#FactCheck - Viral Video Misleadingly Tied to Recent Taiwan Earthquake
Executive Summary:
In the context of the recent earthquake in Taiwan, a video has gone viral and is being spread on social media claiming that the video was taken during the recent earthquake that occurred in Taiwan. However, fact checking reveals it to be an old video. The video is from September 2022, when Taiwan had another earthquake of magnitude 7.2. It is clear that the reversed image search and comparison with old videos has established the fact that the viral video is from the 2022 earthquake and not the recent 2024-event. Several news outlets had covered the 2022 incident, mentioning additional confirmation of the video's origin.
Claims:
There is a news circulating on social media about the earthquake in Taiwan and Japan recently. There is a post on “X” stating that,
“BREAKING NEWS :
Horrific #earthquake of 7.4 magnitude hit #Taiwan and #Japan. There is an alert that #Tsunami might hit them soon”.
Similar Posts:
Fact Check:
We started our investigation by watching the videos thoroughly. We divided the video into frames. Subsequently, we performed reverse search on the images and it took us to an X (formally Twitter) post where a user posted the same viral video on Sept 18, 2022. Worth to notice, the post has the caption-
“#Tsunami warnings issued after Taiwan quake. #Taiwan #Earthquake #TaiwanEarthquake”
The same viral video was posted on several news media in September 2022.
The viral video was also shared on September 18, 2022 on NDTV News channel as shown below.
Conclusion:
To conclude, the viral video that claims to depict the 2024 Taiwan earthquake was from September 2022. In the course of the rigorous inspection of the old proof and the new evidence, it has become clear that the video does not refer to the recent earthquake that took place as stated. Hence, the recent viral video is misleading . It is important to validate the information before sharing it on social media to prevent the spread of misinformation.
Claim: Video circulating on social media captures the recent 2024 earthquake in Taiwan.
Claimed on: X, Facebook, YouTube
Fact Check: Fake & Misleading, the video actually refers to an incident from 2022.
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Introduction
The Indian Cabinet has approved a comprehensive national-level IndiaAI Mission with a budget outlay ofRs.10,371.92 crore. The mission aims to strengthen the Indian AI innovation ecosystem by democratizing computing access, improving data quality, developing indigenous AI capabilities, attracting top AI talent, enabling industry collaboration, providing startup risk capital, ensuring socially-impactful A projects, and bolstering ethical AI. The mission will be implemented by the'IndiaAI' Independent Business Division (IBD) under the Digital India Corporation (DIC) and consists of several components such as IndiaAI Compute Capacity, IndiaAI Innovation Centre (IAIC), IndiaAI Datasets Platform, India AI Application Development Initiative, IndiaAI Future Skills, IndiaAI Startup Financing, and Safe & Trusted AI over the next 5 years.
This financial outlay is intended to befulfilled through a public-private partnership model, to ensure a structured implementation of the IndiaAI Mission. The main objective is to create and nurture an ecosystem for India’s AI innovation. This mission is intended to act as a catalyst for shaping the future of AI for India and the world. AI has the potential to become an active enabler of the digital economy and the Indian government aims to harness its full potential to benefit its citizens and drive the growth of its economy.
Key Objectives of India's AI Mission
● With the advancements in data collection, processing and computational power, intelligent systems can be deployed in varied tasks and decision-making to enable better connectivity and enhance productivity.
● India’s AI Mission will concentrate on benefiting India and addressing societal needs in primary areas of healthcare, education, agriculture, smart cities and infrastructure, including smart mobility and transportation.
● This mission will work with extensive academia-industry interactions to ensure the development of core research capability at the national level. This initiative will involve international collaborations and efforts to advance technological frontiers by generating new knowledge and developing and implementing innovative applications.
The strategies developed for implementing the IndiaAI Mission are via Public-Private Partnerships, Skilling initiatives and AI Policy and Regulation. An example of the work towards the public-private partnership is the pre-bid meeting that the IT Ministry hosted on 29th August2024, which saw industrial participation from Nvidia, Intel, AMD, Qualcomm, Microsoft Azure, AWS, Google Cloud and Palo Alto Networks.
Components of IndiaAI Mission
The IndiaAI Compute Capacity: The IndiaAI Compute pillar will build a high-end scalable AI computing ecosystem to cater to India's rapidly expanding AI start-ups and research ecosystem. The ecosystem will comprise AI compute infrastructure of 10,000 or more GPUs, built through public-private partnerships. An AI marketplace will offer AI as a service and pre-trained models to AI innovators.
