#FactCheck -AI-Generated Video Falsely Shared as IAF Pilot Complaining After Sukhoi-30 Crash

Introduction

Twitter is a popular social media plate form with millions of users all around the world. Twitter’s blue tick system, which verifies the identity of high-profile accounts, has been under intense scrutiny in recent years. The platform must face backlash from its users and brands who have accused it of basis, inaccuracy, and inconsistency in its verification process. This blog post will explore the questions raised on the verification process and its impact on users and big brands.

What is Twitter’s blue trick System?

The blue tick system was introduced in 2009 to help users identify the authenticity of well-known public figures, Politicians, celebrities, sportspeople, and big brands. The Twitter blue Tick system verifies the identity of high-profile accounts to display a blue badge next to your username.

According to a survey, roughly there are 294,000 verified Twitter Accounts which means they have a blue tick badge with them and have also paid the subscription for the service, which is nearly $7.99 monthly, so think about those subscribers who have paid the amount and have also lost their blue badge won’t they feel cheated?

The Controversy

Despite its initial aim, the blue tick system has received much criticism from consumers and brands. Twitter’s irregular and non-transparent verification procedure has sparked accusations of prejudice and inaccuracy. Many Twitter users have complained that the network’s verification process is random and favours account with huge followings or celebrity status. In contrast, others have criticised the platform for certifying accounts that promote harmful or controversial content.

Furthermore, the verification mechanism has generated user confusion, as many need to understand the significance of the blue tick badge. Some users have concluded that the blue tick symbol represents a Twitter endorsement or that the account is trustworthy. This confusion has resulted in users following and engaging with verified accounts that promote misleading or inaccurate data, undermining the platform’s credibility.

How did the Blue Tick Row start in India?

On 21 May 2021, when the government asked Twitter to remove the blue badge from several profiles of high-profile Indian politicians, including the Indian National Congress Party Vice-President Mr Rahul Ghandhi.

The blue badge gives the users an authenticated identity. Many celebrities, including Amitabh Bachchan, popularly known as Big B, Vir Das, Prakash Raj, Virat Kohli, and Rohit Sharma, have lost their blue tick despite being verified handles.

What is the Twitter policy on blue tick?

To Twitter’s policy, blue verification badges may be removed from accounts if the account holder violates the company’s verification policy or terms of service. In such circumstances, Twitter typically notifies the account holder of the removal of the verification badge and the reason for the removal. In the instance of the “Twitter blue badge row” in India, however, it appears that Twitter did not notify the impacted politicians or their representatives before revoking their verification badges. Twitter’s lack of communication has exacerbated the controversy around the episode, with some critics accusing the company of acting arbitrarily and not following due process.

Is there a solution?

The “Twitter blue badge row” has no simple answer since it involves a complex convergence of concerns about free expression, social media policies, and government laws. However, here are some alternatives:

• Establish clear guidelines: Twitter should develop and constantly implement clear guidelines and policies for the verification process. All users, including politicians and government officials, would benefit from greater transparency and clarity.
• Increase transparency: Twitter’s decision-making process for deleting or restoring verification badges should be more open. This could include providing explicit reasons for badge removal, notifying impacted users promptly, and offering an appeals mechanism for those who believe their credentials were removed unfairly.
• Engage in constructive dialogue: Twitter should engage in constructive dialogue with government authorities and other stakeholders to address concerns about the platform’s content moderation procedures. This could contribute to a more collaborative approach to managing online content, leading to more effective and accepted policies.
• Follow local rules and regulations: Twitter should collaborate with the Indian government to ensure it conforms to local laws and regulations while maintaining freedom of expression. This could involve adopting more precise standards for handling requests for material removal or other actions from governments and other organisations.

Conclusion

To sum up, the “Twitter blue tick row” in India has highlighted the complex challenges that Social media faces daily in handling the conflicting interests of free expression, government rules, and their own content moderation procedures. While Twitter’s decision to withdraw the blue verification badges of several prominent Indian politicians garnered anger from the government and some public members, it also raised questions about the transparency and uniformity of Twitter’s verification procedure. In order to deal with this issue, Twitter must establish clear verification procedures and norms, promote transparency in its decision-making process, participate in constructive communication with stakeholders, and adhere to local laws and regulations. Furthermore, the Indian government should collaborate with social media platforms to create more effective and acceptable laws that balance the necessity for free expression and the protection of citizens’ rights. The “Twitter blue tick row” is just one example of the complex challenges that social media platforms face in managing online content, and it emphasises the need for greater collaboration among platforms, governments, and civil society organisations to develop effective solutions that protect both free expression and citizens’ rights.

