The increase in consumer demands has resulted in a sharp increase in digital financing in India. As a result, the reputation of the digital lending sector has been impacted, as bad actors increasingly deploy illicit lending platforms such as fraudulent loans and trading apps. As millions of Indians download fast loan applications to help them meet their financial ends, the fraudulent apps result in cyber crimes including financial fraud. Consumers need to be vigilant of dubious trading or loan applications as bad actors frequently use illegitimate apps to trick victims by advertising limited-period offers and applying pressure.
Recently the Indian Cyber Crime Coordination Centre (I4C) led handel CyberDost has issued a cybercrime alert against the ‘CashExpand-U’ finance assistant app, which has been now removed from the Google Play Store. The app was found to be associated with hostile foreign entities, and the app had made it easier to raise small loans. However, such loan apps are seldom credible and may compromise financial information.
Raising cases of Fraudulent Loan Apps
The finance minister had stated that the government is constantly engaged with the Reserve Bank of India and other regulators and stakeholders to control fraudulent loan apps. In FY23, there were 1,062 complaints against such apps, the Finance Minister shared during a Lok Sabha session. Google removed almost 134 fake apps from the Play Store in a single week in September 2023 after multiple complaints were registered against such apps. The Reserve Bank of India (RBI) had also issued regulatory guidelines on digital lending in April 2023 to bring transparency in the digital loan space.
CyberPeace Policy Wing Advisory for Users
Be cautious of App Permissions
Fake lending apps collect data by fraudulently taking numerous app permissions from consumers and misusing them later. The users must effectively manage their app permissions to avoid denying any extra permissions such as access to contacts, location, and photos. This is because fraudulent digital lenders access users' personal data to extort additional money even after loan repayment.
Practice Due Diligence
Consumers must exercise care & caution before applying for a loan from digital lending platforms. Before applying for a loan or downloading any such apps, consumers must conduct due diligence by verifying the app's name, rating, reviews, physical address, and contact information. Always double-verify the paperwork before signing any agreement or contract. Always apply for loans from RBI-approved and compliant banking and financial services providers.
Download from Official Sources
To avoid downloading counterfeit apps, only download lending apps from official stores like Google Play Store or Apple App Store, and avoid downloading apps from web links sent via SMS, email, or social media, even if shared by your known persons.
Be sceptical of too-good-to-be-true offerings
Be cautious of deals that seem too good to be true, like hassle-free easy loans as they can be fraudulent. If an offer seems too good to be true, it might be a red flag. Hence always conduct your own research to verify the lender and avoid making hasty decisions.
Reporting Mechanism
In case of facing a scam by such fraudulent apps, victims can file a complaint with the ‘National Cyber Crime Reporting Portal’ or Cyber Crime Helpline ‘1930’, or they can also contact us at CyberPeace Helpline +919570000066 and helpline@cyberpeace.net to get assistance in reporting their cases.
Final Words
Illegitimate loan/trading apps have been raising concerns by defrauding innocent consumers who seek financial assistance. The Center has recently warned against the CashExpand-U app, which has been now removed from the Google Play Store. Users are advised to exercise due care and caution while downloading loan apps and applying for loans to prevent any potential scams. keep up to date with news from concerned authorities about common scams and fraudulent practices in the lending space and stay safe in the online world.
A video is being shared on social media showing a female cricket player seemingly making an impressive catch in the air after rotating 360 degrees. The video is being shared with claims that the player pulled off the extraordinary catch in an incredible feat on the cricket field. Research by CyberPeace found the viral claim to be false. Our research revealed that the viral video was edited with the help of AI. The video uses actual broadcast footage from the 2024 Women’s T20 World Cup match between India and New Zealand, but the 360-degree catch shown in the video was not part of the actual match.
Claim:
A video of a female cricketer making an incredible 360-degree catch is being shared on social media as a real incident from a cricket match.
To verify the authenticity of the viral claim, we conducted a Google search using relevant keywords. However, we did not find any credible media reports confirming the claim.
As part of the next step in our research, we conducted a reverse image search of the keyframes from the video. During the search, we found the same video on a YouTube channel, where it was identified as AI-generated.
As the next step, we scanned the viral video using the AI detection tool Hive Moderation. According to the tool’s results, there is a 70 percent probability that the video is AI-generated.
