Key takeaways
- Deepfakes are fake videos or audio made with artificial intelligence to make it look like someone did or said something they didn’t.
- Look for strange facial expressions, mismatched lip movements or unusual video lighting. For audio, listen for robotic sounds or unnatural pauses.
- Make sure the content comes from a reliable source. If it’s from somewhere suspicious, it might be a deepfake.
- Use tools like browser extensions or apps to spot fake content by checking for signs of manipulation.
In today’s digital age, it’s getting harder to tell what’s real and what’s fake, especially when it comes to audio and video.
Imagine seeing a video of a famous tech billionaire announcing a unique cryptocurrency project that offers a buy-one-get-one-free coin or hearing their voice promoting an airdrop opportunity. Sounds convincing, right? But what if it’s all fake?
This is the reality of deepfakes, which are videos and audio clips created using artificial intelligence to make it seem like someone said or did something they didn’t.
While some deepfakes are just for fun, others can be used for scams, misinformation, or even to manipulate public opinion. The Australian Federal Police disclosed that scammers use deepfakes and pig butchering as their primary tactics to defraud victims in the country.
But the good news is that there are ways to spot these fakes, and you can avoid being fooled with a little awareness.
Let’s explore how you can start recognizing deepfakes before they deceive you.
What are deepfakes?
Digitally altered videos or audio that use advanced technology to manipulate someone’s appearance or voice are called deepfakes. A deepfake video or audio seems like they said or did something unreal. But how is it possible to create such a media?
It’s none other than deepfake creation tools that have made it easier for anyone to create these fake videos or audio, leading to some that have gone viral online. While some of the deepfake examples are used for entertainment purposes, the impact of deepfakes on society could be harmful.
For example, there have been instances where deepfake videos featured public figures like Elon Musk seemingly endorsing fake crypto schemes. These famous deepfake videos can spread misinformation, create confusion and even damage reputations, as they easily mislead people into investing in fraudulent projects.
The most challenging part is that deepfake manipulation techniques are becoming so advanced that it’s sometimes hard to tell the difference between deepfakes and real video.
Did you know? The term “deepfake” originated from a combination of “deep learning” (a type of AI used to create fake content) and “fake.” AI-generated fake videos first grabbed public attention in late 2017 when a Reddit user named Deepfakes shared pornographic videos created with a deep neural network-based face-swapping algorithm.
How do deepfakes work?
Deepfakes learn from real data by using powerful AI, and then they produce content that looks and sounds real but isn’t. Here’s a simple rundown of how they are created:
- Gathering data: First, the technology needs many examples of the person’s face or voice to learn from real data. These could be photos, videos or audio recordings.
- Training the AI: The examples serve as the basis for AI to learn how the person looks and sounds. It’s similar to mimicking someone with lots of practice.
- Creating the fake: The AI generates new content after gaining sufficient knowledge. It seems realistic when it switches faces or alters expressions for videos. When used with audio, it imitates a person’s voice to say things they never said.
- Fine-tuning: The AI may make slight adjustments to make the fake content even more believable. This entails fine-tuning specifics to ensure the fake audio or video sounds and looks as authentic as possible.
Now that you know how deepfakes are created, it’s time to find out how to protect yourself from them.
How to spot deepfake videos?
Wondering how to spot deepfake videos? Here are some warning signs you need to be aware of to determine whether a video is genuine or a deepfake:
- Look for inconsistencies: Deepfakes sometimes struggle with natural expressions. If you find a video with odd facial expressions or mismatched lip movements, it’s probably AI-generated.
- Check the eyes: Look closely at the eyes. Deepfakes often have issues with eye movements or reflections that can seem unnatural or out of sync.
- Examine the lighting and shadows: The video may be fake if the lighting on the face doesn’t match the rest of the scene.
- Listen carefully: If it’s a deepfake audio, listen for unnatural pauses, robotic tones or inconsistencies in the voice’s emotion.
- Verify the source: If the video seems to have come from an unknown or suspicious account or an unreliable source, it might be fake.
- Use detection tools: Tools available can analyze videos for signs of manipulation. While not foolproof, they can be a helpful first step.
- Cross-check with trusted information: Look for other sources or news outlets to confirm if the content is genuine or has been reported as fake.
Did you know? One deepfake crypto scam featured a fake site using the “Make America Great Again” logo and an image of Donald Trump, falsely claiming to host “Trump’s biggest crypto giveaway of $100,000,000.”
How to detect deepfake audio
Imagine you received a video on Telegram of someone who sounds like a famous crypto influencer claiming they’ve just launched a revolutionary new coin.