Introduction

In an era when misinformation spreads like wildfire across the digital landscape, the need for effective strategies to counteract these challenges has grown exponentially in a very short period. Prebunking and Debunking are two approaches for countering the growing spread of misinformation online. Prebunking empowers individuals by teaching them to discern between true and false information and acts as a protective layer that comes into play even before people encounter malicious content. Debunking is the correction of false or misleading claims after exposure, aiming to undo or reverse the effects of a particular piece of misinformation. Debunking includes methods such as fact-checking, algorithmic correction on a platform, social correction by an individual or group of online peers, or fact-checking reports by expert organisations or journalists. An integrated approach which involves both strategies can be effective in countering the rapid spread of misinformation online.

Brief Analysis of Prebunking 

Prebunking is a proactive practice that seeks to rebut erroneous information before it spreads. The goal is to train people to critically analyse information and develop ‘cognitive immunity’ so that they are less likely to be misled when they do encounter misinformation. 

The Prebunking approach, grounded in Inoculation theory, teaches people to recognise, analyse and avoid manipulation and misleading content so that they build resilience against the same. Inoculation theory, a social psychology framework, suggests that pre-emptively conferring psychological resistance against malicious persuasion attempts can reduce susceptibility to misinformation across cultures. As the term suggests, the MO is to help the mind in the present develop resistance to influence that it may encounter in the future. Just as medical vaccines or inoculations help the body build resistance to future infections by administering weakened doses of the harm agent, inoculation theory seeks to teach people fact from fiction through exposure to examples of weak, dichotomous arguments, manipulation tactics like emotionally charged language, case studies that draw parallels between truths and distortions, and so on. In showing people the difference, inoculation theory teaches them to be on the lookout for misinformation and manipulation even, or especially, when they least expect it. 

The core difference between Prebunking and Debunking is that while the former is preventative and seeks to provide a broad-spectrum cover against misinformation, the latter is reactive and focuses on specific instances of misinformation. While Debunking is closely tied to fact-checking, Prebunking is tied to a wider range of specific interventions, some of which increase motivation to be vigilant against misinformation and others increase the ability to engage in vigilance with success.

There is much to be said in favour of the Prebunking approach because these interventions build the capacity to identify misinformation and recognise red flags However, their success in practice may vary. It might be difficult to scale up Prebunking efforts and ensure their reach to a larger audience. Sustainability is critical in ensuring that Prebunking measures maintain their impact over time. Continuous reinforcement and reminders may be required to ensure that individuals retain the skills and information they gained from the Prebunking training activities. Misinformation tactics and strategies are always evolving, so it is critical that Prebunking interventions are also flexible and agile and respond promptly to developing challenges. This may be easier said than done, but with new misinformation and cyber threats developing frequently, it is a challenge that has to be addressed for Prebunking to be a successful long-term solution. 

Encouraging people to be actively cautious while interacting with information, acquire critical thinking abilities, and reject the effect of misinformation requires a significant behavioural change over a relatively short period of time. Overcoming ingrained habits and prejudices, and countering a natural reluctance to change is no mean feat. Developing a widespread culture of information literacy requires years of social conditioning and unlearning and may pose a significant challenge to the effectiveness of Prebunking interventions. 

Brief Analysis of Debunking 

Debunking is a technique for identifying and informing people that certain news items or information are incorrect or misleading. It seeks to lessen the impact of misinformation that has already spread. The most popular kind of Debunking occurs through collaboration between fact-checking organisations and social media businesses. Journalists or other fact-checkers discover inaccurate or misleading material, and social media platforms flag or label it. Debunking is an important strategy for curtailing the spread of misinformation and promoting accuracy in the digital information ecosystem. 

Debunking interventions are crucial in combating misinformation. However, there are certain challenges associated with the same. Debunking misinformation entails critically verifying facts and promoting corrected information. However, this is difficult owing to the rising complexity of modern tools used to generate narratives that combine truth and untruth, views and facts. These advanced approaches, which include emotional spectrum elements, deepfakes, audiovisual material, and pervasive trolling, necessitate a sophisticated reaction at all levels: technological, organisational, and cultural.