As part of the next step in our research, we scanned the viral video using an AI detection tool. According to the results, the viral video is AI-generated.
Conclusion
Our research found that the viral video was edited with the help of AI. The video uses actual broadcast footage from the 2024 Women’s T20 World Cup match between India and New Zealand. However, the 360-degree catch shown in the video was not part of the actual match.
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.
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.
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.
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.
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.
Artificial Intelligence (AI) provides a varied range of services and continues to catch intrigue and experimentation. It has altered how we create and consume content. Specific prompts can now be used to create desired images enhancing experiences of storytelling and even education. However, as this content can influence public perception, its potential to cause misinformation must be noted as well. The realistic nature of the images can make it hard to discern as artificially generated by the untrained eye. As AI operates by analysing the data it was trained on previously to deliver, the lack of contextual knowledge and human biases (while framing prompts) also come into play. The stakes are higher whilst dabbling with subjects such as history, as there is a fine line between the creation of content with the intent of mere entertainment and the spread of misinformation owing to biases and lack of veracity left unchecked. AI-generated images enhance storytelling but can also spread misinformation, especially in historical contexts. For instance, an AI-generated image of London during the Black Death might include inaccurate details, misleading viewers about the past.
The Rise of AI-Generated Historical Images as Entertainment
Recently, generated images and videos of various historical instances along with the point of view of the people present have been floating all over the internet. Some of them include the streets of London during the Black Death in the 1300s in England, the eruption of Mount Vesuvius at Pompeii etc. Hogne and Dan, two creators who operate accounts named POV Lab and Time Traveller POV on TikTok state that they create such videos as they feel that seeing the past through a first-person perspective is an interesting way to bring history back to life while highlighting the cool parts, helping the audience learn something new. Mostly sensationalised for visual impact and storytelling, such content has been called out by historians for inconsistencies with respect to details particular of the time. Presently, artists admit to their creations being inaccurate, reasoning them to be more of an artistic interpretation than fact-checked documentaries.
It is important to note that AI models may inaccurately depict objects (issues with lateral inversion), people(anatomical implausibilities), or scenes due to "present-ist" bias. As noted by Lauren Tilton, an associate professor of digital humanities at the University of Richmond, many AI models primarily rely on data from the last 15 years, making them prone to modern-day distortions especially when analysing and creating historical content. The idea is to spark interest rather than replace genuine historical facts while it is assumed that engagement with these images and videos is partly a product of the fascination with upcoming AI tools. Apart from this, there are also chatbots like Hello History and Charater.ai which enable simulations of interacting with historical figures that have piqued curiosity.
Although it makes for an interesting perspective, one cannot ignore that our inherent biases play a role in how we perceive the information presented. Dangerous consequences include feeding into conspiracy theories and the erasure of facts as information is geared particularly toward garnering attention and providing entertainment. Furthermore, exposure of such content to an impressionable audience with a lesser attention span increases the gravity of the matter. In such cases, information regarding the sources used for creation becomes an important factor.
Acknowledging the risks posed by AI-generated images and their susceptibility to create misinformation, the Government of Spain has taken a step in regulating the AI content created. It has passed a bill (for regulating AI-Generated content) that mandates the labelling of AI-generated images and failure to do so would warrant massive fines (up to $38 million or 7% of turnover on companies). The idea is to ensure that content creators label their content which would help to spot images that are artificially created from those that are not.
The Way Forward: Navigating AI and Misinformation
While AI-generated images make for exciting possibilities for storytelling and enabling intrigue, their potential to spread misinformation should not be overlooked. To address these challenges, certain measures should be encouraged.
Media Literacy and Awareness – In this day and age critical thinking and media literacy among consumers of content is imperative. Awareness, understanding, and access to tools that aid in detecting AI-generated content can prove to be helpful.
AI Transparency and Labeling – Implementing regulations similar to Spain’s bill on labelling content could be a guiding crutch for people who have yet to learn to tell apart AI-generated content from others.
Ethical AI Development – AI developers must prioritize ethical considerations in training using diverse and historically accurate datasets and sources which would minimise biases.
As AI continues to evolve, balancing innovation with responsibility is essential. By taking proactive measures in the early stages, we can harness AI's potential while safeguarding the integrity and trust of the sources while generating images.
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