#FactCheck-Phishing Scam-LPG dealership of Hindustan Petroleum

Introduction

The unprecedented rise of social media, challenges with regional languages, and the heavy use of messaging apps like WhatsApp have all led to an increase in misinformation in India. False stories spread quickly and can cause significant harm, like political propaganda and health-related mis/misinformation. Programs that teach people how to use social media responsibly and attempt to check facts are essential, but they do not always connect with people deeply. Reading stories, attending lectures, and using tools that check facts are standard passive learning methods used in traditional media literacy programs. 

Adding game-like features to non-game settings is called "gamification," it could be a new and interesting way to answer this question. Gamification involves engaging people by making them active players instead of just passive consumers of information. Research shows that interactive learning improves interest, thinking skills, and memory. People can learn to recognise fake news safely by turning fact-checking into a game before encountering it in real life. A study by Roozenbeek and van der Linden (2019) showed that playing misinformation games can significantly enhance people's capacity to recognise and avoid false information.

Several misinformation-related games have been successfully implemented worldwide:

• The Bad News Game – This browser-based game by Cambridge University lets players step into the shoes of a fake news creator, teaching them how misinformation is crafted and spread (Roozenbeek & van der Linden, 2019).
• Factitious – A quiz game where users swipe left or right to decide whether a news headline is real or fake (Guess et al., 2020).
• Go Viral! – A game designed to inoculate people against COVID-19 misinformation by simulating the tactics used by fake news peddlers (van der Linden et al., 2020).

For programs to effectively combat misinformation in India, they must consider factors such as the responsible use of smartphones, evolving language trends, and common misinformation patterns in the country. Here are some key aspects to keep in mind:

1. Vernacular Languages

There should be games in Hindi, Tamil, Bengali, Telugu, and other major languages since that is how rumours spread in different areas and diverse cultural contexts. AI voice conversation and translation can help reduce literacy differences. Research shows that people are more likely to engage with and trust information in their native language (Pennycook & Rand, 2019).

2. Games Based on WhatsApp

Interactive tests and chatbot-powered games can educate consumers directly within the app they use most frequently since WhatsApp is a significant hub for false information. A game with a WhatsApp-like interface where players may feel like they are in real life, having to decide whether to avoid, check the facts of, or forward messages that are going viral could be helpful in India.

3. Detecting False Information

As part of a mobile-friendly game, players can pretend to be reporters or fact-checkers and have to prove stories that are going viral. They can do the same with real-life tools like reverse picture searches or reliable websites that check facts. Research shows that doing interactive tasks to find fake news makes people more aware of it over time (Lewandowsky et al., 2017).

4. Reward-Based Participation

Participation could be increased by providing rewards for finishing misleading challenges, such as badges, diplomas, or even incentives on mobile data. This might be easier to do if there are relationships with phone companies. Reward-based learning has made people more interested and motivated in digital literacy classes (Deterding et al., 2011).

5. Universities and Schools 

Educational institutions can help people spot false information by adding game-like elements to their lessons. Hamari et al. (2014) say that students are more likely to join and remember what they learn when there are competitive and interactive parts to the learning. Misinformation games can be used in media studies classes at schools and universities by using models to teach students how to check sources, spot bias, and understand the psychological tricks that misinformation campaigns use.

What Artificial Intelligence Can Do for Gamification

Artificial intelligence can tailor learning experiences to each player in false games. AI-powered misinformation detection bots could lead participants through situations tailored to their learning level, ensuring they are consistently challenged. Recent natural language processing (NLP) developments enable AI to identify nuanced misinformation patterns and adjust gameplay accordingly (Zellers et al., 2019). This could be especially helpful in India, where fake news is spread differently depending on the language and area.

Possible Opportunities

Augmented reality (AR) scavenger hunts for misinformation, interactive misinformation events, and educational misinformation tournaments are all examples of games that help fight misinformation. India can help millions, especially young people, think critically and combat the spread of false information by making media literacy fun and interesting. Using Artificial Intelligence (AI) in gamified treatments for misinformation could be a fascinating area of study in the future. AI-powered bots could mimic real-time cases of misinformation and give quick feedback, which would help students learn more.

