With the rapid advancement of AI technology in recent years, an increasing number of celebrities have become victims of deepfake technology.
Recently, the rising TikTok star Brooke Monk has found herself at the center of a digital storm, thrusting the dark side of deepfake technology into the spotlight.
This unsettling incident not only highlights the personal toll on content creators but also ignites a crucial debate about privacy rights, consent in the digital age, and the ethical boundaries of artificial intelligence.
In this blog, I’ll introduce the Brooke Monk’s Deepfake incident, how to create such deepfake using toady’s AI technology and how to detect deepfake contents.
Overview of Brooke Monk Deepfake Incident
Known for her witty skits and infectious charm, TikTok sensation Brooke Monk suddenly found herself thrust into a nightmarish scenario. A malicious user unleashed a digital wildfire by posting a deceptive video, falsely claiming that explicit photos of Monk had been leaked.
This spark ignited an inferno of fabricated images spreading across the internet like wildfire, shattering Monk’s privacy and subjecting her to a brutal trial by public opinion.
The incident laid bare the terrifying potential of deepfake technology to wreak havoc on unsuspecting individuals.
In a disturbing twist, online voyeurs fueled the fire, urging the account to keep churning out these fabricated intimate videos.
These digital rubberneckers shamelessly proclaimed their engagement with the content, using the hashtag ‘leaktok’ to game TikTok’s algorithm and flood their ‘For You Pages’ with more of the invasive material.
Brooke Monk’s Response to Her Deepfakes
In light of the distressing situation, Brooke publicly expressed her emotional pain and frustration. She described feeling dehumanized and objectified by the malicious use of her image.
Despite her efforts to clarify the authenticity of the circulating content, the deepfakes continued to spread online, highlighting the challenges of combating synthetic media manipulation in today’s digital landscape
Afterwards, Brooke shared a screen recording of the comment section on her backup account, where she lip-synced to Taylor Swift’s song ‘The Man.’ To provide context for her fans, she wrote: ‘These comments are from a DEEP FAKE video of me’
Public Reaction and Support
The original account has been banned, but a new one has emerged, promising to continue posting. They’ve labeled Brooke as an “enemy” and shared a screen recording of the ban message to prove they are the same person.
Fortunately, Brooke’s fans are stepping in to defend her. One fan commented, “I saw that 🙁 it made me so sad. I’m so sorry Brooke, nobody deserves that.” Another added, “I am so sorry, omg that’s terrible.”
However, the individual responsible for posting the misleading video exhibited clout-chasing behavior, aiming to capitalize on Brooke’s popularity for personal gain.
Some people are still interacting with the account, trying to flood the algorithm with fake content about Brooke.
What is DeepFake?
Deepfake technology is a fascinating yet concerning innovation in the realm of artificial intelligence (AI) that allows for the creation of highly realistic fake images, videos, and audio recordings.
The term “deepfake” is a combination of “deep learning” and “fake.” Deep learning refers to a subset of AI that uses neural networks to analyze vast amounts of data and learn from it.
Deepfakes utilize this technology to manipulate media content, making it appear as though someone is doing or saying something they did not actually do or say.
How DeepFake Works?
Deepfake technology uses two main types of AI algorithms:
- Generator: This algorithm creates fake content by learning from existing images or videos of a person.
- Discriminator: This algorithm checks the generated content to see if it looks real or fake.
These algorithms work together through a process called Generative Adversarial Networks (GANs).
The generator keeps improving its fake content based on feedback from the discriminator until the fake content looks just like real media.
There are 3 types of Deepfakes:
- Video Deepfakes: These swap faces in videos or overlay one person’s face onto another’s actions. For example, a video might falsely show a celebrity saying something controversial.
- Audio Deepfakes: These use AI to mimic someone’s voice, creating realistic audio clips of things they never actually said.
- Image Manipulation: This alters still images to create fake photos that misrepresent reality.
How Were Deepfakes Created?
To create a successful Deepfake, there are three objects involved:
- Target Photo/Video: This is the material where you want to replace the face, keeping everything else the same.
- Source Photo: This is the image of the face to use for the swap.
