#FactCheck-India Passport Ranking Claim Comparing 2014 and 2026 Rankings Is Misleading

Introduction

The first activity one engages in while using social media is scrolling through their feed and liking or reacting to posts. Social media users' online activity is passive, involving merely reading and observing, while active use occurs when a user consciously decides to share information or comment after actively analysing it. We often "like" photos, posts, and tweets reflexively, hardly stopping to think about why we do it and what information it contains. This act of "liking" or "reacting" is a passive activity that can spark an active discourse. Frequently, we encounter misinformation on social media in various forms, which could be identified as false at first glance if we exercise caution and avoid validating it with our likes.

Passive engagement, such as liking or reacting to a post, triggers social media algorithms to amplify its reach, exposing it to a broader audience. This amplification increases the likelihood of misinformation spreading quickly as more people interact with it. As the content circulates, it gains credibility through repeated exposure, reinforcing false narratives and expanding its impact.

Social media platforms are designed to facilitate communication and conversations for various purposes. However, this design also enables the sharing, exchange, distribution, and reception of content, including misinformation. This can lead to the widespread spread of false information, influencing public opinion and behaviour. Misinformation has been identified as a contributing factor in various contentious events, ranging from elections and referenda to political or religious persecution, as well as the global response to the COVID-19 pandemic.

The Mechanics of Passive Sharing

Sharing a post without checking the facts mentioned or sharing it without providing any context can create situations where misinformation can be knowingly or unknowingly spread. The problem with sharing and forwarding information on social media without fact-checking is that it usually starts in small, trusted networks before going on to be widely seen across the internet. This web which begins is infinite and cutting it from the roots is necessary. The rapid spread of information on social media is driven by algorithms that prioritise engagement and often they amplify misleading or false content and contribute to the spread of misinformation.  The algorithm optimises the feed and ensures that the posts that are most likely to engage with appear at the top of the timeline, thus encouraging a cycle of liking and posting that keeps users active and scrolling.

The internet reaches billions of individuals and enables them to tailor persuasive messages to the specific profiles of individual users. The internet because of its reach is an ideal medium for the fast spread of falsehoods at the expense of accurate information. 

Recommendations for Combating Passive Sharing

The need to combat passive sharing that we indulge in is important and some ways in which we can do so are as follows:

• We need to critically evaluate the sources before sharing any content. This will ensure that the information source is not corrupted and used as a means to cause disruptions. The medium should not be used to spread misinformation due to the source's ulterior motives. Tools such as crowdsourcing and AI methods have been used in the past to evaluate the sources and have been successful to an extent.
• Engaging with fact-checking tools and verifying the information is also crucial. The information that has been shared on the post needs to be verified through authenticated sources before indulging in the practice of sharing. 
• Being mindful of the potential impact of online activity, including likes and shares is important. The kind of reach that social media users have today is due to several reasons ranging from the content they create, the rate at which they engage with other users etc.  Liking and sharing content might not seem much for an individual user but the impact it has collectively is huge.

Conclusion 

Passive sharing of misinformation, like liking or sharing without verification, amplifies false information, erodes trust in legitimate sources, and deepens social and political divides. It can lead to real-world harm and ethical dilemmas. To combat this, critical evaluation, fact-checking, and mindful online engagement are essential to mitigating this passive spread of misinformation. The small act of “like” or “share” has a much more far-reaching effect than we anticipate and we should be mindful of all our activities on the digital platform. 

References

• https://www.tandfonline.com/doi/full/10.1080/00049530.2022.2113340#summary-abstract 
• https://timesofindia.indiatimes.com/city/thane/badlapur-protest-police-warn-against-spreading-fake-news/articleshow/112750638.cms

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Introduction

In the era of digitalisation, social media has become an essential part of our lives, with people spending a lot of time updating every moment of their lives on these platforms. Social media networks such as WhatsApp, Facebook, and YouTube have emerged as significant sources of Information. However, the proliferation of misinformation is alarming since misinformation can have grave consequences for individuals, organisations, and society as a whole. Misinformation can spread rapidly via social media, leaving a higher impact on larger audiences. Bad actors can exploit algorithms for their benefit or some other agenda, using tactics such as clickbait headlines, emotionally charged language, and manipulated algorithms to increase false information.