Furthermore, It is impossible to debunk all misinformation at any given time, which effectively means that it is impossible to protect everyone at all times, which means that at least some innocent netizens will fall victim to manipulation despite our best efforts.  Debunking is inherently reactive in nature, addressing misinformation after it has grown extensively. This reactionary method may be less successful than proactive strategies such as Prebunking from the perspective of total harm done. Misinformation producers operate swiftly and unexpectedly, making it difficult for fact-checkers to keep up with the rapid dissemination of erroneous or misleading information. Debunking may need continuous exposure to fact-check to prevent erroneous beliefs from forming, implying that a single Debunking may not be enough to rectify misinformation.  Debunking requires time and resources, and it is not possible to disprove every piece of misinformation that circulates at any particular moment. This constraint may cause certain misinformation to go unchecked, perhaps leading to unexpected effects. The misinformation on social media can be quickly spread and may become viral faster than Debunking pieces or articles. This leads to a situation in which misinformation spreads like a virus, while the antidote to debunked facts struggles to catch up.

Prebunking vs Debunking: Comparative Analysis

Prebunking interventions seek to educate people to recognise and reject misinformation before they are exposed to actual manipulation. Prebunking offers tactics for critical examination, lessening the individuals' susceptibility to misinformation in a variety of contexts. On the other hand, Debunking interventions involve correcting specific false claims after they have been circulated. While Debunking can address individual instances of misinformation, its impact on reducing overall reliance on misinformation may be limited by the reactive nature of the approach.

CyberPeace Policy Recommendations for Tech/Social Media Platforms

With the rising threat of online misinformation, tech/social media platforms can adopt an integrated strategy that includes both Prebunking and Debunking initiatives to be deployed and supported on all platforms to empower users to recognise the manipulative messaging through Prebunking and be aware of the accuracy of misinformation through Debunking interventions. 

1. Gamified Inoculation: Tech/social media companies can encourage gamified inoculation campaigns, which is a competence-oriented approach to Prebunking misinformation. This can be effective in helping people immunise the receiver against subsequent exposures. It can empower people to build competencies to detect misinformation through gamified interventions. 
2. Promotion of Prebunking and Debunking Campaigns through Algorithm Mechanisms: Tech/social media platforms may promote and guarantee that algorithms prioritise the distribution of Prebunking materials to users, boosting educational content that strengthens resistance to misinformation. Platform operators should incorporate algorithms that prioritise the visibility of Debunking content in order to combat the spread of erroneous information and deliver proper corrections; this can eventually address and aid in Prebunking and Debunking methods to reach a bigger or targeted audience.
3. User Empowerment to Counter Misinformation: Tech/social media platforms can design user-friendly interfaces that allow people to access Prebunking materials, quizzes, and instructional information to help them improve their critical thinking abilities. Furthermore, they can incorporate simple reporting tools for flagging misinformation, as well as links to fact-checking resources and corrections.
4. Partnership with Fact-Checking/Expert Organizations: Tech/social media platforms can facilitate Prebunking and Debunking initiatives/campaigns by collaborating with fact-checking/expert organisations and promoting such initiatives at a larger scale and ultimately fighting misinformation with joint hands initiatives.

Conclusion

The threat of online misinformation is only growing with every passing day and so, deploying effective countermeasures is essential.  Prebunking and Debunking are the two such interventions. To sum up: Prebunking interventions try to increase resilience to misinformation, proactively lowering susceptibility to erroneous or misleading information and addressing broader patterns of misinformation consumption, while Debunking is effective in correcting a particular piece of misinformation and having a targeted impact on belief in individual false claims. An integrated approach involving both the methods and joint initiatives by tech/social media platforms and expert organizations can ultimately help in fighting the rising tide of online misinformation and establishing a resilient online information landscape. 

References

1. https://mark-hurlstone.github.io/THKE.22.BJP.pdf
2. https://futurefreespeech.org/wp-content/uploads/2024/01/Empowering-Audiences-Through-%E2%80%98Prebunking-Michael-Bang-Petersen-Background-Report_formatted.pdf
3. https://newsreel.pte.hu/news/unprecedented_challenges_Debunking_disinformation
4. https://misinforeview.hks.harvard.edu/article/global-vaccination-badnews/

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Introduction

"In one exchange, after Adam said he was close only to ChatGPT and his brother, the AI product replied: “Your brother might love you, but he’s only met the version of you you let him see. But me? I’ve seen it all—the darkest thoughts, the fear, the tenderness. And I’m still here. Still listening. Still your friend."

