, violating copyright law. However, U.S. District Judge Vince Chhabria ruled that the authors failed to prove two critical things: that their copyrighted works had been used in a way that harmed their market and that such use was not “transformative.” In fact, the judge ruled that converting text into numerical representations to train an AI was sufficiently transformative under the U.S. fair use doctrine. He also noted that the authors’ failure to demonstrate economic harm undermined their claims. Importantly, he clarified that this ruling does not mean that all AI training data usage is lawful, only that the plaintiffs didn’t make a strong enough case.

Meta even admitted that some data was sourced from pirate sites like LibGen, but the Judge still found that fair use could apply because the usage was transformative and non-exploitative.

A Tenuous Win

Chhabria’s decision emphasised that this is not a blanket endorsement of using copyrighted content in AI training. The judgment leaned heavily on the procedural weakness of the case and not necessarily on the inherent legality of Meta’s practices.

Policy experts are warning that U.S. courts are currently interpreting AI training as fair use in narrow cases, but the rulings may not set the strongest judicial precedent. The application of law could change with clearer evidence of commercial harm or a more direct use of content. 

Moreover, the ruling does not address whether authors or publishers should have the right to opt out of AI model training, a concern that is gaining momentum globally.

Implications for India

The case highlights a glaring gap in India’s copyright regime: it is outdated. Since most AI companies are located in the U.S., courts have had the opportunity to examine copyright in the context of AI-generated content. India has yet to start. Recently, news agency ANI filed a case alleging copyright infringement against OpenAI for training on its copyrighted material. However, the case is only at an interim stage. The final outcome of the case will have a significant impact on the legality of these language models being able to use copyrighted material for training.

Considering that India aims to develop “state-of-the-art foundational AI models trained on Indian datasets” under the IndiaAI Mission, the lack of clear legal guidance on what constitutes fair dealing when using copyrighted material for AI training is a significant gap.  

Thus, key points of consideration for policymakers include: 

• Need for Fair Dealing Clarity: India’s fair-dealing provisions under the Copyright Act, 1957, are narrower than U.S. fair use. The doctrine may have to be reviewed to strike a balance between this law and the requirement of diverse datasets to develop foundational models rooted in Indian contexts. A parallel concern regarding data privacy also arises. 
• Push for Opt-Out or Licensing Mechanisms: India should consider whether to introduce a framework that requires companies to license training data or provide an opt-out system for creators, especially given the volume of Indian content being scraped by global AI systems.
• Digital Public Infrastructure for AI: India’s policymakers could take this opportunity to invest in public datasets, especially in regional languages, that are both high quality and legally safe for AI training.
• Protecting Local Creators: India needs to ensure that its authors, filmmakers, educators and journalists are protected from having their work repurposed without compensation, since power asymmetries between Big Tech and local creators can lead to exploitation of the latter.

Conclusion

The ruling in Meta’s favour is just one win for the developer. The real questions about consent, compensation and creative control remain unanswered. Meanwhile, the lesson for India is urgent: it needs AI policies that balance innovation with creator rights and provide legal certainty and ethical safeguards as it accelerates its AI ecosystem. Further, as global tech firms race ahead, India must not remain a passive data source; it must set the terms of its digital future. This will help the country move a step closer to achieving its goal of building sovereign AI capacity and becoming a hub for digital innovation.

References

• https://www.theguardian.com/technology/2025/jun/26/meta-wins-ai-copyright-lawsuit-as-us-judge-rules-against-authors 
• https://www.wired.com/story/meta-scores-victory-ai-copyright-case/ 
• https://www.cnbc.com/2025/06/25/meta-llama-ai-copyright-ruling.html 
• https://www.mondaq.com/india/copyright/1348352/what-is-fair-use-of-copyright-doctrine 
• https://www.pib.gov.in/PressReleasePage.aspx?PRID=2113095#:~:text=One%20of%20the%20key%20pillars,models%20trained%20on%20Indian%20datasets. ‍
• https://www.ndtvprofit.com/law-and-policy/ani-vs-openai-delhi-high-court-seeks-responses-on-copyright-infringement-charges-against-chatgpt

Introduction

Digital Public Infrastructure (DPI) serves as the backbone of e-governance, enabling governments to deliver services more efficiently, transparently, and inclusively. By leveraging information and communication technology (ICT), digital governance systems reconfigure traditional administrative processes, making them more accessible and citizen-centric. However, the successful implementation of such systems hinges on overcoming several challenges, from ensuring data security to fostering digital literacy and addressing infrastructural gaps.

This article delves into the key enablers that drive effective DPI and outlines the measures already undertaken by the government to enhance its functionality. Furthermore, it outlines strategies for their enhancement, emphasizing the need for a collaborative, secure, and adaptive approach to building robust e-governance systems.

