ZeroFake
ZeroFake
Design Challenge
Design Challenge
Timeline
Timeline
March 2025
48 Hours
March 2025
48 Hours
Role
Role
UX Researcher
UI/UX Designer
Art Direction
UX Researcher
UI/UX Designer
Art Direction
Tool
Tool
Figma
Deepfakes web
Midjourney
Runway
Chatgpt
Figma
Deepfakes web
Midjourney
Runway
Chatgpt
ZeroFake is the first mobile app that leverages iOS Dynamic Island to deliver real-time deepfake detection, helping users instantly identify, understand, and respond to deepfake content, fostering awareness and trust in the digital age.
ZeroFake is the first mobile app that leverages iOS Dynamic Island to deliver real-time deepfake detection, helping users instantly identify, understand, and respond to deepfake content, fostering awareness and trust in the digital age.
Timeline
Timeline
Timeline
15h 3/28-3/30
15h 3/28-3/30
15h 3/28-3/30
Challenge Prompt
Challenge Prompt
Challenge Prompt
Deepfake technology on platforms like youtube/social media poses a threat by spreading misinformation, defamation, and harmful content. The ease of creating and sharing deepfakes undermines trust, manipulates public opinion, and damages reputations. There is a pressing need for solutions to detect and prevent deepfake content on social media.
Deepfake technology on platforms like youtube/social media poses a threat by spreading misinformation, defamation, and harmful content. The ease of creating and sharing deepfakes undermines trust, manipulates public opinion, and damages reputations. There is a pressing need for solutions to detect and prevent deepfake content on social media.
Deepfake technology on platforms like youtube/social media poses a threat by spreading misinformation, defamation, and harmful content. The ease of creating and sharing deepfakes undermines trust, manipulates public opinion, and damages reputations. There is a pressing need for solutions to detect and prevent deepfake content on social media.
Challenge Prompt
Deepfake technology on platforms like youtube/social media poses a threat by spreading misinformation, defamation, and harmful content. The ease of creating and sharing deepfakes undermines trust, manipulates public opinion, and damages reputations. There is a pressing need for solutions to detect and prevent deepfake content on social media.
Solution
Solution
Solution
ZeroFake is the first ios app to provide real-time deepfake detection and use iOS Dynamic Island for instant alerts. With detailed reports, one-tap reporting, and interactive learning modules, it empowers people to spot, understand, and stop deepfakes, restoring trust in the content they consume.
ZeroFake is the first ios app to provide real-time deepfake detection and use iOS Dynamic Island for instant alerts. With detailed reports, one-tap reporting, and interactive learning modules, it empowers people to spot, understand, and stop deepfakes, restoring trust in the content they consume.
ZeroFake is the first ios app to provide real-time deepfake detection and use iOS Dynamic Island for instant alerts. With detailed reports, one-tap reporting, and interactive learning modules, it empowers people to spot, understand, and stop deepfakes, restoring trust in the content they consume.
ZeroFake is the first ios app to provide real-time deepfake detection and use iOS Dynamic Island for instant alerts. With detailed reports, one-tap reporting, and interactive learning modules, it empowers people to spot, understand, and stop deepfakes, restoring trust in the content they consume.
Live Detection and Instant Feedback
Live Detection and Instant Feedback
Live Detection and Instant Feedback
Live Detection and Instant Feedback
Detailed Analysis and Seamless Reporting
Detailed Analysis and Seamless Reporting
Detailed Analysis and Seamless Reporting
With detailed analysis featuring confidence levels and insights, users can understand the reasoning behind detection.
With detailed analysis featuring confidence levels and insights, users can understand the reasoning behind detection.
With detailed analysis featuring confidence levels and insights, users can understand the reasoning behind detection.
With detailed analysis featuring confidence levels and insights, users can understand the reasoning behind detection.
With one tap, the report will be forward to trusted platforms
With one tap, the report will be forward to trusted platforms
With one tap, the report will be forward to trusted platforms
With one tap, the report will be forward to trusted platforms
After report submission, users can track the final decision, gaining a sense of achievement in contributing to online safety.
After report submission, users can track the final decision, gaining a sense of achievement in contributing to online safety.
After report submission, users can track the final decision, gaining a sense of achievement in contributing to online safety.
After report submission, users can track the final decision, gaining a sense of achievement in contributing to online safety.
Interactive Modules for Deepfake Awareness
Interactive Modules for Deepfake Awareness
Interactive Modules for Deepfake Awareness
Quizzes to test and enhance users’ judgment
Quizzes to test and enhance users’ judgment
Quizzes to test and enhance users’ judgment
Quizzes to test and enhance users’ judgment
The learn feature provides users with educational activities, structured learning modules, and curated articles to build awareness and knowledge of deepfakes.
The learn feature provides users with educational activities, structured learning modules, and curated articles to build awareness and knowledge of deepfakes.
The learn feature provides users with educational activities, structured learning modules, and curated articles to build awareness and knowledge of deepfakes.
The learn feature provides users with educational activities, structured learning modules, and curated articles to build awareness and knowledge of deepfakes.
Process
Process
Process
What Is Deepfake?
What Is Deepfake?
What Is Deepfake?
Deepfake technology uses autoencoders and GANs to swap faces in videos. It extracts facial features from one person, maps them onto another using a trained model, and improves realism through a generator–discriminator loop. This process creates highly realistic fake videos that are hard to detect.