Problems and Moral Consequences

While gaming is an interesting way to fight false information, it also comes with some problems that you should think about:

• Ethical Concerns: Games that try to imitate how fake news spreads must ensure players do not learn how to spread false information by accident.
• Scalability: Although worldwide misinformation initiatives exist, developing and expanding localised versions for India's varied language and cultural contexts provide significant challenges.
• Assessing Impact: There is a necessity for rigorous research approaches to evaluate the efficacy of gamified treatments in altering misinformation-related behaviours, keeping cultural and socio-economic contexts in the picture.

Conclusion 

A gamified approach can serve as an effective tool in India's fight against misinformation. By integrating game elements into digital literacy programs, it can encourage critical thinking and help people recognize misinformation more effectively. The goal is to scale these efforts, collaborate with educators, and leverage India's rapidly evolving technology to make fact-checking a regular practice rather than an occasional concern.

As technology and misinformation evolve, so must the strategies to counter them. A coordinated and multifaceted approach, one that involves active participation from netizens, strict platform guidelines, fact-checking initiatives, and support from expert organizations that proactively prebunk and debunk misinformation can be a strong way forward.

References

• Deterding, S., Dixon, D., Khaled, R., & Nacke, L. (2011). From game design elements to gamefulness: defining "gamification". Proceedings of the 15th International Academic MindTrek Conference.
• Guess, A., Nagler, J., & Tucker, J. (2020). Less than you think: Prevalence and predictors of fake news dissemination on Facebook. Science Advances.
• Hamari, J., Koivisto, J., & Sarsa, H. (2014). Does gamification work?—A literature review of empirical studies on gamification. Proceedings of the 47th Hawaii International Conference on System Sciences.
• Lewandowsky, S., Ecker, U. K., & Cook, J. (2017). Beyond misinformation: Understanding and coping with the “post-truth” era. Journal of Applied Research in Memory and Cognition.
• Pennycook, G., & Rand, D. G. (2019). Fighting misinformation on social media using “accuracy prompts”. Nature Human Behaviour.
• Roozenbeek, J., & van der Linden, S. (2019). The fake news game: actively inoculating against the risk of misinformation. Journal of Risk Research.
• van der Linden, S., Roozenbeek, J., Compton, J. (2020). Inoculating against fake news about COVID-19. Frontiers in Psychology.
• Zellers, R., Holtzman, A., Rashkin, H., Bisk, Y., Farhadi, A., Roesner, F., & Choi, Y. (2019). Defending against neural fake news. Advances in Neural Information Processing Systems.

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Introduction

The Telecommunications Act of 2023 was passed by Parliament in December, receiving the President's assent and being published in the official Gazette on December 24, 2023. The act is divided into 11 chapters 62 sections and 3 schedules. Sections 1, 2, 10-30, 42-44, 46, 47, 50-58, 61 and 62 already took effect on June 26, 2024. 

On July 04, 2024, the Centre issued a Gazetted Notification and sections 6-8, 48 and 59(b) were notified to be effective from July 05, 2024. The Act aims to amend and consolidate the laws related to telecommunication services, telecommunication networks, and spectrum assignment and it ‘repeals’ certain older colonial-era legislations like the Indian Telegraph Act 1885 and Indian Wireless Telegraph Act 1933. Due to the advancements in technology in the telecom sector, the new law is enacted. 

On 18 July 2024 Thursday, the telecom minister while launching the theme of Indian Mobile Congress (IMC), announced that all rules and provisions of the new Telecom Act would be notified within the next 180 days, hence making the Act operational at full capacity. 

