#FactCheck: An image shows Sunita Williams with Trump and Elon Musk post her space return.

Executive Summary:

Old footage of Indian Cricketer Virat Kohli celebrating Ganesh Chaturthi in September 2023 was being promoted as footage of Virat Kohli at the Ram Mandir Inauguration. A video of cricketer Virat Kohli attending a Ganesh Chaturthi celebration last year has surfaced, with the false claim that it shows him at the Ram Mandir consecration ceremony in Ayodhya on January 22. The Hindi newspaper Dainik Bhaskar and Gujarati newspaper Divya Bhaskar also displayed the now-viral video in their respective editions on January 23, 2024, escalating the false claim. After thorough Investigation, it was found that the Video was old and it was Ganesh Chaturthi Festival where the cricketer attended.

Claims:

Many social media posts, including those from news outlets such as Dainik Bhaskar and Gujarati News Paper Divya Bhaskar, show him attending the Ram Mandir consecration ceremony in Ayodhya on January 22, where after investigation it was found that the Video was of Virat Kohli attending Ganesh Chaturthi in September, 2023.

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The caption of Dainik Bhaskar E-Paper reads, “ क्रिकेटर विराट कोहली भी नजर आए ”

Fact Check:

CyberPeace Research Team did a reverse Image Search of the Video where several results with the Same Black outfit was shared earlier, from where a Bollywood Entertainment Instagram Profile named Bollywood Society shared the same Video in its Page, the caption reads, “Virat Kohli snapped for Ganapaati Darshan” the post was made on 20 September, 2023.

Taking an indication from this we did some keyword search with the Information we have, and it was found in an article by Free Press Journal, Summarizing the article we got to know that Virat Kohli paid a visit to the residence of Shiv Sena leader Rahul Kanal to seek the blessings of Lord Ganpati. The Viral Video and the claim made by the news outlet is false and Misleading.

Conclusion:

The recent Claim made by the Viral Videos and News Outlet is an Old Footage of Virat Kohli attending Ganesh Chaturthi the Video back to the year 2023 but not of the recent auspicious day of Ram Mandir Pran Pratishtha. To be noted that, we also confirmed that Virat Kohli hadn’t attended the Program; there was no confirmation that Virat Kohli attended on 22 January at Ayodhya. Hence, we found this claim to be fake.

• Claim:  Virat Kohli attending the Ram Mandir consecration ceremony in Ayodhya on January 22
• Claimed on: Youtube, X
• Fact Check: Fake

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Introduction

In today’s digital world, where everything is related to data, the more data you own, the more control and compliance you have over the market, which is why companies are looking for ways to use data to improve their business. But at the same time, they have to make sure they are protecting people’s privacy. It is very tricky to strike a balance between both of them. Imagine you are trying to bake a cake where you need to use all the ingredients to make it taste great, but you also have to make sure no one can tell what’s in it. That’s kind of what companies are dealing with when it comes to data. Here, ‘Pseudonymisation’ emerges as a critical technical and legal mechanism that offers a middle ground between data anonymisation and unrestricted data processing. 

Legal Framework and Regulatory Landscape 

Pseudonymisation, as defined by the General Data Protection Regulation (GDPR) in Article 4(5), refers to “the processing of personal data in such a manner that the personal data can no longer be attributed to a specific data subject without the use of additional information, provided that such additional information is kept separately and is subject to technical and organisational measures to ensure that the personal data are not attributed to an identified or identifiable natural person”. This technique represents a paradigm shift in data protection strategy, enabling organisations to preserve data utility while significantly reducing privacy risks. The growing importance of this balance is evident in the proliferation of data protection laws worldwide, from GDPR in Europe to India’s Digital Personal Data Protection Act (DPDP) of 2023. 

