#FactCheck-Viral ‘Human Pyramid Surviving Strong Winds’ Video Is AI-Generated Introduction

Introduction

Recently the Indian Government banned the import of Laptops and tablets in India under the computers of HSN 8471. According to the notification of the government, Directorate General of foreign trade, there will be restrictions on the import of Laptops, tablets, and other electronic items from 1^st November 2023. The government advised the Domestic companies to apply for the license within three months. As the process is simple, and many local companies have already applied for the license. The government will require a valid license for the import of laptops and other electronic items.

The Government imposed restrictions on the Import of Laptops & other electronic products

The DGFT (The directorate General of foreign trade) imposed restrictions on the import of electronic items in India. And, there has been the final date has also been given that the companies only have 3 months to apply for a valid license, from November 1^st 2023there will be a requirement for a valid license for the import, and there will be a proper ban on the import of laptops & tablets, and other electronic items. The ban is on the HSN-8471. These are the products that indicate that they are taxable. It is a classification code to identify the taxable items. India has sufficient capacity and capability to manufacture their own IT hardware devices and boost production.

The government has notified production linked incentive, PLI Scheme 2.0, for the IT devices, which will soon be disclosed, and the scheme is expected to lead to a total of 29 thousand crore rupees worth of IT hardware nearly. And this will create future job opportunities in the five to six years.

The pros & cons of the import

Banning import has two sides. The positive one is that, it will promote the domestic manufacturers, local companies will able to grow, and there will be job opportunities, but if we talk about the negative side of the import, then the prices will be high for the consumers. One aspect is making India’s digital infrastructure stable, and the other side is affecting consumers.

Reasons Behind the ban on the Import of electronic items

There are the following reasons behind the ban on the Import of laptops and tablets,

• The primary reason why the government banned the import of laptops and other electronic items is because of security concerns about the data. And to prevent data theft a step has been taken by the Government.
• The banning will help the domestic manufacturer to grow and will provide opportunities to the local companies in India.
• It will help in the creation of Job vacancies in the country.
• There will be a curb down of selling of Chinese products.

The government will promote the digital infrastructure of India by putting a ban on imports. Such as there are domestic companies like Reliance recently launched a laptop by the name of Jio Book, and there is a company that sells the cheapest tablet called Aakash, so the import ban will promote these types of electronic items of the local companies. This step will soon result in digital advancement in India.

Conclusion

The laptop, tablets, and other electronic products that have been banned in India will make a substantial move with the implications. The objective of the ban is to encourage domestic manufacturing and to secure the data, however, it will also affect the consumers which can not be ignored. The other future effects are yet to be seen. But the one scenario is clear, that the policy will significantly make a change in India’s Technology industry.

Introduction 

The link between social media and misinformation is undeniable. Misinformation, particularly the kind that evokes emotion, spreads like wildfire on social media and has serious consequences, like undermining democratic processes, discrediting science, and promulgating hateful discourses which may incite physical violence. If left unchecked, misinformation propagated through social media has the potential to incite social disorder, as seen in countless ethnic clashes worldwide.  This is why social media platforms have been under growing pressure to combat misinformation and have been developing models such as fact-checking services and community notes to check its spread. This article explores the pros and cons of the models and evaluates their broader implications for online information integrity.

How the Models Work 

1. Third-Party Fact-Checking Model (formerly used by Meta) Meta initiated this program in 2016 after claims of extraterritorial election tampering through dis/misinformation on its platforms. It entered partnerships with third-party organizations like AFP and specialist sites like Lead Stories and PolitiFact, which are certified by the International Fact-Checking Network (IFCN) for meeting neutrality, independence, and editorial quality standards. These fact-checkers identify misleading claims that go viral on platforms and publish verified articles on their websites, providing correct information. They also submit this to Meta through an interface, which may link the fact-checked article to the social media post that contains factually incorrect claims. The post then gets flagged for false or misleading content, and a link to the article appears under the post for users to refer to. This content will be demoted in the platform algorithm, though not removed entirely unless it violates Community Standards. However, in January 2025, Meta announced it was scrapping this program and beginning to test X’s Community Notes Model in the USA, before rolling it out in the rest of the world. It alleges that the independent fact-checking model is riddled with personal biases, lacks transparency in decision-making, and has evolved into a censoring tool. 
2. Community Notes Model ( Used by X and being tested by Meta): This model relies on crowdsourced contributors who can sign up for the program, write contextual notes on posts and rate the notes made by other users on X. The platform uses a bridging algorithm to display those notes publicly, which receive cross-ideological consensus from voters across the political spectrum. It does this by boosting those notes that receive support despite the political leaning of the voters, which it measures through their engagements with previous notes. The benefit of this system is that it is less likely for biases to creep into the flagging mechanism. Further, the process is relatively more transparent than an independent fact-checking mechanism since all Community Notes contributions are publicly available for inspection, and the ranking algorithm can be accessed by anyone, allowing for external evaluation of the system by anyone. 

CyberPeace Insights

Meta’s uptake of a crowdsourced model signals social media’s shift toward decentralized content moderation, giving users more influence in what gets flagged and why. However, the model’s reliance on diverse agreements can be a time-consuming process. A study (by Wirtschafter & Majumder, 2023) shows that only about 12.5 per cent of all submitted notes are seen by the public, making most misleading content go unchecked. Further, many notes on divisive issues like politics and elections may not see the light of day since reaching a consensus on such topics is hard. This means that many misleading posts may not be publicly flagged at all, thereby hindering risk mitigation efforts. This casts aspersions on the model’s ability to check the virality of posts which can have adverse societal impacts, especially on vulnerable communities. On the other hand, the fact-checking model suffers from a lack of transparency, which has damaged user trust and led to allegations of bias. 