Here’s how you can identify if it’s a real or a deepfake:
- Listen for robotic tones: A deepfake often has a strange, mechanical quality. For example, if the influencer’s voice lacks the natural ups and downs and is smoother than expected, that could be a sign of artificial manipulation.
- Pay attention to speech patterns: Notice if the speech flows naturally. It might not be a genuine recording if the expert pauses awkwardly, the speech patterns seem off, and there are unnatural breaks or stutters.
- Check for emotional disconnect: Genuine voices typically convey feelings appropriate for the situation. It may be a deepfake if the expert seems unduly excited or strangely flat when discussing something that ought to elicit a different emotional response.
- Compare to known recordings: If you have other recordings of the expert, compare them. Are there differences in how they speak or pronounce words? That could help you spot a fake.
- Observe background noise: Real recordings often include background sounds like an office buzz or distant chatter. If the audio is too clear or lacks these details, it’s a red flag.
- Use detection software: Tools that analyze audio to spot signs of manipulation are available. Running the clip through one of these tools can provide an extra layer of verification.
Tools to identify deepfakes
According to Bitget Research, crypto losses from deepfake scams are expected to exceed $25 billion in 2024, more than doubling last year’s figures. Their June report highlighted a 245% rise in deepfake incidents globally, according to data from Sumsub. Therefore, it’s more important than ever to identify deepfakes and protect yourself from scams.
There are several tools available to help you spot deepfakes:
- Browser extensions: Some extensions can be added to your web browser to flag potentially fake content as you browse.
- Video forensics tools: These tools scan video files for indications of manipulation, such as pixel mismatches or altered information.
- Deepfake detection apps: These applications scan pictures and videos for indications of tampering. They frequently observe things like changes in lighting and facial expressions.
- Reverse Image Search: Tools like Google Reverse Image Search can help you find an image’s original source, which might reveal whether it’s been altered.
- Voice analysis software: These can help detect deepfake audio by analyzing voice recordings for synthetic tones.
Did you know? Bitget predicts that, without stronger safeguards, deepfakes could make up as much as 70% of crypto-related crimes by 2026.
History of deepfakes
As you have learned what deepfakes are and how to spot fake videos and audio, you might want to know how the world ended up with videos that look so real but are entirely fake. Here’s a quick tour through the history of deepfakes:
Early days
- 1990s: People started making computers change faces in videos.
- 1997: A program called “Video Rewrite” could change a person’s face in a video to match a different voice.
The rise of deepfakes
- 2017: The term “deepfake” gained widespread attention with the emergence of the Reddit subreddit and the release of open-source deepfake creation tools (e.g., deep learning frameworks like TensorFlow and PyTorch).
- 2018: As deepfakes’ quality rose and their potential for abuse grew, they became a serious concern.
- 2019: Deepfakes were used in various malicious activities, including political disinformation and financial fraud.
The fight against deepfakes
- 2020 to present: As technology improves, efforts to find ways to identify fake audio recordings and videos like mismatched lip-syncing and unnatural speech patterns are getting stronger. Researchers are also developing fake video detection tools that can help analyze inconsistencies that may not be visible to the naked eye.
Ethical concerns of deepfakes
You shouldn’t overlook the significant ethical concerns that come with deepfakes. They raise serious questions about truth and trust since they are able to produce fake yet highly realistic videos and audio.
Deepfakes, for example, can be used to spread misleading information, trick people into thinking they are hearing the truth, or even destroy reputations by fabricating controversies.
Additionally, the technology can violate privacy by using people’s voices or faces in misleading or improper circumstances. It resembles having a superpower that can be applied to both negative and positive ends.
Deepfakes are becoming more advanced, therefore, it’s critical that tech companies, governments and individuals collaborate to discover solutions to stop their misuse and keep people safe.
Did you know? Bitget predicts that, without stronger safeguards, deepfakes could make up as much as 70% of crypto-related crimes by 2026.
The future of deepfake technology
Deepfake technology is expected to be both exciting and challenging. It has the potential to completely change how people produce and consume media. It can be used to create realistic and engaging virtual reality experiences, bring back deceased actors or create new characters that were once beyond anyone’s reach.
But there’s a flip side too. Deepfakes have the potential to spread incorrect information or produce convincingly fake proof. To fully realize the potential of deepfakes while constraining their harmful applications, it will be imperative that you follow ethical guidelines properly.
Plus, blockchain forensics could be helpful. By using blockchain to create a clear, tamper-proof record of where media comes from and how it’s been changed, it becomes easier to verify the authenticity of digital content. This approach could work alongside measures like the Content Origin Protection and Integrity from Edited and Deepfaked Media Act, helping to tell the difference between real and manipulated content. Finding the right balance between innovation and caution will be critical as the technology evolves.