#FactCheck-Mosque fire in India? False, it's from Indonesia

Introduction

Google India announced sachet loans on the Google Pay application to help small businesses in the country. Google India said that merchants in India often need smaller loans, hence, the tech giant launched sachet loans on the Gpay application. The company will provide loans to small businesses, which can be repaid in easier repayment instalments. To provide the load services, Google Pay has partnered with DMI Finance. This move comes at the Google for India, 2023, the flagship event to launch the Indian interventions planned by the big tech. 

What is a Sachet Loan? 

The loan system is the primary backbone of the global banking system. Since we have seen a massive transition towards the digital mode of transactions and banking operations, many online platforms have emerged. With the advent of QR codes, the Unified Payment Interface (UPI) has been rampantly used by Indians for making small or petty payments. Seeing this, Sachet loans made an advent as well, Sachet loans are essentially small-ticket loans ranging from Rs 10,000 to Rs 1 lakh, with repayment tenures between 7 days and 12 months. This nano-credit addresses immediate financial needs and is designed for swift approval and disbursement. Satchel loans are one of the most sought-after loan forms in the Western world. The ease of accessibility and easy repayment options have made it a successful form of money lending, which in turn has sparked the interest of the tech giant Google to execute similar operations in India. 

Google Pay

Pertaining to the fact that UPI payments are the most preferred form of online payment, google came out with GPay in 2013 and now enjoys a user base of 67 million Indians. Google Pay has a 36.10% mobile application market share in India, and 26% of the UPI payments made have been through Google Pay. Google Pay adoption for in-store payments in India was higher in 2023 than it was in early 2019, signalling a growing use among consumers. The numbers shown here refer to the share of respondents who indicated they used Google Pay in the last 12 months, either for POS transactions with a mobile device in stores and restaurants or for online shopping. Eight out of 10 respondents from India indicated they had used Google Pay in a POS setting between April 2022 and March 2023, with an additional seven out of 10 saying they used Google Pay during this same time for online payments.

Pertaining to the Indian spectrum, the following aspects should be kept into consideration: 

• PhonePe, Google Pay and Paytm accounted for nearly 96% of all UPI transactions by value in March
• PhonePe remained the top UPI app, processing 407.63 Cr transactions worth INR 7.07 Lakh Cr
• While Google Pay and Paytm retained second and third positions, respectively, Amazon Pay pushed CRED to the fifth spot in terms of the number of transactions
• Walmart-owned PhonePe, Google Pay and Paytm continued their dominance in India’s UPI payments space, together processing 94% of payments in March 2023.
• According to data from the National Payments Corporation of India (NPCI), the top three apps accounted for nearly 96% of all UPI transactions by value. This translates to about 841.91 Cr transactions worth INR 13.44 Lakh Cr between the three apps.

Conclusion

The big tech giant Google.org has been fundamental in creating and provisioning best-in-class services which are easily accessible to all the netizens. Satchel loans are the new services introduced by the platform and the widespread access of Gpay will go a long way in providing financial services and ease to the deprived and needy lot of the Indian population. This transition can also be seen by other payment portals like Paypal and Paytm, which clearly shows India's massive potential in leading the world of online banking and UPI transactions. As per stats, 40% of global online banking transactions take place in India. These aspects, coupled with the cores of Digital India and Make in India, clearly show how India is the global destination for investment in the current era.  

References

• https://www.livemint.com/companies/news/google-enters-retail-loan-business-in-india-11697697999246.html
• https://www.statista.com/statistics/1389649/google-pay-adoption-in-india/#:~:text=Eight%20out%20of%2010%20respondents,same%20time%20for%20online%20payments
• https://playtoday.co/blog/stats/google-pay-statistics/#:~:text=67%20million%20active%20users%20of%20Google%20Pay%20are%20in%20India.&text=Google%20Pay%20users%20in%20India,in%2Dstore%20and%20online%20purchases.
• https://inc42.com/buzz/phonepe-google-pay-paytm-process-94-of-upi-transactions-march-2023/

‍

‍

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/

‍

Introduction

The increasing online interaction and popularity of social media platforms for netizens have made a breeding ground for misinformation generation and spread. Misinformation propagation has become easier and faster on online social media platforms, unlike traditional news media sources like newspapers or TV. The big data analytics and Artificial Intelligence (AI) systems have made it possible to gather, combine, analyse and indefinitely store massive volumes of data. The constant surveillance of digital platforms can help detect and promptly respond to false and misinformation content. 