The IndiaAI Innovation Centre will undertake the development and deployment of indigenous Large Multimodal Models (LMMs) and domain-specific foundational models in critical sectors. The IndiaAI Datasets Platform will streamline access to quality on-personal datasets for AI innovation.
The IndiaAI Future Skills pillar will mitigate barriers to entry into AI programs and increase AI courses in undergraduate, master-level, and Ph.D. programs. Data and AI Labs will be set up in Tier 2 and Tier 3 cities across India to impart foundational-level courses.
The IndiaAI Startup Financing pillar will support and accelerate deep-tech AI startups, providing streamlined access to funding for futuristic AI projects.
The Safe & Trusted AI pillar will enable the implementation of responsible AI projects and the development of indigenous tools and frameworks, self-assessment check lists for innovators, and other guidelines and governance frameworks by recognising the need for adequate guardrails to advance the responsible development, deployment, and adoption of AI.
CyberPeace Considerations for the IndiaAI Mission
● Data privacy and security are paramount as emerging privacy instruments aim to ensure ethical AI use. Addressing bias and fairness in AI remains a significant challenge, especially with poor-quality or tampered datasets that can lead to flawed decision-making, posing risks to fairness, privacy, and security.
● Geopolitical tensions and export control regulations restrict access to cutting-edge AI technologies and critical hardware, delaying progress and impacting data security. In India, where multilingualism and regional diversity are key characteristics, the unavailability of large, clean, and labeled datasets in Indic languages hampers the development of fair and robust AI models suited to the local context.
● Infrastructure and accessibility pose additional hurdles in India’s AI development. The country faces challenges in building computing capacity, with delays in procuring essential hardware, such as GPUs like Nvidia’s A100 chip, hindering businesses, particularly smaller firms. AI development relies heavily on robust cloud computing infrastructure, which remains in its infancy in India. While initiatives like AIRAWAT signal progress, significant gaps persist in scaling AI infrastructure. Furthermore, the scarcity of skilled AI professionals is a pressing concern, alongside the high costs of implementing AI in industries like manufacturing. Finally, the growing computational demands of AI lead to increased energy consumption and environmental impact, raising concerns about balancing AI growth with sustainable practices.
Conclusion
We advocate for ethical and responsible AI development adoption to ensure ethical usage, safeguard privacy, and promote transparency. By setting clear guidelines and standards, the nation would be able to harness AI's potential while mitigating risks and fostering trust. The IndiaAI Mission will propel innovation, build domestic capacities, create highly-skilled employment opportunities, and demonstrate how transformative technology can be used for social good and enhance global competitiveness.
References
● https://pib.gov.in/PressReleasePage.aspx?PRID=2012375
What are Deepfakes?
A deepfake is essentially a video of a person in which their face or body has been digitally altered so that they appear to be someone else, typically used maliciously or to spread false information. Deepfake technology is a method for manipulating videos, images, and audio utilising powerful computers and deep learning. It is used to generate fake news and commit financial fraud, among other wrongdoings. It overlays a digital composite over an already-existing video, picture, or audio; cybercriminals use Artificial Intelligence technology. The term deepfake was coined first time in 2017 by an anonymous Reddit user, who called himself deepfake.
Deepfakes works on a combination of AI and ML, which makes the technology hard to detect by Web 2.0 applications, and it is almost impossible for a layman to see if an image or video is fake or has been created using deepfakes. In recent times, we have seen a wave of AI-driven tools which have impacted all industries and professions across the globe. Deepfakes are often created to spread misinformation. There lies a key difference between image morphing and deepfakes. Image morphing is primarily used for evading facial recognition, but deepfakes are created to spread misinformation and propaganda.
Issues Pertaining to Deepfakes in India
Deepfakes are a threat to any nation as the impact can be divesting in terms of monetary losses, social and cultural unrest, and actions against the sovereignty of India by anti-national elements. Deepfake detection is difficult but not impossible. The following threats/issues are seen to be originating out of deep fakes:
- Misinformation: One of the biggest issues of Deepfake is misinformation, the same was seen during the Russia-Ukraine conflict, where in a deepfake of Ukraine’s president, Mr Zelensky, surfaced on the internet and caused mass confusion and propaganda-based misappropriation among the Ukrainians.
- Instigation against the Union of India: Deepfake poses a massive threat to the integrity of the Union of India, as this is one of the easiest ways for anti-national elements to propagate violence or instigate people against the nation and its interests. As India grows, so do the possibilities of anti-national attacks against the nation.