Impact 

The impact of misinformation on our lives is devastating, affecting individuals, communities, and society as a whole. False or misleading health information can have serious consequences, such as believing in unproven remedies or misinformation about some vaccines can cause serious illness, disability, or even death. Any misinformation related to any financial scheme or investment can lead to false or poor financial decisions that could lead to bankruptcy and loss of long-term savings.

In a democratic nation, misinformation plays a vital role in forming a political opinion, and the misinformation spread on social media during elections can affect voter behaviour, damage trust, and may cause political instability.

Mitigating strategies

The best way to minimise or stop the spreading of misinformation requires a multi-faceted approach. These strategies include promoting media literacy with critical thinking, verifying information before sharing, holding social media platforms accountable, regulating misinformation, supporting critical research, and fostering healthy means of communication to build a resilient society.

To put an end to the cycle of misinformation and move towards a better future, we must create plans to combat the spread of false information. This will require coordinated actions from individuals, communities, tech companies, and institutions to promote a culture of information accuracy and responsible behaviour.

The widespread spread of false information on social media platforms presents serious problems for people, groups, and society as a whole. It becomes clear that battling false information necessitates a thorough and multifaceted strategy as we go deeper into comprehending the nuances of this problem.

Encouraging consumers to develop media literacy and critical thinking abilities is essential to preventing the spread of false information. Being educated is essential for equipping people to distinguish between reliable sources and false information. Giving individuals the skills to assess information critically will enable them to choose the content they share and consume with knowledge. Public awareness campaigns should be used to promote and include initiatives that aim to improve media literacy in school curriculum.

Ways to Stop Misinformation

As we have seen, misinformation can cause serious implications; the best way to minimise or stop the spreading of misinformation requires a multifaceted approach; here are some strategies to combat misinformation.

• Promote Media Literacy with Critical Thinking: Educate individuals about how to critically evaluate information, fact check, and recognise common tactics used to spread misinformation, the users must use their critical thinking before forming any opinion or perspective and sharing the content.
• Verify Information: we must encourage people to verify the information before sharing, especially if it seems sensational or controversial, and encourage the consumption of news or any information from a reputable source of news that follows ethical journalistic standards.
• Accountability: Advocate for social media networks' openness and responsibility in the fight against misinformation. Encourage platforms to put in place procedures to detect and delete fraudulent content while boosting credible sources.
• Regulate Misinformation: Looking at the current situation, it is important to advocate for policies and regulations that address the spread of misinformation while safeguarding freedom of expression. Transparency in online communication by identifying the source of information and disclosing any conflict of interest.
• Support Critical Research: Invest in research and study on the sources, impacts, and remedies to misinformation. Support collaborative initiatives by social scientists, psychologists, journalists, and technology to create evidence-based techniques for countering misinformation. 

Conclusion

To prevent the cycle of misinformation and move towards responsible use of the Internet, we must create strategies to combat the spread of false information. This will require coordinated actions from individuals, communities, tech companies, and institutions to promote a culture of information accuracy and responsible behaviour.

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When your digital identity becomes raw material for someone else’s imagination, who really owns your face?

On July 7, 2026, Meta launched Muse Image, the first standalone image-generation model developed by Meta Superintelligence Labs under Alexandr Wang. Positioned as a competitor to OpenAI’s GPT Images 2.0 and Google’s Nano Banana 2, the launch highlights Meta’s growing ambitions in the generative AI race. Yet beneath the technical advancements lies a far more consequential question than what AI can create, but about who gets to decide what it creates with?

That ambition of generative AI comes with a cost, and one of Muse Image's most controversial design choices is its integration with Instagram, which allows public profiles to become creative references for AI-generated images. Users can tag public Instagram accounts in prompts and generate AI images inspired by that person’s publicly available content. Meta presents this as a new form of personalization and creativity. However, critics argue that the feature transforms years of personal photographs into a massive library of AI-ready human identities, where non-action automatically becomes permission. The concern is not just that AI can generate realistic images. The concern is that consent itself is being manipulated in a way.