During the recent Israel-Hamas conflict, there was a lot of misinformation spread on big platforms like X (formerly Twitter) and Telegram. Images and videos were falsely shared attributing to the ongoing conflict, and had spread widespread confusion and tension. While advanced technologies such as AI and big data analytics can help flag harmful content quickly, they must be carefully balanced against privacy concerns to ensure that surveillance practices do not infringe upon individual privacy rights. Ultimately, the challenge lies in creating a system that upholds both public security and personal privacy, fostering trust without compromising on either front.

The Need for Real-Time Misinformation Surveillance

According to a recent survey from the Pew Research Center, 54% of U.S. adults at least sometimes get news on social media. The top spots are taken by Facebook and YouTube respectively with Instagram trailing in as third and TikTok and X as fourth and fifth. Social media platforms provide users with instant connectivity allowing them to share information quickly with other users without requiring the permission of a gatekeeper such as an editor as in the case of traditional media channels. 

Keeping in mind the data dumps that generated misinformation due to the elections that took place in 2024 (more than 100 countries), the public health crisis of COVID-19, the conflicts in the West Bank and Gaza Strip and the sheer volume of information, both true and false, has been immense. Identifying accurate information amid real-time misinformation is challenging. The dilemma emerges as the traditional content moderation techniques may not be sufficient in curbing it. Traditional content moderation alone may be insufficient, hence the call for a dedicated, real-time misinformation surveillance system backed by AI and with certain human sight and also balancing the privacy of user's data, can be proven to be a good mechanism to counter misinformation on much larger platforms. The concerns regarding data privacy need to be prioritized before deploying such technologies on platforms with larger user bases. 

Ethical Concerns Surrounding Surveillance in Misinformation Control

Real-time misinformation surveillance could pose significant ethical risks and privacy risks. Monitoring communication patterns and metadata, or even inspecting private messages, can infringe upon user privacy and restrict their freedom of expression. Furthermore, defining misinformation remains a challenge; overly restrictive surveillance can unintentionally stifle legitimate dissent and alternate perspectives. Beyond these concerns, real-time surveillance mechanisms could be exploited for political, economic, or social objectives unrelated to misinformation control. Establishing clear ethical standards and limitations is essential to ensure that surveillance supports public safety without compromising individual rights. 

In light of these ethical challenges, developing a responsible framework for real-time surveillance is essential.

Balancing Ethics and Efficacy in Real-Time Surveillance: Key Policy Implications

Despite these ethical challenges, a reliable misinformation surveillance system is essential. Key considerations for creating ethical, real-time surveillance may include:

• Misinformation-detection algorithms should be designed with transparency and accountability in mind. Third-party audits and explainable AI can help ensure fairness, avoid biases, and foster trust in monitoring systems.
• Establishing clear, consistent definitions of misinformation is crucial for fair enforcement. These guidelines should carefully differentiate harmful misinformation from protected free speech to respect users’ rights.
• Only collecting necessary data and adopting a consent-based approach which protects user privacy and enhances transparency and trust. It further protects them from stifling dissent and profiling for targeted ads.
• An independent oversight body that can monitor surveillance activities while ensuring accountability and preventing misuse or overreach can be created. These measures, such as the ability to appeal to wrongful content flagging, can increase user confidence in the system.

Conclusion: Striking a Balance

Real-time misinformation surveillance has shown its usefulness in counteracting the rapid spread of false information online. But, it brings complex ethical challenges that cannot be overlooked such as balancing the need for public safety with the preservation of privacy and free expression is essential to maintaining a democratic digital landscape. The references from the EU’s Digital Services Act and Singapore’s POFMA underscore that, while regulation can enhance accountability and transparency, it also risks overreach if not carefully structured. Moving forward, a framework for misinformation monitoring must prioritise transparency, accountability, and user rights, ensuring that algorithms are fair, oversight is independent, and user data is protected. By embedding these safeguards, we can create a system that addresses the threat of misinformation and upholds the foundational values of an open, responsible, and ethical online ecosystem. Balancing ethics and privacy and policy-driven AI Solutions for Real-Time Misinformation Monitoring are the need of the hour.

References

• https://www.pewresearch.org/journalism/fact-sheet/social-media-and-news-fact-sheet/ 
• https://eur-lex.europa.eu/legal-content/EN/TXT/HTML/?uri=OJ:C:2018:233:FULL 

‍