By Ankush Sabharwal, CEO & Founder, CoRover.ai
Protests occurring today typically commence in the streets, but they can rapidly gain traction through smartphones. Videos that show cops beating protesters, politicians making remarks, or mobs engaging in arson can be shared on social media within minutes. But what if these clips cannot be trusted? Since technology has made it easier to produce fake videos, audios, and images, deepfakes have become more and more prevalent, as they can now be used to spread misinformation throughout protests and public opinion.
When Seeing Is No Longer Believing
Deepfakes are produced by applying AI algorithms to create realistic video clips and sounds. It makes people look like they said something they did not, show events that actually never took place, and process real video clips in order to change their meaning. The emergence of this content is especially dangerous during protests, as the atmosphere is charged with emotions and information keeps flowing.
For example, fake videos of politicians offending a community or computer-generated videos of police brutality can cause outrage before journalists and law enforcement agencies are able to check the information. The threat goes beyond the use of false content. Real videos or images can be used out of context, which will lead to the distortion of the real meaning of the content.
The Impact of AI on Misinformation during Protests
The advent of generative AI has made it considerably easier for people to create deepfake content. Unlike in the past when producing deepfakes required specific knowledge and skills, now, almost anyone with an internet connection can create such content. Deepfakes can be disseminated in multiple ways, including social media, instant messaging apps, and short video platforms. Content that evokes strong emotional reactions is more likely to be shared quickly, and people may do so before double-checking its veracity. At the same time, the use of fake accounts to promote those narratives might create the impression that the people are supporting the claims.
What is alarming is that the speed of dissemination might create problems during protests, as people will be updating each other in real time, understanding where to go, how to react, and whether the place is safe or not. If a piece of information about violence appears to be fake, it may cause people to panic or direct them to unsafe places. Nonetheless, not every misleading post is part of an organized disinformation effort. Some people do not realize they are spreading deepfakes because the content looks trustworthy or supports their beliefs. This makes solving the problem of misinformation more complicated than merely moderating online content.
Consequences in Real Life of Misinformation
The effects of changing the truth in terms of protests are felt beyond the virtual space. False statements can not only ruin reputations but also stir up conflicts in society, make people lose trust in institutions, and hamper safety efforts. They have the ability to obstruct advancements in legitimate journalism. If footage of violence comes to light, those looking to deny its validity may classify it as a deepfake. The result is a situation where fake evidence is mistaken for the truth while credible evidence is disregarded as fake.
The Real-World Consequences of Digital Deception
For journalists, this presents a tough job because newsrooms find themselves in a battle between the need to cover breaking news and the need to authenticate visual evidence. If they publish a video they have not verified, they could create a false narrative. On the other hand, rejecting legitimate footage without proper verification can inhibit the damage. One of the ways to deal with this situation is to make sure technology companies, government institutions, news organisations, and citizens work together towards that end. Tech giants should implement better fake media detection technologies, mark verified synthetic content where applicable, and react quickly to misinformation. Governments need to support transparency and accountability but without misusing misinformation concerns to punish legitimate dissent and peaceful protest.
News organisations should check the source of the footage, investigate its metadata where possible, compare it to independent reports, and find corroboration with reliable witnesses. AI detection tools can assist in this process, but should not be considered conclusive proof since detection systems can yield false positives and false negatives. A Composite AI approach, combining AI-based detection methods with independent evidence and human judgment, can support more reliable verification than relying on a single automated system.
Responsible AI requires transparency, accountability, and appropriate human oversight to ensure that automated detection supports informed decisions rather than becoming the sole basis for judging the authenticity of digital content.
Citizens also have an important role to play. Before forwarding a dramatic video, it is the duty of users to check the source, production date, location, and reports.
Responsible Deepfakes: Using AI for Inclusion and Wider Reach
While deepfakes pose significant risks when used to spread misinformation, synthetic media can also serve a constructive purpose when created with the right intent, transparency, and informed consent. When deployed responsibly, this technology can help communicate verified information in a more engaging, accessible, and human-centric manner, reaching wider and more diverse audiences across languages and digital platforms.
These AI-powered solutions can make authentic, authorised information more accessible, particularly for people who face language, literacy, or accessibility barriers. From delivering public service information to enabling interactive communication, such applications demonstrate how synthetic media can contribute to greater inclusivity and wider access to reliable information.
The distinction lies in how the technology is developed and deployed. Consent, transparency, clear disclosure where appropriate, and accountability are essential to ensuring that synthetic media informs rather than deceives. When guided by these principles, deepfake and digital-twin technologies can move beyond the risks of manipulation to become meaningful tools for responsible communication, public awareness, and inclusive digital experiences.
Safeguarding the Reality Underlying the Protests
Deepfake technology is not merely a technical problem; it also poses a significant risk to the informational environment of democratic engagement. Participating in demonstrations requires people to comprehend what is happening, to challenge those in power and to form their opinions on the basis of accurate information. Artificial intelligence is responsible for the proliferation of disinformation faster and more convincingly than before, although how effective its influence will be still depends on the responses of audiences, platforms and members of the political sphere.
The solution is not to mistrust all images and videos; rather, it is necessary to enforce more rigorous verification habits and hold accountable those distributing information. A human-centric AI approach must prioritise people’s safety, access to reliable information, and ability to make informed decisions, particularly when digital misinformation can influence real-world actions. When digital deception is capable of affecting people’s actions on the streets, safeguarding the truth is a matter of public safety and trust.