Deepfake Apps: How They Work, Risks, and Spotting Fakes

If you have seen that viral video of Tom Cruise that looked so real but was totally fake then you must remember that was a deepfake. These doctored videos are getting crazy good thanks to new apps that use artificial intelligence to swap faces and voices. We know that it’s creepy and messed up. But as these apps spread, you gotta educate yourself so you don’t get fooled or taken advantage of. In this article, we’ll break down how deepfake software works its magic, the scary ways it can be abused, and tips to spot a phony video. Get ready for a deep dive into the wild world of deepfakes.

What Are Deepfake Apps and How Do They Work?

Deepfake apps use machine learning algorithms to manipulate or generate visual content like images, video, and audio. They analyze facial features, expressions and sounds from a source person and map them onto a target person. 

• Using tons of data and computing power, the apps learn how to seamlessly swap faces or voices to create synthetic media. Anyone with some technical know-how can download free deepfake tools and swap celebrities’ faces into explicit videos or manipulate political speeches.
• While the technology behind deepfakes is groundbreaking, these counterfeit creations undermine trust in media and can have serious consequences. They’re often used to spread misinformation or target individuals by putting their likeness into compromising situations.
• Spotting deepfakes requires a trained eye. Look for unnatural eye movements or sounds, weird shadows or reflections, or loss of details like teeth or hair. Of course, as the technology improves, detection may become nearly impossible.

Though regulation could help curb malicious deepfakes, limiting innovation is tricky. In the meantime, think critically about the media you consume and consider the motivations behind anything that seems too outrageous to be true. 

8 Best deepfake Apps in 2024

These are the most used 8 deepfake apps in 2024.

Zao

This popular Chinese app lets you swap faces in photos and videos. Just upload a photo of yourself and the app will replace your face with someone else’s in a matter of seconds. The results can be scarily realistic. While fun, this tech could easily be misused.

Avatarify

This open source tool allows you to animate any photo using deep learning. You can make photos smile, wink and move their head. The app is designed for fun filters and effects but some worry it could enable more malicious videos.

Wombo

This AI can generate synthetic videos of people talking or singing. Just type in some text and the AI will create a video of someone speaking or singing it. The results are far from perfect but the tech is advancing rapidly.

DeepFaceLab

DeepFaceLab is one of the most popular deepfake tools. It uses neural networks to swap faces in videos and photos. The app is free but requires a high-end GPU to run. If you’ve got the tech, it can produce shockingly realistic results.

FaceSwap

Another free, open-source tool, FaceSwap uses deep learning to swap faces in photos and videos. It works best if you provide multiple images of the faces you want to swap. The results won’t fool anyone up close but can be convincing from a distance.

Doublicat

Doublicat is a simple web app for creating deepfakes. Just upload photos of two people, and the AI will blend their faces together in a short video. The results are crude but a good way to see how deepfake tech works. Best of all, Doublicat runs in the browser, so you don’t need a powerful computer.

First Order Model (FOM)

FOM is an open-source tool for creating and detecting deepfakes. Unlike the other tools here, FOM focuses on video-to-video translation. Feed it clips of two people speaking, and it will swap their faces and lip movements. FOM requires significant tech skills to set up but produces high-quality deepfakes if you can get it working.

Reface

Reface is popular for swapping your face into GIFs and short clips. The app is free, easy to use, and creates pretty convincing results. You just upload a selfie, select a clip, and Reface handles the rest.

Apps like these demonstrate both the promise and perils of deepfake tech. While some are designed for entertainment, the possibility of misuse is real. As the tech behind deepfakes continues advancing, being able to spot fakes will only become more crucial. 

The Dangers and Risks of Using Deepfake Apps

You should be aware of Deepfake apps risks and dangers before using them.

Privacy and Data Concerns

Many deepfake apps access your personal photos to create the fakes. But what happens to your data after that? Your photos could be stored and used for other purposes without your consent. Some apps have been caught sharing or selling user data, so do your research on any app’s privacy policy before handing over your photos.

Potential for Misuse

Deepfakes can be used to spread misinformation or manipulate people. Your fake videos or photos could be taken out of context and shared as real. Criminals may also use deepfake technology for fraud, blackmail, or harassment.

Psychological Impact

Seeing a realistic fake of yourself in a compromising or manipulated situation could be psychologically disturbing. Deepfakes are getting harder and harder to detect, and could seriously damage someone’s reputation or sense of safety.

While deepfake apps are an amusing novelty, they also have a dark side with risks you should weigh before using one. Protect your privacy, personal data, and psychological well-being by avoiding questionable apps and being extremely judicious about what content you create and share. 

How to spot a deepfake photo or video?

Spotting deepfakes requires a keen eye. Look for subtle clues that reveal the media has been manipulated.

Lighting and Shadows

Check if the lighting and shadows in the photo or video seem natural and consistent. Deepfakes often have uneven, mismatched lighting and shadows that look slightly “off”. The subject may be too brightly lit compared to the surroundings, or shadows may fall in the wrong direction. 