Since both models have their advantages and disadvantages, the future of misinformation control will require a hybrid approach. Data accuracy and polarization through social media are issues bigger than an exclusive tool or model can effectively handle. Thus, platforms can combine expert validation with crowdsourced input to allow for accuracy, transparency, and scalability. 

Conclusion 

Meta’s shift to a crowdsourced model of fact-checking is likely to have bigger implications on public discourse since social media platforms hold immense power in terms of how their policies affect politics, the economy, and societal relations at large.  This change comes against the background of sweeping cost-cutting in the tech industry, political changes in the USA and abroad, and increasing attempts to make Big Tech platforms more accountable in jurisdictions like the EU and Australia, which are known for their welfare-oriented policies. These co-occurring contestations are likely to inform the direction the development of misinformation-countering tactics will take.  Until then, the crowdsourcing model is still in development, and its efficacy is yet to be seen, especially regarding polarizing topics. 

References 

• https://www.cyberpeace.org/resources/blogs/new-youtube-notes-feature-to-help-users-add-context-to-videos
• https://en-gb.facebook.com/business/help/315131736305613?id=673052479947730
• http://techxplore.com/news/2025-01-meta-fact.html 
• https://about.fb.com/news/2025/01/meta-more-speech-fewer-mistakes/ 
• https://communitynotes.x.com/guide/en/about/introduction 
• https://blogs.lse.ac.uk/impactofsocialsciences/2025/01/14/do-community-notes-work/?utm_source=chatgpt.com 
• https://www.techpolicy.press/community-notes-and-its-narrow-understanding-of-disinformation/ 
• https://www.rstreet.org/commentary/metas-shift-to-community-notes-model-proves-that-we-can-fix-big-problems-without-big-government/ 
• https://tsjournal.org/index.php/jots/article/view/139/57 

‍

As Generative AI continues to make strides by creating content through user prompts, the increasing sophistication of language models widens the scope of the services they can deliver. However, they have their own limitations. Recently, alerts by Apple Intelligence on the iPhone’s latest version have come under fire for misrepresenting news by news agencies.

The new feature was introduced with the aim of presenting an effective way to group and summarise app notifications in a single alert on a user’s lock screen. This was to enable an easier scan for important details amongst a large number of notifications, doing away with overwhelming updates for the user. This, however, resulted in the misrepresentation of news channels and reporting of fake news such as the arrest of Israeli Prime Minister Benjamin Netanyahu, Luke Litter winning the PDC World Darts Championship even before the competition, tennis Player Rafael Nadal coming out as gay, among other news alerts. Following false alerts, BBC had complained about its journalism being misrepresented. In response, Apple’s proposed solution was to clarify to the user that when the text summary is displayed in the notifications, it is clearly stated to be a product of notification Apple Intelligence and not of the news agency. It also claimed the complexity of having to compress content into short summaries which resulted in fallacious alerts. Further comments revealed that the AI alert feature was in beta and is continuously being worked on depending on the user’s feedback. Owing to the backlash, Apple has suspended this service and announced that an improved version of the feature is set to be released in the near future, however, no dates have been set.

CyberPeace Insights

The rush to release new features often exacerbates the problem, especially when AI-generated alerts are responsible for summarising news reports. This can significantly damage the credibility and trust that brands have worked hard to build. The premature release of features that affect the dissemination, content, and public comprehension of information carries substantial risks, particularly in the current environment where misinformation is widespread. Timely action and software updates, which typically require weeks to implement, are crucial in mitigating these risks. The desire to be ahead in the game and bring out competitive features must not resolve the responsibility of providing services that are secure and reliable. This aforementioned incident highlights the inherent nature of generative AI, which operates by analysing the data it was trained on to deliver the best possible responses based on user prompts. However, these responses are not always accurate or reliable. When faced with prompts beyond its scope, AI systems often produce untrustworthy information, underlining the need for careful oversight and verification. A question to deliberate on is whether we require such services at all, which in practice, do save our time, but do so at the risk of the spread of false tidbits.

References

• https://www.theguardian.com/technology/2025/jan/07/apple-update-ai-inaccurate-news-alerts-bbc-apple-intelligence-iphone
• https://www.firstpost.com/tech/apple-intelligence-hallucinates-falsely-credits-bbc-for-fake-news-broadcaster-lodges-complaint-13845214.html
• https://www.cnbc.com/2025/01/08/apple-ai-fake-news-alerts-highlight-the-techs-misinformation-problem.html
• https://news.sky.com/story/apple-ai-feature-must-be-revoked-over-notifications-misleading-users-say-journalists-13288716
• https://www.hindustantimes.com/world-news/apple-to-pay-95-million-in-user-privacy-violation-lawsuit-on-siri-101735835058198.html
• https://www.hindustantimes.com/business/apple-denies-claims-of-siri-violating-user-privacy-after-95-million-class-action-suit-settlement-101736445941497.html#:~:text=Apple%20denies%20claims%20of%20Siri,action%20suit%20settlement%20%2D%20Hindustan%20Times
• https://www.google.com/search?q=apple+AI+alerts+misinformation&oq=apple+AI+alerts+misinformation+&gs_lcrp=EgZjaHJvbWUyBggAEEUYOTIHCAEQIRigATIHCAIQIRigATIHCAMQIRigATIHCAQQIRigAdIBCTEyMzUxajBqN6gCALACAA&sourceid=chrome&ie=UTF-8
• https://www.fastcompany.com/91261727/apple-intelligence-news-summaries-mistakes
• https://timesofindia.indiatimes.com/technology/tech-news/siris-secret-listening-costs-apple-95m/articleshow/116906209.cms
• https://www.theguardian.com/technology/2025/jan/17/apple-suspends-ai-generated-news-alert-service-after-bbc-complaint 

‍

‍