Joshua Lukose
Date: 3/7/2026
Soon, the most viral video on TikTok might not even be real. That’s the reality with deepfakes, where AI can generate realistic media that looks exactly like real people, but they are doing and saying things that never happened. With tools becoming increasingly powerful and accessible, deepfakes aren’t just a Hollywood niche anymore, they’re something that anyone can make on their phone. This raises an important question: are deepfakes a breakthrough, or the end of trust in media as we know it? Deepfakes can be used for entertainment and art, but they also create huge risks for misinformation and abuse.
Deepfakes operate by training an AI model on images, videos, and audio of someone, and then generating content that matches this data. Someone could take a celebrity’s voice, feed it into one such model, and make it “say” a fake statement; one could create a video of a politician “announcing” something that never even happened. And the scariest part about this is that some of these clips are so realistic that someone who isn’t actively trying to find a deepfake wouldn’t notice anything wrong. As the technology gets more refined, identifying deepfakes by “looking closely” becomes less and less reliable.
There are benefits to the technology, though. Deepfake-style tools can be utilized in filmmaking to reduce costs and increase operational efficiency. Movies can use such technology to de-age actors, avoid reshoots, or translate content while still matching lip movement. Deepfakes can also be used for education; historical documentaries could recreate figures for learning (as long as it’s made clear that it was a deepfake), and voice cloning could help those who lost their ability to speak. Also, like many tools, it can be used creatively, such as parody, satire, and art.
But the concerns potentially outweigh the benefits. The most pressing issue is misinformation: if anyone can make a realistic deepfake, then it becomes child’s play to spread false stories quickly, especially during major events. Another problem is harassment, as people can use deepfakes to put someone’s face into content they never agreed to, ruining reputations and causing real-life harm. Even if a video is proven to be a deepfake later on, the damage might already be done. If deepfakes become too common, people may stop trusting real videos too, so someone caught doing something wrong can just say “it’s AI” and the reality becomes debatable.
Deepfakes aren’t a tech trend; they’re a compliance issue, and the challenge at hand is building systems that handle them responsibly. This could mean watermarking AI media, like what’s done with Sora AI, developing better detection tools, or even policymaking that punishes misuse. Deepfakes can certainly be used for good, but if accountability is not pushed, then they can make the internet an untrustworthy place, where nothing is believable anymore. As the lines between reality and AI blur, it is important to choose what matters more.