Lighting and shadows can reveal inconsistencies in deepfakes. Since the fake face and the background are created separately, the lighting and shadows may not match perfectly. Look for:

• Shadows that don’t align with the lighting conditions in the scene
• Inconsistent shadows under the chin, around the nose, or under the eyes
• Highlights and shadows that don’t match the face contours or angle of the light source
• Shadows that are too crisp or perfectly defined
• An overall lack of shadows and highlights on the face that makes it look flat
• Shadows or highlights that appear pixelated or lower resolution than the rest of the image

If a face looks like it’s lit from multiple light sources or the shadows don’t make sense, that could indicate manipulation. Pay close attention to how shadows fall across the eyes, nose, and jawline since those are often difficult for AI to replicate accurately.

Blurred or Distorted Areas

Deepfake software struggles to generate realistic details, often resulting in smudged or warped areas, especially around the edges of the subject. The distortion may seem minor, but indicates manipulation.

If a deepfake video or photo of yourself appears online, don’t simply assume it is genuine. Take steps to report and verify the media. Look closely for signs of manipulation like blurred or distorted areas that could indicate edits. Then, contact the relevant social media platforms, hosting sites, and authorities to have the deepfake removed and investigated.

With awareness, vigilance and the right response, you can minimize the damage from a deepfake of yourself. The key is verifying any questionable media and quickly reporting it through the proper channels.

Unnatural Movement or Facial Expressions

In videos, look for unnatural movement or facial expressions. Deepfakes can make subtle human movements and expressions seem strange or mechanical. The timing and coordination may be off. Movements like blinking, head tilts or mouth movements may look awkward and unnatural. Trust your instincts if something feels “not quite right”.

While deepfakes are getting more sophisticated and realistic, a discerning eye can still detect signs of fakery. Look closely at the details, especially around the main subject, and watch for anything that seems even slightly unnatural or implausible. 

Are deepfake apps illegal?

With the rise of deepfakes, many are left wondering about their legal status. As it stands currently, deepfakes themselves are not illegal in the U.S. and many other countries. However, their use can be illegal under certain circumstances.

For example, using a deepfake to spread misinformation or manipulate people can violate laws around fraud, defamation, and false advertising. Deepfakes that violate a person’s privacy or are used for harassment may also face legal consequences. Some states have laws explicitly banning the nonconsensual creation or distribution of deepfakes.

While deepfake technology is rapidly advancing, laws and policies are still playing catch-up. Pending legislation like the DEEPFAKES Accountability Act aims to criminalize distributing deepfakes with the intent to harm or deceive. Critics argue these laws could infringe on free speech rights.

The key takeaway is that deepfakes themselves are legal, but how they’re used and distributed can cross legal lines. As the technology continues advancing, more comprehensive laws and policies will likely be needed to curb malicious use while protecting civil liberties. 

What Are the Benefits of DeepFakes?

Deepfake technology have some useful applications if used responsibly. 

1. Deepfakes can be used to create interactive virtual characters for entertainment or educational purposes. They have the potential to bring historical figures or characters to life for an immersive experience.
2. Deepfakes also show promise in the medical field. AI techniques used to generate deepfakes could help enhance medical imaging or create realistic avatars for telemedicine. Doctors have even used deepfake-style AI to model how a patient’s face may age over time to help plan cosmetic surgery.
3. Some companies are also experimenting with deepfakes for corporate training or product marketing. Anthropic, an AI safety startup, used deepfake videos of their own employees for a company-wide training on deepfake detection. Companies like Anthropomorphics create personalized AI avatars to help market products.

While deepfakes certainly pose risks, they also have the potential for many exciting and productive applications if developed and applied responsibly. 

When did Deepfake technology got invented?

Deepfake technology has been around for over 20 years, though it has advanced rapidly in recent times. The term “deepfake” first emerged in 2017, but the techniques that power deepfakes, neural networks and deep learning, have been developing since the 1990s.

In 2014, researchers from the University of Montreal published a paper demonstrating how neural networks could be used to generate highly realistic images of fictional handwritten digits. This helped inspire the development of Generative Adversarial Networks or GANs—the machine learning models behind most deepfakes today.

GANs work by pitting two neural networks against each other. One generates fake images or videos while the other tries to detect them as fakes. By repeating this process, the generative network gets better at creating realistic fakes that can fool humans and AI detectors.

Using these advances in AI, the first viral deepfakes began appearing on Reddit in late 2017, with people swapping celebrity faces into explicit videos. Since then, deepfake technology has become widely available in open-source software kits, enabling people to generate deceptive images and videos on their home computers.

Though the technology behind deepfakes has been in the works for decades, their use for malicious purposes is a relatively recent phenomenon. And as AI continues advancing rapidly, deepfakes are becoming more sophisticated, widespread and harder to detect.

Deepfake Incidents that Shook the World

1. The FaceApp “Deepfake” of Nancy Pelosi

In 2019, a video of Nancy Pelosi speaking that was altered using AI software went viral, slurring her speech and making it seem like she was intoxicated. The video spread rapidly online and raised concerns about the potential dangers of deepfakes.