Its legal treatment varies across jurisdictions, but a convergent approach is emerging that recognises its value as a data protection safeguard while maintaining that the pseudonymised data remains personal data. Article 25(1) of GDPR recognises it as “an appropriate technical and organisational measure” and emphasises its role in reducing risks to data subjects. It protects personal data by reducing the risk of identifying individuals during data processing. The European Data Protection Board’s (EDPB) 2025 Guidelines on Pseudonymisation provide detailed guidance emphasising the importance of defining the “pseudonymisation domain”. It defines who is prevented from attributing data to specific individuals and ensures that the technical and organised measures are in place to block unauthorised linkage of pseudonymised data to the original data subjects. In India, while the DPDP Act does not explicitly define pseudonymisation, legal scholars argue that such data would still fall under the definition of personal data, as it remains potentially identifiable. The Act defines personal data defined in section 2(t) broadly as “any data about an individual who is identifiable by or in relation to such data,” suggesting that the pseudonymised information, being reversible, would continue to require compliance with data protection obligations. 

Further, the DPDP  Act, 2023 also includes principles of data minimisation and purpose limitation. Section 8(4) says that a “Data Fiduciary shall implement appropriate technical and organisational measures to ensure effective observance of the provisions of this Act and the Rules made under it.” The concept of Pseudonymization fits here because it is a recognised technical safeguard, which means companies can use pseudonymization as one of the methods or part of their compliance toolkit under Section 8(4) of the DPDP Act. However, its use should be assessed on a case to case basis, since ‘encryption’ is also considered one of the strongest methods for protecting personal data. The suitability of pseudonymization depends on the nature of the processing activity, the type of data involved, and the level of risk that needs to be mitigated. In practice, organisations may use pseudonymization in combination with other safeguards to strengthen overall compliance and security.

The European Court of Justice’s recent jurisprudence has introduced nuanced considerations about when pseudonymised data might not constitute personal data for certain entities. In cases where only the original controller possesses the means to re-identify individuals, third parties processing such data may not be subject to the full scope of data protection obligations, provided they cannot reasonably identify the data subjects. The “means reasonably likely” assessment represents a significant development in understanding the boundaries of data protection law. 

Corporate Implementation Strategies 

Companies find that pseudonymisation is not just about following rules, but it also brings real benefits. By using this technique, businesses can keep their data more secure and reduce the damage in the event of a breach. Customers feel more confident knowing that their information is protected, which builds trust. Additionally, companies can utilise this data for their research or other important purposes without compromising user privacy. 

Key Benefits of Pseudonymisation:

1. Enhanced Privacy Protection: It hides personal details like names or IDs with fake ones (with artificial values or codes), making it harder for accidental privacy breaches.
2. Preserved Data Utility: Unlike completely anonymous data, pseudonymised data keeps its usefulness by maintaining important patterns and relationships within datasets.
3. Facilitate Data Sharing: It’s easier to share pseudonymised data with partners or researchers because it protects privacy while still being useful.

However, using pseudonymisation is not as easy as companies have to deal with tricky technical issues like choosing the right methods, such as encryption or tokenisation and managing security keys safely. They have to implement strong policies to stop anyone from figuring out who the data belongs to. This can get expensive and complicated, especially when dealing with a large amount of data, and it often requires expert help and regular upkeep. 

Balancing Privacy Rights and Data Utility

The primary challenge in pseudonymisation is striking the right balance between protecting individuals' privacy and maintaining the utility of the data. To get this right, companies need to consider several factors, such as why they are using the data, the potential hacker's level of skill, and the type of data being used.

Conclusion 

Pseudonymisation offers a practical middle ground between full anonymisation and restricted data use, enabling organisations to harness the value of data while protecting individual privacy. Legally, it is recognised as a safeguard but still treated as personal data, requiring compliance under frameworks like GDPR and India’s DPDP Act. For companies, it is not only regulatory adherence but also ensuring that it builds trust and enhances data security. However, its effectiveness depends on robust technical methods, governance, and vigilance. Striking the right balance between privacy and data utility is crucial for sustainable, ethical, and innovation-driven data practices.