- Cyberbullying/ Harassment: Deepfakes can be used by bad actors to harass and bully people online in order to extort money from them.
- Exposure to Illicit Content: Deepfakes can be easily used to create illicit content, and oftentimes, it is seen that it is being circulated on online gaming platforms where children engage the most.
- Threat to Digital Privacy: Deepfakes are created by using existing videos. Hence, bad actors often use photos and videos from Social media accounts to create deepfakes, this directly poses a threat to the digital privacy of a netizen.
- Lack of Grievance Redressal Mechanism: In the contemporary world, the majority of nations lack a concrete policy to address the aspects of deepfake. Hence, it is of paramount importance to establish legal and industry-based grievance redressal mechanisms for the victims.
- Lack of Digital Literacy: Despite of high internet and technology penetration rates in India, digital literacy lags behind, this is a massive concern for the Indian netizens as it takes them far from understanding the tech, which results in the under-reporting of crimes. Large-scale awareness and sensitisation campaigns need to be undertaken in India to address misinformation and the influence of deepfakes.
How to spot deepfakes?
Deepfakes look like the original video at first look, but as we progress into the digital world, it is pertinent to establish identifying deepfakes in our digital routine and netiquettes in order to stay protected in the future and to address this issue before it is too late. The following aspects can be kept in mind while differentiating between a real video and a deepfake
- Look for facial expressions and irregularities: Whenever differentiating between an original video and deepfake, always look for changes in facial expressions and irregularities, it can be seen that the facial expressions, such as eye movement and a temporary twitch on the face, are all signs of a video being a deepfake.
- Listen to the audio: The audio in deepfake also has variations as it is imposed on an existing video, so keep a check on the sound effects coming from a video in congruence with the actions or gestures in the video.
- Pay attention to the background: The most easiest way to spot a deepfake is to pay attention to the background, in all deepfakes, you can spot irregularities in the background as, in most cases, its created using virtual effects so that all deepfakes will have an element of artificialness in the background.
- Context and Content: Most of the instances of deepfake have been focused towards creating or spreading misinformation hence, the context and content of any video is an integral part of differentiating between an original video and deepfake.
- Fact-Checking: As a basic cyber safety and digital hygiene protocol, one should always make sure to fact-check each and every piece of information they come across on social media. As a preventive measure, always make sure to fact-check any information or post sharing it with your known ones.
- AI Tools: When in doubt, check it out, and never refrain from using Deepfake detection tools like- Sentinel, Intel’s real-time deepfake detector - Fake catcher, We Verify, and Microsoft’s Video Authenticator tool to analyze the videos and combating technology with technology.
Recent Instance
A deepfake video of actress Rashmika Mandanna recently went viral on social media, creating quite a stir. The video showed a woman entering an elevator who looked remarkably like Mandanna. However, it was later revealed that the woman in the video was not Mandanna, but rather, her face was superimposed using AI tools. Some social media users were deceived into believing that the woman was indeed Mandanna, while others identified it as an AI-generated deepfake. The original video was actually of a British-Indian girl named Zara Patel, who has a substantial following on Instagram. This incident sparked criticism from social media users towards those who created and shared the video merely for views, and there were calls for strict action against the uploaders. The rapid changes in the digital world pose a threat to personal privacy; hence, caution is advised when sharing personal items on social media.
Legal Remedies
Although Deepfake is not recognised by law in India, it is indirectly addressed by Sec. 66 E of the IT Act, which makes it illegal to capture, publish, or transmit someone's image in the media without that person's consent, thus violating their privacy. The maximum penalty for this violation is ₹2 lakh in fines or three years in prison. The DPDP Act's applicability in 2023 means that the creation of deepfakes will directly affect an individual's right to digital privacy and will also violate the IT guidelines under the Intermediary Guidelines, as platforms will be required to exercise caution while disseminating and publishing misinformation through deepfakes. The indirect provisions of the Indian Penal Code, which cover the sale and dissemination of derogatory publications, songs and actions, deception in the delivery of property, cheating and dishonestly influencing the delivery of property, and forgery with the intent to defame, are the only legal remedies available for deepfakes. Deep fakes must be recognized legally due to the growing power of misinformation. The Data Protection Board and the soon-to-be-established fact-checking body must recognize crimes related to deepfakes and provide an efficient system for filing complaints.
Conclusion
Deepfake is an aftermath of the advancements of Web 3.0 and, hence is just the tip of the iceberg in terms of the issues/threats from emerging technologies. It is pertinent to upskill and educate the netizens about the keen aspects of deepfakes to stay safe in the future. At the same time, developing and developed nations need to create policies and laws to efficiently regulate deepfake and to set up redressal mechanisms for victims and industry. As we move ahead, it is pertinent to address the threats originating out of the emerging techs and, at the same time, create a robust resilience for the same.