2. Jordan Peele’s Obama Video Warning

In 2018, Actor Jordan Peele created a “deepfake” video of Barack Obama warning about the threat of synthetic media, calling for increased awareness and technological solutions. The video helped raise public attention to the deepfake issue.

3. The Deepfake App Used to Impersonate a CEO

In 2019, a UK marketing firm allegedly used deepfake technology to impersonate the CEO of a rival firm, tricking the company into revealing confidential information. The incident demonstrated how deepfakes could enable fraud and impersonation scams.

4. Deepfake video of Mark Zuckerberg

 In 2019, a viral deepfake video of Mark Zuckerberg surfaced, showing the Facebook CEO talking about stealing data and manipulating users. The video highlighted the dangers of misinformation and was created by artists to raise awareness about deepfakes.

How to Control Deepfakes?

With deepfake technology advancing rapidly, regulating and controlling their spread has become crucial. Unfortunately, there are currently no foolproof methods to detect or prevent deepfakes. However, there are a few steps individuals and companies can take to gain some control over deepfakes.

1. To spot deepfakes, look for subtle details that seem off, like blurred edges, unnatural eye movements or lighting changes, or differences in image quality across the video. You can also search online to verify the source and check if others have debunked it as fake. If you come across a deepfake, report it to the appropriate companies and authorities.
2. Platforms like Facebook, Twitter, and YouTube are starting to ban accounts that frequently share deepfakes and are investing in detection tools. However, deepfakes are still often shared on fringe websites and private groups. 
3. Laws against nonconsensual deepfakes could help, but regulating them poses risks to privacy and free speech.
4. In the future, improved digital forensics, blockchain-based media authentication, and AI detection systems may help identify deepfakes more accurately. However, as the technology continues advancing, the arms race between deepfake creators and detectors is unlikely to end. 

Overall, the best way to control the spread of deepfakes is through education and promoting critical thinking so people can better assess the media they consume.

How to download a Deepfake app?

Downloading a deepfake app is pretty straightforward. Here are the basic steps:

1. Some apps allow you to download them directly onto your mobile device or computer. Check the app store on your device, and search for “deepfake.” You’ll find options like DeepFaceLab, Faceswap, and ReFace. These apps are free to download and use.
2. After downloading the app, you’ll have to allow it access to your photos, videos, and camera. The app needs access to images of the faces it will be manipulating and swapping. Choose photos of the people you want to create deepfakes of.
3. Upload the photos to the app. It will detect the faces in the images and allow you to map them onto videos or other photos. Select the video or image you want to add the face to. The app does the rest, mapping the facial features and adjusting the new face to match lighting and head position.
4. Some apps offer additional customization, like adjusting hair color or adding facial hair. You can review the results and make tweaks to improve the realism. When you’re satisfied, save the deepfake video by using deepfake video maker to your camera roll or share directly to social media.

That’s the basic process for downloading and using a deepfake app to create convincing face-swapped videos and images. 

FAQs:

Can I create a deepfake for free?

Yes, there are free deepfake tools available for hobbyists and amateurs. Deepfakery, Zao and Reface are popular free apps that use AI to swap faces in photos and videos. They’re easy to use but limited to manipulating selfies and short clips. For higher quality, personalized deepfakes, you’ll need paid software and lots of images of the people you want to simulate.

Are deepfake apps easy to spot?

Not always. While many deepfakes still look obviously artificial, the technology is advancing rapidly. Higher quality deepfakes that manipulate real photos and videos of a person can be very convincing. Some signs a video may be a deepfake include:

• Unnatural head/eye movements or facial expressions
• Blurred or distorted areas around the mouth or eyes
• Inconsistent skin tones or lighting on the face compared to the rest of the video

The best way to spot deepfakes is to look for these types of visual anomalies, especially around the eyes and mouth, and see if anything looks “off”. When in doubt, check verified social media accounts of public figures to confirm the authenticity of suspicious media.

Can deepfakes be tracked or detected?

Deepfake detectors are in development but still limited. Some forensics techniques can analyze photos and videos for signs of manipulation, but deepfake creators are also working to evade detection with improved realism. There are also “deepfake provenance” techniques which aim to identify the deepfake generation model used, in order to trace a deepfake back to its creator. However, if a deepfake is convincing enough, it may still spread widely before being debunked.

Conclusion

Deepfake apps may seem fun and harmless, but they come with serious risks that you should weigh carefully. While the technology behind them is impressive, it’s also dangerous when used irresponsibly or maliciously. The best thing you can do is educate yourself on how to spot deepfake videos, protect your photos from being used, and speak out against unethical uses. We all have to do our part to promote truth in the digital age. But don’t let fear stop you from embracing new tech responsibly. With care and wisdom, we can harness AI for good while mitigating the bad. What matters most is cultivating discernment, empathy and integrity within ourselves and our communities..

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