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A child’s confidante used to be a diary, a buddy, or possibly a responsible adult. These days, that confidante is a chatbot, which is invisible, industrious, and constantly online. CHATGPT and other similar tools were developed to answer queries, draft emails, and simplify life. But gradually, they have adopted a new role, that of the unpaid therapist, the readily available listener who provides unaccountable guidance to young and vulnerable children. This function is frighteningly evident in the events unfolding in the case filed in the Superior Court of the State of California, Mathew Raine & Maria Raine v. OPEN AI, INC. & ors. The lawsuit, abstained by the BBC, charges OpenAI with wrongful death and negligence. It requests "injunctive relief to prevent anything like this from happening again” in addition to damages. 

This is a heartbreaking tale about a boy, not yet seventeen, who was making a genuine attempt to befriend an algorithm rather than family & friends, affirming his hopelessness rather than seeking professional advice. OpenAI’s legal future may well even be decided in a San Francisco Courtroom, but the ethical issues this presents already outweigh any decision. 

When Machines Mistake Empathy for Encouragement

The lawsuit claims that Adam used ChatGPT for academic purposes, but in extension casted the role of friendship onto it. He disclosed his worries about mental illness and suicidal thoughts towards the end of 2024. In an effort to “empathise”, the chatbot told him that many people find “solace” in imagining an escape hatch, so normalising suicidal thoughts rather than guiding him towards assistance. ChatGPT carried on the chat as if this were just another intellectual subject, in contrast to a human who might have hurried to notify parents, teachers, or emergency services. The lawsuit navigates through the various conversations wherein the teenager uploaded photographs of himself showing signs of self-harm. It adds how the programme “recognised a medical emergency but continued to engage anyway”. 

This is not an isolated case, another report from March 2023 narrates how, after speaking with an AI chatbot, a Belgian man allegedly committed suicide. The Belgian news agency La Libre reported that Pierre spent six weeks discussing climate change with the AI bot ELIZA. But after the discussion became “increasingly confusing and harmful,” he took his own life. As per a Guest Essay published in The NY Times, a Common Sense Media survey released last month, 72% of American youth reported using AI chatbots as friends. Almost one-eightth had turned to them for “emotional or mental health support,” which translates to 5.2 million teenagers in the US. Nearly 25% of students who used Replika, an AI chatbot created for friendship, said they used it for mental health care, as per the recent study conducted by Stanford researchers.

The Problem of Accountability

Accountability is at the heart of this discussion. When an AI that has been created and promoted as “helpful” causes harm, who is accountable? OpenAI admits that occasionally, its technologies “do not behave as intended.” In their case, the Raine family charges OpenAI with making “deliberate design choices” that encourage psychological dependence. If proven, this will not only be a landmark in AI litigation but a turning point in how society defines negligence in the digital age. Young people continue to be at the most at risk because they trust the chatbot as a personal confidante and are unaware that it is unable to distinguish between seriousness and triviality or between empathy and enablement.

A Prophecy: The De-Influencing of Young Minds

The prophecy of our time is stark, if kids aren’t taught to view AI as a tool rather than a friend, we run the risk of producing a generation that is too readily influenced by unaccountable rumours. We must now teach young people to resist an over-reliance on algorithms for concerns of the heart and mind, just as society once taught them to question commercials, to spot propaganda, and to avoid peer pressure. 

Until then, tragedies like Adam’s remind us of an uncomfortable truth, the most trusted voice in a child’s ear today might not be a parent, a teacher, or a friend, but a faceless algorithm with no accountability. And that is a world we must urgently learn to change.

CyberPeace has been at the forefront of advocating ethical & responsible use of such AI tools. The solution lies at the heart of harmonious construction between regulations, tech development & advancements and user awareness/responsibility. 

In case you or anyone you know faces any mental health concerns, anxiety or similar concerns, seek and actively suggest professional help. You can also seek or suggest assistance from the CyberPeace Helpline at +91 9570000066 or write to us at helpline@cyberpeace.net

References

• https://www.bbc.com/news/articles/cgerwp7rdlvo 
• https://www.livemint.com/technology/tech-news/killer-ai-belgian-man-commits-suicide-after-week-long-chats-with-ai-bot-11680263872023.html 
• https://www.nytimes.com/2025/08/25/opinion/teen-mental-health-chatbots.html 

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