- Result Photo/Video: This is the final product after the face has been swapped.
A successful deepfakes will need:
- Photos of Target face: Note that only photos are sufficient. Only the facial features will be extracted by AI.
- Target video: The face and voice of the target video needs to to replaced.
- Right Tools for swapping face
Once you have the necessary materials, using the appropriate tools is crucial for creation. GenZone AI is an all-in-one AI tool website that offers both video/photo face swap tools.
*Disclaimer: The websites used in the following demo are only for showcasing face-swapping functionality and do not support any deepfake services.
(1) Visit genzone.ai/video-face-swap sign up or sign in.
(2) Click ‘upload content’ to upload the target video
(3) Click ‘Faces’ on the right and ‘Add Face’ to upload the face you want to swap.
(4) Click ‘Generate’ and wait for a few seconds you’ll have the result. You can download the video directly.
Damage and Problems caused by DeepFake
Deepfake technology brings many issues that affect individuals, society, and the law.
Misinformation and Public Trust
Deepfakes can create misleading content that spreads quickly online, causing confusion and distrust.
As deepfakes get better, it becomes harder to tell what’s real. This makes people skeptical of all digital content, undermining trust in media and government.
Privacy Violations
Deepfakes often use images or videos of people without their permission, leading to serious privacy issues. This is especially troubling with deepfake pornography, which can cause psychological harm and damage reputations.
Victims of deepfakes, especially women, may face harassment or exploitation, leading to emotional distress and trauma.
Legal Ramifications
Deepfakes can create fake evidence that misleads courts, potentially causing wrongful convictions or acquittals.
Fraud and Financial Crimes: Deepfakes have been used in scams, like impersonating executives in video calls to authorize fraudulent transactions.
Societal Impact
Malicious actors can use deepfakes to create chaos or manipulate politics. Fake videos of leaders making inflammatory statements can incite unrest or change public perception during elections or crises.
Psychological Effects
Being targeted by deepfakes can cause severe emotional distress, including feelings of humiliation, anxiety, and depression.
The widespread use of deepfakes can make people doubt the authenticity of real interactions, affecting trust and communication in society.
How To Detect a Deepfake Video using your eyes?
Spotting deepfake content can be challenging, but there are several visual cues and techniques you can use to identify potential fakes.
(1）Look at the Face: High-end DeepFakes usually focuses on facial transformations.
(2) Check the Cheeks and Forehead: Is the skin too smooth or too wrinkly? Does it match the age of the hair and eyes? DeepFakes might not get these details right.
(3) Examine the Eyes and Eyebrows: Are the shadows where they should be? DeepFakes might miss the natural physics of a scene.
(4) Inspect the Glasses: Is there glare? Is it too much? Does the glare change angle when the person moves? DeepFakes might not handle lighting correctly.
(5) Look at Facial Hair: Does the facial hair look real? DeepFakes might add or remove mustaches, sideburns, or beards, but they might not look natural.
(6) Notice Facial Moles: Do the moles look real?
(7) Watch for Blinking: Does the person blink enough or too much?
(8) Observe Lip Movements: Some DeepFakes use lip syncing. Do the lip movements look natural?
(9) Assess Lighting and Shadows: Look at how light interacts with the face and surroundings. In real videos, lighting should be consistent. Deepfakes might have conflicting shadows or unnatural lighting that doesn’t match the environment.
(10) Inspect Background Details: The background should move naturally with the subject. If the background elements are out of sync, overly blurred, or pixelated, it could be a sign of digital manipulation.
Further Reading: Taylor Swift’s Deepfake incident
In early 2024, explicit and fabricated images of Taylor Swift began circulating widely on social media platforms, particularly on X (formerly Twitter). These deepfakes depicted her in pornographic scenarios without her consent, leading to a massive outcry from her fanbase, known as “Swifties,” and raising alarm among lawmakers and advocacy groups.
Final Thoughts
As AI technology continues to advance, our privacy and security online face significant challenges.
In the future, while enhancing security measures, we should also understand that we should be skeptical of any content online, whether audio or video.
Once people stop taking online content at face value, the harm caused by deepfakes will be greatly reduced.
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