#FactCheck - AI-Generated Image Falsely Linked to Doda Army Vehicle Accident

Introduction

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Purchasing online currencies through one of the numerous sizable digital marketplaces designed specifically for this purpose is the simplest method. The quantity of cryptocurrency and money paid. These online marketplaces impose an exchange fee. After being obtained, digital cash is stored in a digital wallet and can be used in the metaverse or as real money to make purchases of goods and services in the real world. Blockchain ensures the security and decentralisation of each exchange. 

Its worth and application are comparable to those of gold: when a large number of investors choose this valuable asset, its value increases and vice versa. This also applies to cryptocurrencies, which explains why they have become so popular in recent years. The metaphysical realm is an online space where users can communicate with one another via virtual personas, among other features. Furthermore, money and commerce always come up when people communicate. 

Web3 is welcoming the metaverse, and in an environment where conventional currency isn't functional, its technologies are making it possible to use cryptocurrencies. Non-Fungible Tokens (NFTs) can be used to monitor intellectual rights to ownership in the metaverse, while cryptocurrencies are used to pay for content and incentivise consumers. This write-up addresses what the metaverse crypto is. It also delves into the advantages, disadvantages, and applications of crypto in this context. 

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Convergence of Metaverse and Cryptocurrency

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As the main form of digital money in the Metaverse, digital currencies can be used to do business and exchange in the digital realm. The term "metaverse" describes a simulation of reality where users can communicate in real time with other users and an environment created by computers. The acquisition and exchange of virtual products, virtual possessions, and electronic creativity within the Metaverse can all be made possible via cryptocurrency. 

Many digital currencies are based on blockchain software, which can offer an accessible and safe way to confirm payments and manage digital currencies in the Metaverse. By giving consumers vouchers or other electronic currencies in exchange for their accomplishments or contributions, cryptocurrency might encourage consumer engagement and involvement in the Metaverse.

In the Metaverse, cryptocurrency can also facilitate portable connectivity, enabling users to move commodities and their worth between various virtual settings and platforms.

The idea of fragmentation in the Metaverse, where participants have more ownership and control over their virtual worlds, is consistent with the decentralised characteristics of cryptocurrencies.

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Advantages of Metaverse Cryptocurrency

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There are countless opportunities for creativity and discovery in the metaverse. Because the blockchain is accessible to everyone, unchangeable, and password-protected, metaverse-centric cryptocurrencies offer greater safety and adaptability than cash. Crypto will be crucial to the evolution of the metaverse as it keeps growing and more individuals show interest in using it. Here are a few of the variables influencing the growth of this new virtual environment.

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Safety

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Your Bitcoin wallet is intimately linked to your personal information, progress, and metaverse possessions. Additionally, if your digital currency wallet is compromised, especially if your account credentials are weak, public, or connected to your real-world identity, cybercriminals may try to steal your money or personal data. 

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Adaptability

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Digital assets can be accessed and exchanged worldwide due to cryptocurrencies’ ability to transcend national borders. By utilising a local cryptocurrency, many metaverse platforms streamline transactions and eliminate the need for frequent currency conversions between various digital or fiat currencies. Another advantage of using autonomous contract languages is for metaverse cryptos. When consumers make transactions within the network, applications do away with the need for administrative middlemen.

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Objectivity

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By exposing interactions in a publicly accessible distributed database, the use of blockchain improves accountability. It is more difficult for dishonest people to raise the cost of digital goods and land since Bitcoin transactions are public. Metaverse cryptocurrencies are frequently employed to control project modifications. The outcomes of these legislative elections are made public using digital contracts. 

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NFT, Virtual worlds, and Digital currencies  

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Using the NFT is an additional method of using Bitcoin for metaverse transactions. These are distinct electronic documents that have significant potential value.  

A creator must convert an electronic work of art into a virtual object or virtual world if they want to display it digitally in the metaverse. Artists produce one-of-a-kind, serialised pieces that are given an NFT that may be acquired through Bitcoin payments. 