Important definitions under Telecommunications Act, 2023

1. Authorisation: Section 2(d) entails “authorisation” means a permission, by whatever name called, granted under this Act for— (i) providing telecommunication services; (ii) establishing, operating, maintaining or expanding telecommunication networks; or (iii) possessing radio equipment.
2. Telecommunication: Section 2(p) entails “Telecommunication” means transmission, emission or reception of any messages, by wire, radio, optical or other electro-magnetic systems, whether or not such messages have been subjected to rearrangement, computation or other processes by any means in the course of their transmission, emission or reception.
3. Telecommunication Network: Section 2(s) entails “telecommunication network” means a system or series of systems of telecommunication equipment or infrastructure, including terrestrial or satellite networks or submarine networks, or a combination of such networks, used or intended to be used for providing telecommunication services, but does not include such telecommunication equipment as notified by the Central Government.
4. Telecommunication Service: Section 2(t) entails “telecommunication service” means any service for telecommunication.

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Measures for Cyber Security for the Telecommunication Network/Services

Section 22 of the Telecommunication Act, 2023 talks about the protection of telecommunication networks and telecommunication services. The section specifies that the centre may provide rules to ensure the cybersecurity of telecommunication networks and telecommunication services. Such measures may include the collection, analysis and dissemination of traffic data that is generated, transmitted, received or stored in telecommunication networks. ‘Traffic data’ can include any data generated, transmitted, received, or stored in telecommunication networks – such as type, duration, or time of a telecommunication. 

Section 22 further empowers the central government to declare any telecommunication network, or part thereof, as Critical Telecommunication Infrastructure. It may further provide for standards, security practices, upgradation requirements and procedures to be implemented for such Critical Telecommunication Infrastructure. 

CyberPeace Policy Wing Outlook:

The Telecommunication Act, 2023 marks a significant change & growth in the telecom sector by providing a robust regulatory framework, encouraging research and development, promoting infrastructure development, and measures for consumer protection. The Central Government is empowered to authorize individuals for (a) providing telecommunication services, (b) establishing, operating, maintaining, or expanding telecommunication networks, or (c) possessing radio equipment. Section 48 of the act provides no person shall possess or use any equipment that blocks telecommunication unless permitted by the Central Government. 

The Central Government will protect users by implementing different measures, such as the requirement of prior consent of users for receiving particular messages, keeping a 'Do Not Disturb' register to stop unwanted messages, the mechanism to enable users to report any malware or specified messages received, the preparation and maintenance of “Do Not Disturb” register, to ensure that users do not receive specified messages or class of specified messages without prior consent. The authorized entity providing telecommunication services will also be required to create an online platform for users for their grievances pertaining to telecommunication services. 

In certain limited circumstances such as national security measures, disaster management and public safety, the act contains provisions empowering the Government to take temporary possession of telecom services or networks from authorised entity; direct interception or disclosure of messages, with measures to be specified in rulemaking. This entails that the government gains additional controls in case of emergencies to ensure security and public order. However, this has to be balanced with appropriate measures protecting individual privacy rights and avoiding any unintended arbitrary actions. 

Taking into account the cyber security in the telecommunication sector, the government is empowered under the act to introduce standards for cyber security for telecommunication services and telecommunication networks; and encryption and data processing in telecommunication. 

The act also promotes the research and development and pilot projects under Digital Bharat Nidhi. The act also promotes the approach of digital by design by bringing online dispute resolution and other frameworks. Overall the approach of the government is noteworthy as they realise the need for updating the colonial era legislation considering the importance of technological advancements and keeping pace with the digital and technical revolution in the telecommunication sector. 

References:

1. The Telecommunications Act, 2023 https://acrobat.adobe.com/id/urn:aaid:sc:AP:88cb04ff-2cce-4663-ad41-88aafc81a416
2. https://pib.gov.in/PressReleasePage.aspx?PRID=2031057
3. https://pib.gov.in/PressReleaseIframePage.aspx?PRID=2027941
4. https://economictimes.indiatimes.com/industry/telecom/telecom-news/new-telecom-act-will-be-notified-in-180-days-bsnl-4g-rollout-is-monitored-on-a-daily-basis-scindia/articleshow/111851845.cms?from=mdr
5. https://www.azbpartners.com/wp-content/uploads/2024/06/Update-Staggered-Enforcement-of-Telecommunications-Act-2023.pdf
6. https://telecom.economictimes.indiatimes.com/blog/analysing-the-impact-of-telecommunications-act-2023-on-digital-india-mission/111828226

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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 

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