#FactCheck- Old Dubai Flood Videos Falsely Shared as Recent Storm Footage
Executive Summary
Amid reports of heavy rainfall and flooding in several cities of the United Arab Emirates, a video is being widely circulated on social media claiming to show recent scenes from Dubai. The clip allegedly depicts severe waterlogging at Dubai Airport and inside shopping malls, with users linking it to a “recent storm.”According to research by CyberPeace, the viral footage is not recent. The video is actually a compilation of three different clips stitched together and dates back to 2024, when Dubai experienced unprecedented flooding following heavy rains.
Claim
The misleading post was shared by an X (formerly Twitter) user named ‘Ruksar Khan’ on March 28, 2026, with a caption suggesting that Dubai had been submerged after just one day of rain. The post attempted to sensationalize the situation by portraying the visuals as current.
Fact Check:
To verify the claim, keyframes from the viral video were extracted using the InVid tool and analyzed through reverse image search. One of the clips was traced to a Facebook post by “9 News,” uploaded on April 17, 2024. The video showed waterlogged runways at Dubai International Airport following intense rainfall and flooding.
Further verification led to a report published by Hindustan Times on April 17, 2024, which featured similar visuals and confirmed that the footage was from the floods that hit Dubai in 2024.
Conclusion:
The viral claim suggesting that the video shows recent flooding in Dubai is false. The footage is nearly two years old and originates from the 2024 floods in Dubai. It is now being reshared with misleading claims to create confusion around current weather events.
Related Blogs
Executive Summary
A video circulating on social media shows a lion carrying away a woman who was washing clothes near a pond. Users are sharing the clip claiming it depicts a real incident. However, research by CyberPeace found the viral claim to be false. The research revealed that the video is not real but AI-generated.
Claim
A user on Facebook shared the viral video claiming that a lion attacked and carried away a woman from a pond while she was washing clothes. The link to the post and its archived version are provided below
Fact Check:
Upon closely examining the viral clip, we noticed several visual inconsistencies that raised suspicion about its authenticity. The video was then analyzed using the AI-detection tool Sightengine. According to the analysis results, the viral video was identified as AI-generated.
Conclusion
The research confirms that the viral video does not depict a real incident. The clip is digitally created using artificial intelligence and is being falsely shared as a genuine event.
There has been a struggle to create legal frameworks that can define where free speech ends and harmful misinformation begins, specifically in democratic societies where the right to free expression is a fundamental value. Platforms like YouTube, Wikipedia, and Facebook have gained a huge consumer base by focusing on hosting user-generated content. This content includes anything a visitor puts on a website or social media pages.
The legal and ethical landscape surrounding misinformation is dependent on creating a fine balance between freedom of speech and expression while protecting public interests, such as truthfulness and social stability. This blog is focused on examining the legal risks of misinformation, specifically user-generated content, and the accountability of platforms in moderating and addressing it.
The Rise of Misinformation and Platform Dynamics
Misinformation content is amplified by using algorithmic recommendations and social sharing mechanisms. The intent of spreading false information is closely interwoven with the assessment of user data to identify target groups necessary to place targeted political advertising. The disseminators of fake news have benefited from social networks to reach more people, and from the technology that enables faster distribution and can make it more difficult to distinguish fake from hard news.
Multiple challenges emerge that are unique to social media platforms regulating misinformation while balancing freedom of speech and expression and user engagement. The scale at which content is created and published, the different regulatory standards, and moderating misinformation without infringing on freedom of expression complicate moderation policies and practices.
The impacts of misinformation on social, political, and economic consequences, influencing public opinion, electoral outcomes, and market behaviours underscore the urgent need for effective regulation, as the consequences of inaction can be profound and far-reaching.
Legal Frameworks and Evolving Accountability Standards
Safe harbour principles allow for the functioning of a free, open and borderless internet. This principle is embodied under the US Communications Decency Act and the Information Technology Act in Sections 230 and 79 respectively. They play a pivotal role in facilitating the growth and development of the Internet. The legal framework governing misinformation around the world is still in nascent stages. Section 230 of the CDA protects platforms from legal liability relating to harmful content posted on their sites by third parties. It further allows platforms to police their sites for harmful content and protects them from liability if they choose not to.