References:

1. https://gdpr-info.eu/art-4-gdpr/
2. https://www.meity.gov.in/static/uploads/2024/06/2bf1f0e9f04e6fb4f8fef35e82c42aa5.pdf
3. https://gdpr-info.eu/art-25-gdpr/
4. https://www.edpb.europa.eu/system/files/2025-01/edpb_guidelines_202501_pseudonymisation_en.pdf
5. https://curia.europa.eu/juris/document/document.jsf?text=&docid=303863&pageIndex=0&doclang=EN&mode=req&dir=&occ=first&part=1&cid=16466915
6. https://curia.europa.eu/juris/document/document.jsf?text=&docid=303863&pageIndex=0&doclang=EN&mode=req&dir=&occ=first&part=1&cid=16466915

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Introduction

Search engines have become indispensable in our daily lives, allowing us to find information instantly by entering keywords or phrases. Using the prompt "search Google or type a URL" reflects just how seamless this journey to knowledge has become. With millions of searches conducted every second, and Google handling over 6.3 million searches per minute as of 2023 (Statista), one critical question arises: do search engines prioritise results based on user preferences and past behaviours, or are they truly unbiased?

Understanding AI Bias in Search Algorithms

AI bias is also known as machine learning bias or algorithm bias. It refers to the occurrence of biased results due to human biases that deviate from the original training data or AI algorithm which leads to distortion of outputs and creation of potentially harmful outcomes. The sources of this bias are algorithmic bias, data bias and interpretation bias which emerge from user history, geographical data, and even broader societal biases in training data. 

Common biases include excluding certain groups of people from opportunities because of AI bias. In healthcare, underrepresenting data of women or minority groups can skew predictive AI algorithms. While AI helps streamline the automation of resume scanning during a search to help identify ideal candidates, the information requested and answers screened out can result in biased outcomes due to a biased dataset or any other bias in the input data.

Case in Point: Google’s "Helpful" Results and Its Impact 

Google optimises results by analysing user interactions to determine satisfaction with specific types of content. This data-driven approach forms ‘filter bubbles’ by repeatedly displaying content that aligns with a user’s preferences, regardless of factual accuracy. While this can create a more personalised experience, it risks confining users to a limited view, excluding diverse perspectives or alternative viewpoints.

The personal and societal impacts of such biases are significant. At an individual level, filter bubbles can influence decision-making, perceptions, and even mental health. On a societal level, these biases can reinforce stereotypes, polarise opinions, and shape collective narratives. There is also a growing concern that these biases may promote misinformation or limit users’ exposure to diverse perspectives, all stemming from the inherent bias in search algorithms.

Policy Challenges and Regulatory Measures

Regulating emerging technologies like AI, especially in search engine algorithms, presents significant challenges due to their intricate, proprietary nature. Traditional regulatory frameworks struggle to keep up with them as existing laws were not designed to address the nuances of algorithm-driven platforms. Regulatory bodies are pushing for transparency and accountability in AI-powered search algorithms to counter biases and ensure fairness globally. For example, the EU’s Artificial Intelligence Act aims to establish a regulatory framework that will categorise AI systems based on risk and enforces strict standards for transparency, accountability, and fairness, especially for high-risk AI applications, which may include search engines. India has proposed the Digital India Act in 2023 which will define and regulate High-risk AI. 

Efforts include ethical guidelines emphasising fairness, accountability, and transparency in information prioritisation. However, a complex regulatory landscape could hinder market entrants, highlighting the need for adaptable, balanced frameworks that protect user interests without stifling innovation.

CyberPeace Insights

In a world where search engines are gateways to knowledge, ensuring unbiased, accurate, and diverse information access is crucial. True objectivity remains elusive as AI-driven algorithms tend to personalise results based on user preferences and past behaviour, often creating a biased view of the web. Filter bubbles, which reinforce individual perspectives, can obscure factual accuracy and limit exposure to diverse viewpoints. Addressing this bias requires efforts from both users and companies. Users should diversify sources and verify information, while companies should enhance transparency and regularly audit algorithms for biases. Together, these actions can promote a more equitable, accurate, and unbiased search experience for all users. 

References 

• https://www.bbc.com/future/article/20241101-how-online-photos-and-videos-alter-the-way-you-think 
• https://www.bbc.com/future/article/20241031-how-google-tells-you-what-you-want-to-hear
• https://www.ibm.com/topics/ai-bias#:~:text=In%20healthcare%2C%20underrepresenting%20data%20of,can%20skew%20predictive%20AI%20algorithms

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