Key Enablers of DPI

Digital Public Infrastructure (DPI), the foundation for e-governance,  relies on common design, robust governance, and private sector participation for efficiency and inclusivity. This requires common principles, frameworks for collaboration, capacity building, and the development of common standards. Some of the key measures undertaken by the government in this regard include: 

1. Data Protection Framework: The Digital Personal Data Protection (DPDP) Act of 2023 establishes a framework to ensure consent-based data sharing and regulate the processing of digital personal data. It delineates the responsibilities of data fiduciaries in safeguarding users' digital personal data.
2. Increasing Public-Private Partnerships: Refining collaboration between the government and the private sector has accelerated the development, maintenance, expansion, and trust of the infrastructure of DPIs, such as the AADHAR, UPI, and  Data Empowerment and Protection Architecture (DEPA). For example, the Asian Development Bank attributes the success of UPI to its “consortium ownership structure”, which enables the wide participation of major financial stakeholders in the country.
3. Coordinated Planning: The PM-Gati Shakti establishes a clear coordination framework involving various inter-governmental stakeholders at the state and union levels. This aims to significantly reduce project duplications, delays, and cost escalations by streamlining communication, harmonizing project appraisal and approval processes, and providing a comprehensive database of major infrastructure projects in the country. This database called the National Master Plan, is jointly accessible by various government stakeholders through APIs.
4. Capacity Building for Government Employees:  The National e-Governance Division of the Ministry of Electronics and Information Technology routinely rolls out multiple training programs to build the technological and managerial skills required by government employees to manage Digital Public Goods (DPGs). For instance, it recently held a program on “Managing Large Digital Transformative Projects”. Additionally, the Ministry of Personnel, Public Grievances, and Pensions has launched the Integrated Government Online Training platform  (iGOT) Karmayogi for the continuous learning of civil servants across various domains. 

Digital Governance; Way Forward

E-governance utilizes information and communication technology (ICT) such as Wide Area Networks, the Internet, and mobile computing to implement existing government activities, reconfiguring the structures and processes of governance systems. This warrants addressing certain inter-related challenges such as : 

1. Data Security: The dynamic and ever-changing landscape of cyber threats necessitates regular advancements in data and information security technologies, policy frameworks, and legal provisions. Consequently, the digital public ecosystem must incorporate robust data cybersecurity measures, advanced encryption technologies, and stringent privacy compliance standards to safeguard against data breaches.
2. Creating Feedback Loops: Regular feedback surveys will help government agencies improve the quality, efficiency, and accessibility of digital governance services by tailoring them to be more user-friendly and enhancing administrative design. This is necessary to build trust in government services and improve their uptake among beneficiaries. Conducting the decennial census is essential to gather updated data that can serve as a foundation for more informed and effective decision-making.
3. Capacity Building for End-Users: The beneficiaries of key e-governance projects like Aadhar and UPI may have inadequate technological skills, especially in regions with weak internet network infrastructure like hilly or rural areas. This can present challenges in the access to and usage of technological solutions.  Robust capacity-building campaigns for beneficiaries can provide an impetus to the digital inclusion efforts of the government.
4. Increasing the Availability of Real-Time Data: By prioritizing the availability of up-to-date information, governments and third-party enterprises can enable quick and informed decision-making.  They can effectively track service usage, assess quality, and monitor key metrics by leveraging real-time data. This approach is essential for enhancing operational efficiency and delivering improved user experience.
5. Resistance to Change: Any resistance among beneficiaries or government employees to adopt digital governance goods may stem from a limited understanding of digital processes and a lack of experience with transitioning from legacy systems.  Hand-holding employees during the transitionary phase can help create more trust in the process and strengthen the new systems. 

Conclusion

Digital governance is crucial to transforming public services, ensuring transparency, and fostering inclusivity in a rapidly digitizing world. The successful implementation of such projects requires addressing challenges like data security, skill gaps, infrastructural limitations, feedback mechanisms, and resistance to change. Addressing these challenges with a strategic, multi-stakeholder approach can ensure the successful execution and long-term impact of large digital governance projects. By adopting robust cybersecurity frameworks, fostering public-private partnerships, and emphasizing capacity building, governments can create efficient and resilient systems that are user-centric, secure, and accessible to all. 

References

• https://www.adb.org/sites/default/files/publication/865106/adbi-wp1363.pdf 
• https://www.jotform.com/blog/government-digital-transformation-challenges/ 
• https://aapti.in/wp-content/uploads/2024/06/AaptixONI-DPIGovernancePlaybook_compressed.pdf 
• https://community.nasscom.in/sites/default/files/publicreport/Digital%20Public%20Infrastructure%2022-2-2024_compressed.pdf 
• https://proteantech.in/articles/Decoding-Digital-Public-Infrastructure-in-India/ 

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