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Applications of Metaverse Cryptography

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Fiat money or independent virtual currencies like Robux are used by Web 2 metaverse initiatives to pay for goods, real estate, and services. Fiat lacked the adaptability of cryptocurrencies with automated contract capabilities, even though it may be used to pay for goods and finance the creation of projects. Users can stake these within the network virtual currencies to administer distributed metaverses, and they have all the same functions as fiat currency.

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Banking operations

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Lending digital cash to purchase metaverse land is possible. Banks that have already made inroads into the metaverse include HSBC and JPMorgan, both of which possess virtual real estate. "We are making our foray into the metaverse, allowing us to create innovative brand experiences for both new and existing customers," said Suresh Balaji, chief marketing officer for HSBC in Asia-Pacific.

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Purchasing

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An increasingly important aspect of the metaverse is online commerce. Users can interact with real-world brands, tour simulated malls, and try on virtual apparel for their characters. Adidas, for instance, debuted an NFT line in 2021 that included customizable peripherals for the Sandbox. Buyers of NFTs crossed the line separating the virtual universe and the actual world to obtain the tangible goods associated with their NFTs.

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Authority

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Metaverse initiatives are frequently governed by cryptocurrency. Decentraland, a well-known Ethereum-based metaverse featuring virtual reality components, permits users to submit and vote on suggestions provided they own specific tokens.

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Conclusion

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The combination of the virtual world and cryptocurrencies creates novel opportunities for trade, innovation, and communication. The benefits of using the blockchain system are increased objectivity, safety, and flexibility. By facilitating exclusive ownership of digital assets, NFTs enhance metaverse immersion even more. In the metaverse, cryptocurrencies are used in banking, shopping, and government, forming a user-driven, autonomous digital world. The combination of cryptocurrencies and the metaverse will revolutionise how we interact with online activities, creating a dynamic environment that presents both opportunities and difficulties.

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References

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• https://www.telefonica.com/en/communication-room/blog/metaverse-and-cryptocurrencies-what-is-their-relationship/
• https://hedera.com/learning/metaverse/metaverse-crypto
• https://www.linkedin.com/pulse/unleashing-power-connection-between-cryptocurrency-ai-amit-chandra/

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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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Introduction

The Senate bill introduced on 19 March 2024 in the United States would require online platforms to obtain consumer consent before using their data for Artificial Intelligence (AI) model training. If a company fails to obtain this consent, it would be considered a deceptive or unfair practice and result in enforcement action from the Federal Trade Commission (FTC) under the AI consumer opt-in, notification standards, and ethical norms for training (AI Consent) bill. The legislation aims to strengthen consumer protection and give Americans the power to determine how their data is used by online platforms. 

The proposed bill also seeks to create standards for disclosures, including requiring platforms to provide instructions to consumers on how they can affirm or rescind their consent. The option to grant or revoke consent should be made available at any time through an accessible and easily navigable mechanism, and the selection to withhold or reverse consent must be at least as prominent as the option to accept while taking the same number of steps or fewer as the option to accept.

The AI Consent bill directs the FTC to implement regulations to improve transparency by requiring companies to disclose when the data of individuals will be used to train AI and receive consumer opt-in to this use. 
The bill also commissions an FTC report on the technical feasibility of de-identifying data, given the rapid advancements in AI technologies, evaluating potential measures companies could take to effectively de-identify user data.

The definition of ‘Artificial Intelligence System’ under the proposed bill

ARTIFICIALINTELLIGENCE SYSTEM- The term artificial intelligence system“ means a machine-based system that—

1. Is capable of influencing the environment by producing an output, including predictions, recommendations or decisions, for a given set of objectives; and
2. 2. Uses machine or human-based data and inputs to

(i) Perceive real or virtual environments;

(ii) Abstract these perceptions into models through analysis in an automated manner (such as by using machine learning) or manually; and

(iii) Use model inference to formulate options for outcomes.

Importance of the proposed AI Consent Bill USA

1. Consumer Data Protection: The AI Consent bill primarily upholds the privacy rights of an individual. Consent is necessitated from the consumer before data is used for AI Training; the bill aims to empower individuals with unhinged autonomy over the use of personal information. The scope of the bill aligns with the greater objective of data protection laws globally, stressing the criticality of privacy rights and autonomy.