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 The opt-out system most users never asked for

Muse Image operates through Meta AI’s integration with Instagram. A user can reference a public Instagram profile in a prompt, allowing the system to generate images influenced by that person’s existing content and likeness. Under the default arrangement, the person whose profile is being referenced may not necessarily approve the generation beforehand.

Meta does provide users with controls to restrict this functionality. The setting exists under Instagram’s “Sharing and reuse” options, where users can disable permissions related to the use of their posts and reels with Meta’s AI features. But the larger issue is the direction in which responsibility flows. Instead of requiring active permission before someone’s likeness becomes available for AI-generated content, the burden is placed on individuals to discover the feature, understand the implications, locate the setting, and disable it. In a digital environment where users already navigate endless privacy menus, cookie banners, and terms of service agreements, expecting meaningful awareness from billions of people becomes unrealistic. Consent that depends on finding the exit door is very different from consent that begins with a choice.

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A guide for opting-out

One way of opting out is to have a private account. As verified, Meta does not encroach on private accounts as of now for image-generation.

But if you have a public account, here are the steps that can be followed to secure yourself from Meta’s Muse automatic consent:

On your profile, tap the menu bar which is on the top right (≡), you will enter into ‘setting and activity’, after that you will see an option of ‘sharing and refuse’ and then disable the options under it, namely- Allow people to reuse your content on Instagram and with AI features at Meta. Notably, the changes made will be only for your future content not the already existing content on your public profile.

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 Why “public” does not mean “available for anything”

The debate around Muse Image highlights a deeper misunderstanding at the center of modern digital platforms: the difference between visibility and reuse. When someone makes an Instagram account public, they are generally making a decision about the audience. They are allowing others to view their photos, discover their profile, or engage with their content. That decision was never traditionally understood as permission for their face, appearance, personal moments, or identity markers to become reusable components in AI-generated media. A photograph posted online has context. It represents a specific moment, purpose, relationship, or expression. Generative AI changes that equation because it separates identity from context. A person’s likeness can be extracted from its original context and placed into entirely new situations created by someone else. Muse Image does not just expand who can see your content. It expands what can be done with it. That distinction is what scales the problem for every public user on the app. The privacy implications become significantly larger because of Instagram’s global reach. With billions of users worldwide, even a small percentage of affected public accounts represents an enormous number of people. Many public profiles do not belong to celebrities, influencers, or creators who intentionally operate as public brands. They belong to students, professionals, small businesses, artists, photographers, and everyday users who simply chose visibility within a social network.

For years, platforms encouraged people to share more, build audiences, and maintain a public digital presence. Now, the meaning of that public presence is changing after the fact. The question becomes: should a decision made years ago to share photos socially automatically extend into permission for generative AI systems built years later?

There is also a catch while opting out. Changing these settings only protects your content from being used in future AI generations,  it does not undo anything that has already happened. Any AI images previously created using your public profile will remain unaffected. Essentially, the opt-out works as a shield for what comes next, not a reset button for what has already been created.

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 A familiar pattern in the AI era

Muse Image reflects a broader pattern emerging across the technology industry. New AI capabilities are introduced at massive scale, participation becomes the default, and individual control arrives afterward through settings that many users may never find. The same debates that once surrounded targeted advertising, data collection, and algorithmic profiling are now moving into a far more personal territory, the human identity itself. Faces are not ordinary data points. Unlike a username, password, or preference setting, a person cannot simply replace their appearance once it has been widely replicated.

Technical solutions such as AI watermarking and content labels may help identify generated material, but they address authenticity after creation. They do not answer the question of whether the generation should have happened in the first place.

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 Innovation cannot replace consent

The technological progress behind Muse Image is significant. Better image generation, improved text rendering, and more personalized creative tools represent genuine advances in artificial intelligence. But capability alone cannot determine acceptability. The future of AI will not only depend on how realistic images become, how powerful models become, or how quickly companies can deploy new features. It will also depend on whether people feel they have meaningful control over their own digital identities. Muse Image is therefore more than another AI product launch. It represents a defining question for the next phase of the internet: Will our online presence remain something we control, or will it become something others can generate?

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