By granting exemptions to intermediaries, these safe harbour provisions help nurture an online environment that fosters free speech and enables users to freely express themselves without arbitrary intrusions.
A shift in regulations has been observed in recent times. An example is the enactment of the Digital Services Act of 2022 in the European Union. The Act requires companies having at least 45 million monthly users to create systems to control the spread of misinformation, hate speech and terrorist propaganda, among other things. If not followed through, they risk penalties of up to 6% of the global annual revenue or even a ban in EU countries.
Challenges and Risks for Platforms
There are multiple challenges and risks faced by platforms that surround user-generated misinformation.
- Moderating user-generated misinformation is a big challenge, primarily because of the quantity of data in question and the speed at which it is generated. It further leads to legal liabilities, operational costs and reputational risks.
- Platforms can face potential backlash, both in instances of over-moderation or under-moderation. It can be considered as censorship, often overburdening. It can also be considered as insufficient governance in cases where the level of moderation is not protecting the privacy rights of users.
- Another challenge is more in the technical realm, including the limitations of AI and algorithmic moderation in detecting nuanced misinformation. It holds out to the need for human oversight to sift through the misinformation that is created by AI-generated content.
Policy Approaches: Tackling Misinformation through Accountability and Future Outlook
Regulatory approaches to misinformation each present distinct strengths and weaknesses. Government-led regulation establishes clear standards but may risk censorship, while self-regulation offers flexibility yet often lacks accountability. The Indian framework, including the IT Act and the Digital Personal Data Protection Act of 2023, aims to enhance data-sharing oversight and strengthen accountability. Establishing clear definitions of misinformation and fostering collaborative oversight involving government and independent bodies can balance platform autonomy with transparency. Additionally, promoting international collaborations and innovative AI moderation solutions is essential for effectively addressing misinformation, especially given its cross-border nature and the evolving expectations of users in today’s digital landscape.
Conclusion
A balance between protecting free speech and safeguarding public interest is needed to navigate the legal risks of user-generated misinformation poses. As digital platforms like YouTube, Facebook, and Wikipedia continue to host vast amounts of user content, accountability measures are essential to mitigate the harms of misinformation. Establishing clear definitions and collaborative oversight can enhance transparency and build public trust. Furthermore, embracing innovative moderation technologies and fostering international partnerships will be vital in addressing this cross-border challenge. As we advance, the commitment to creating a responsible digital environment must remain a priority to ensure the integrity of information in our increasingly interconnected world.
References
- https://www.thehindu.com/opinion/op-ed/should-digital-platform-owners-be-held-liable-for-user-generated-content/article68609693.ece
- https://www.thehindu.com/opinion/op-ed/should-digital-platform-owners-be-held-liable-for-user-generated-content/article68609693.ece
- https://hbr.org/2021/08/its-time-to-update-section-230
- https://www.cnbctv18.com/information-technology/deepfakes-digital-india-act-safe-harbour-protection-information-technology-act-sajan-poovayya-19255261.htm
When your digital identity becomes raw material for someone else’s imagination, who really owns your face?
On July 7, 2026, Meta launched Muse Image, the first standalone image-generation model developed by Meta Superintelligence Labs under Alexandr Wang. Positioned as a competitor to OpenAI’s GPT Images 2.0 and Google’s Nano Banana 2, the launch highlights Meta’s growing ambitions in the generative AI race. Yet beneath the technical advancements lies a far more consequential question than what AI can create, but about who gets to decide what it creates with?
That ambition of generative AI comes with a cost, and one of Muse Image's most controversial design choices is its integration with Instagram, which allows public profiles to become creative references for AI-generated images. Users can tag public Instagram accounts in prompts and generate AI images inspired by that person’s publicly available content. Meta presents this as a new form of personalization and creativity. However, critics argue that the feature transforms years of personal photographs into a massive library of AI-ready human identities, where non-action automatically becomes permission. The concern is not just that AI can generate realistic images. The concern is that consent itself is being manipulated in a way.