2. Prohibition Measures: The proposed bill intends to prohibit covered entities from exploiting the data of consumers for training purposes without their consent. This prohibition extends to the sale of data, transfer to third parties and usage. Such measures aim to prevent data misuse and exploitation of personal information. The bill aims to ensure companies are leveraged by consumer information for the development of AI without a transparent process of consent.

3. Transparent Consent Procedures: The bill calls for clear and conspicuous disclosures to be provided by the companies for the intended use of consumer data for AI training. The entities must provide a comprehensive explanation of data processing and its implications for consumers. The transparency fostered by the proposed bill allows consumers to make sound decisions about their data and its management, hence nurturing a sense of accountability and trust in data-driven practices.

4. Regulatory Compliance: The bill's guidelines call for strict requirements for procuring the consent of an individual. The entities must follow a prescribed mechanism for content solicitation, making the process streamlined and accessible for consumers. Moreover, the acquisition of content must be independent, i.e. without terms of service and other contractual obligations. These provisions underscore the importance of active and informed consent in data processing activities, reinforcing the principles of data protection and privacy.

5. Enforcement and Oversight: To enforce compliance with the provisions of the bill, robust mechanisms for oversight and enforcement are established. Violations of the prescribed regulations are treated as unfair or deceptive acts under its provisions. Empowering regulatory bodies like the FTC to ensure adherence to data privacy standards. By holding covered entities accountable for compliance, the bill fosters a culture of accountability and responsibility in data handling practices, thereby enhancing consumer trust and confidence in the digital ecosystem.

Importance of Data Anonymization

Data Anonymization is the process of concealing or removing personal or private information from the data set to safeguard the privacy of the individual associated with it. Anonymised data is a sort of information sanitisation in which data anonymisation techniques encrypt or delete personally identifying information from datasets to protect data privacy of the subject. This reduces the danger of unintentional exposure during information transfer across borders and allows for easier assessment and analytics after anonymisation. When personal information is compromised, the organisation suffers not just a security breach but also a breach of confidence from the client or consumer. Such assaults can result in a wide range of privacy infractions, including breach of contract, discrimination, and identity theft.

The AI consent bill asks the FTC to study data de-identification methods. Data anonymisation is critical to improving privacy protection since it reduces the danger of re-identification and unauthorised access to personal information. Regulatory bodies can increase privacy safeguards and reduce privacy risks connected with data processing operations by investigating and perhaps implementing anonymisation procedures.

The AI consent bill emphasises de-identification methods, as well as the DPDP Act 2023 in India, while not specifically talking about data de-identification, but it emphasises the data minimisation principles, which highlights the potential future focus on data anonymisation processes or techniques in India.

Conclusion

The proposed AI Consent bill in the US represents a significant step towards enhancing consumer privacy rights and data protection in the context of AI development. Through its stringent prohibitions, transparent consent procedures, regulatory compliance measures, and robust enforcement mechanisms, the bill strives to strike a balance between fostering innovation in AI technologies while safeguarding the privacy and autonomy of individuals.

References:

• https://fedscoop.com/consumer-data-consent-training-ai-models-senate-bill/#:~:text=%E2%80%9CThe%20AI%20CONSENT%20Act%20gives,Welch%20said%20in%20a%20statement
• https://www.dataguidance.com/news/usa-bill-ai-consent-act-introduced-house#:~:text=USA%3A%20Bill%20for%20the%20AI%20Consent%20Act%20introduced%20to%20House%20of%20Representatives,-ConsentPrivacy%20Law&text=On%20March%2019%2C%202024%2C%20US,the%20U.S.%20House%20of%20Representatives
• https://datenrecht.ch/en/usa-ai-consent-act-vorgeschlagen/
• https://www.lujan.senate.gov/newsroom/press-releases/lujan-welch-introduce-billto-require-online-platforms-receive-consumers-consent-before-using-their-personal-data-to-train-ai-models/

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