References
Introduction
Advanced deepfake technology blurs the line between authentic and fake. To ascertain the credibility of the content it has become important to differentiate between genuine and manipulated or curated online content highly shared on social media platforms. AI-generated fake voice clone, videos are proliferating on the Internet and social media. There is the use of sophisticated AI algorithms that help manipulate or generate synthetic multimedia content such as audio, video and images. As a result, it has become increasingly difficult to differentiate between genuine, altered, or fake multimedia content. McAfee Corp., a well-known or popular global leader in online protection, has recently launched an AI-powered deepfake audio detection technology under Project “Mockingbird” intending to safeguard consumers against the surging threat of fabricated or AI-generated audio or voice clones to dupe people for money or unauthorisly obtaining their personal information. McAfee Corp. announced its AI-powered deepfake audio detection technology, known as Project Mockingbird, at the Consumer Electronics Show, 2024.
What is voice cloning?
To create a voice clone of anyone's, audio can be deeplyfaked, too, which closely resembles a real voice but, in actuality, is a fake voice created through deepfake technology.
Emerging Threats: Cybercriminal Exploitation of Artificial Intelligence in Identity Fraud, Voice Cloning, and Hacking Acceleration
AI is used for all kinds of things from smart tech to robotics and gaming. Cybercriminals are misusing artificial intelligence for rather nefarious reasons including voice cloning to commit cyber fraud activities. Artificial intelligence can be used to manipulate the lips of an individual so it looks like they're saying something different, it could also be used for identity fraud to make it possible to impersonate someone for a remote verification for your bank and it also makes traditional hacking more convenient. Cybercriminals have been misusing advanced technologies such as artificial intelligence, which has led to an increase in the speed and volume of cyber attacks, and that's been the theme in recent times.
Technical Analysis
To combat Audio cloning fraudulent activities, McAfee Labs has developed a robust AI model that precisely detects artificially generated audio used in videos or otherwise.
- Context-Based Recognition: Contextual assessment is used by technological devices to examine audio components in the overall setting of an audio. It improves the model's capacity to recognise discrepancies suggestive of artificial intelligence-generated audio by evaluating its surroundings information.
- Conductual Examination: Psychological detection techniques examine linguistic habits and subtleties, concentrating on departures from typical individual behaviour. Examining speech patterns, tempo, and pronunciation enables the model to identify artificially or synthetically produced material.
- Classification Models: Auditory components are categorised by categorisation algorithms for detection according to established traits of human communication. The technology differentiates between real and artificial intelligence-synthesized voices by comparing them against an extensive library of legitimate human speech features.
- Accuracy Outcomes: McAfee Labs' deepfake voice recognition solution, which boasts an impressive ninety per cent success rate, is based on a combined approach incorporating psychological, context-specific, and categorised identification models. Through examining audio components in the larger video context and examining speech characteristics, such as intonation, rhythm, and pronunciation, the system can identify discrepancies that could be signs of artificial intelligence-produced audio. Categorical models make an additional contribution by classifying audio information according to characteristics of known human speech. This all-encompassing strategy is essential for precisely recognising and reducing the risks connected to AI-generated audio data, offering a strong barrier against the growing danger of deepfake situations.
- Application Instances: The technique protects against various harmful programs, such as celebrity voice-cloning fraud and misleading content about important subjects.
Conclusion
It is important to foster ethical and responsible consumption of technology. Awareness of common uses of artificial intelligence is a first step toward broader public engagement with debates about the appropriate role and boundaries for AI. Project Mockingbird by Macafee employs AI-driven deepfake audio detection to safeguard against cyber criminals who are using fabricated AI-generated audio for scams and manipulating the public image of notable figures, protecting consumers from financial and personal information risks.
References:
- https://www.cnbctv18.com/technology/mcafee-deepfake-audio-detection-technology-against-rise-in-ai-generated-misinformation-18740471.htm
- https://www.thehindubusinessline.com/info-tech/mcafee-unveils-advanced-deepfake-audio-detection-technology/article67718951.ece
- https://lifestyle.livemint.com/smart-living/innovation/ces-2024-mcafee-ai-technology-audio-project-mockingbird-111704714835601.html
- https://news.abplive.com/fact-check/audio-deepfakes-adding-to-cacophony-of-online-misinformation-abpp-1654724