The opt-out system most users never asked for
Muse Image operates through Meta AI’s integration with Instagram. A user can reference a public Instagram profile in a prompt, allowing the system to generate images influenced by that person’s existing content and likeness. Under the default arrangement, the person whose profile is being referenced may not necessarily approve the generation beforehand.
Meta does provide users with controls to restrict this functionality. The setting exists under Instagram’s “Sharing and reuse” options, where users can disable permissions related to the use of their posts and reels with Meta’s AI features. But the larger issue is the direction in which responsibility flows. Instead of requiring active permission before someone’s likeness becomes available for AI-generated content, the burden is placed on individuals to discover the feature, understand the implications, locate the setting, and disable it. In a digital environment where users already navigate endless privacy menus, cookie banners, and terms of service agreements, expecting meaningful awareness from billions of people becomes unrealistic. Consent that depends on finding the exit door is very different from consent that begins with a choice.
A guide for opting-out
One way of opting out is to have a private account. As verified, Meta does not encroach on private accounts as of now for image-generation.
But if you have a public account, here are the steps that can be followed to secure yourself from Meta’s Muse automatic consent:
On your profile, tap the menu bar which is on the top right (≡), you will enter into ‘setting and activity’, after that you will see an option of ‘sharing and refuse’ and then disable the options under it, namely- Allow people to reuse your content on Instagram and with AI features at Meta. Notably, the changes made will be only for your future content not the already existing content on your public profile.
Why “public” does not mean “available for anything”
The debate around Muse Image highlights a deeper misunderstanding at the center of modern digital platforms: the difference between visibility and reuse. When someone makes an Instagram account public, they are generally making a decision about the audience. They are allowing others to view their photos, discover their profile, or engage with their content. That decision was never traditionally understood as permission for their face, appearance, personal moments, or identity markers to become reusable components in AI-generated media. A photograph posted online has context. It represents a specific moment, purpose, relationship, or expression. Generative AI changes that equation because it separates identity from context. A person’s likeness can be extracted from its original context and placed into entirely new situations created by someone else. Muse Image does not just expand who can see your content. It expands what can be done with it. That distinction is what scales the problem for every public user on the app. The privacy implications become significantly larger because of Instagram’s global reach. With billions of users worldwide, even a small percentage of affected public accounts represents an enormous number of people. Many public profiles do not belong to celebrities, influencers, or creators who intentionally operate as public brands. They belong to students, professionals, small businesses, artists, photographers, and everyday users who simply chose visibility within a social network.
For years, platforms encouraged people to share more, build audiences, and maintain a public digital presence. Now, the meaning of that public presence is changing after the fact. The question becomes: should a decision made years ago to share photos socially automatically extend into permission for generative AI systems built years later?
There is also a catch while opting out. Changing these settings only protects your content from being used in future AI generations, it does not undo anything that has already happened. Any AI images previously created using your public profile will remain unaffected. Essentially, the opt-out works as a shield for what comes next, not a reset button for what has already been created.
A familiar pattern in the AI era
Muse Image reflects a broader pattern emerging across the technology industry. New AI capabilities are introduced at massive scale, participation becomes the default, and individual control arrives afterward through settings that many users may never find. The same debates that once surrounded targeted advertising, data collection, and algorithmic profiling are now moving into a far more personal territory, the human identity itself. Faces are not ordinary data points. Unlike a username, password, or preference setting, a person cannot simply replace their appearance once it has been widely replicated.
Technical solutions such as AI watermarking and content labels may help identify generated material, but they address authenticity after creation. They do not answer the question of whether the generation should have happened in the first place.
Innovation cannot replace consent
The technological progress behind Muse Image is significant. Better image generation, improved text rendering, and more personalized creative tools represent genuine advances in artificial intelligence. But capability alone cannot determine acceptability. The future of AI will not only depend on how realistic images become, how powerful models become, or how quickly companies can deploy new features. It will also depend on whether people feel they have meaningful control over their own digital identities. Muse Image is therefore more than another AI product launch. It represents a defining question for the next phase of the internet: Will our online presence remain something we control, or will it become something others can generate?