Deepfake technology uses autoencoders and GANs to swap faces in videos. It extracts facial features from one person, maps them onto another using a trained model, and improves realism through a generator–discriminator loop. This process creates highly realistic fake videos that are hard to detect.
Deepfake technology uses autoencoders and GANs to swap faces in videos. It extracts facial features from one person, maps them onto another using a trained model, and improves realism through a generator–discriminator loop. This process creates highly realistic fake videos that are hard to detect.
Deepfake technology uses autoencoders and GANs to swap faces in videos. It extracts facial features from one person, maps them onto another using a trained model, and improves realism through a generator–discriminator loop. This process creates highly realistic fake videos that are hard to detect.
*Technical Mechanism
*Technical Mechanism
Autoencoders
Autoencoders
A shared encoder compresses the source face into a latent representation capturing traits such as structure and movement, which a target-specific decoder uses to reconstruct the target face.
A shared encoder compresses the source face into a latent representation capturing traits such as structure and movement, which a target-specific decoder uses to reconstruct the target face.
A shared encoder compresses the source face into a latent representation capturing traits such as structure and movement, which a target-specific decoder uses to reconstruct the target face.
Generative Adversarial Networks (GANs)
Generative Adversarial Networks (GANs)
The generator produces images from the latent space, while the discriminator judges their realism.”
The generator produces images from the latent space, while the discriminator judges their realism.”
The generator produces images from the latent space, while the discriminator judges their realism.”
Deepfakes on Social and Video Platforms
Deepfakes on Social and Video Platforms
Deepfakes on Social and Video Platforms
Social Risks and Impact
Social Risks and Impact
Impact on Media & Journalism
Impact on Media & Journalism
Impact on Media & Journalism
Misinformation & Trust Crisis
Misinformation & Trust Crisis
Misinformation & Trust Crisis
Reputation Damage & Personal Harm
Reputation Damage & Personal Harm
Reputation Damage & Personal Harm
Financial Fraud & Scams
Financial Fraud & Scams
Financial Fraud & Scams
Political Manipulation and Election Integrity
Political Manipulation and Election Integrity
Political Manipulation and Election Integrity
Legal and Ethical Concerns
Legal and Ethical Concerns
Legal and Ethical Concerns
Market Research
Market Research
Market Research
Who are the Target Users?
Who are the Target Users?
Who are the Target Users?
Young adults aged 18–29, who make up 37% of social media and video platform users, are the most active group online therefore particularly vulnerable to misinformation and the unintentional spread of deepfake content.
Young adults aged 18–29, who make up 37% of social media and video platform users, are the most active group online therefore particularly vulnerable to misinformation and the unintentional spread of deepfake content.
Young adults aged 18–29, who make up 37% of social media and video platform users, are the most active group online therefore particularly vulnerable to misinformation and the unintentional spread of deepfake content.
Young adults aged 18–29, who make up 37% of social media and video platform users, are the most active group online therefore particularly vulnerable to misinformation and the unintentional spread of deepfake content.
Key Opportunities
Key Opportunities
Get Suspicious Content Checked with Ease
Get Suspicious Content Checked with Ease
Get Suspicious Content Checked with Ease
Users like Emily often act impulsively, a seamless and fast way to verify content is essential to interrupt misinformation before it's shared.
Users like Emily often act impulsively, a seamless and fast way to verify content is essential to interrupt misinformation before it's shared.
Users like Emily often act impulsively, a seamless and fast way to verify content is essential to interrupt misinformation before it's shared.
Deepfaked Content Should be Warned or Reported
Deepfaked Content Should be Warned or Reported
Deepfaked Content Should be Warned or Reported
Without visible cues or reporting tools, users may unknowingly trust and amplify manipulated content.
Without visible cues or reporting tools, users may unknowingly trust and amplify manipulated content.
Without visible cues or reporting tools, users may unknowingly trust and amplify manipulated content.
Enhance User Awareness of Deepfake and Its Risks
Enhance User Awareness of Deepfake and Its Risks
Enhance User Awareness of Deepfake and Its Risks
Many young adults lack basic knowledge of deepfakes, leaving them vulnerable to manipulation and false narratives.
Many young adults lack basic knowledge of deepfakes, leaving them vulnerable to manipulation and false narratives.
Many young adults lack basic knowledge of deepfakes, leaving them vulnerable to manipulation and false narratives.
Ideation
Ideation
During ideation, I brainstormed different solutions to address the pain points. After finalizing the key features, I explored the feature’s layout and user flow, establishing a foundation for the product’s structure.
During ideation, I brainstormed different solutions to address the pain points. After finalizing the key features, I explored the feature’s layout and user flow, establishing a foundation for the product’s structure.
Brand Direction
Brand Direction
With a bold purple and neutral gray palette paired with modern, neutral typography, the brand creates a minimalist yet tech-driven aesthetic and conveys professionalism and trust.
With a bold purple and neutral gray palette paired with modern, neutral typography, the brand creates a minimalist yet tech-driven aesthetic and conveys professionalism and trust.
Reflection
Reflection
Reflection
Technical depth
Technical depth
Although I researched deepfake-related technologies, mobile AI backend detection and Dynamic Island permissions. This was only a preliminary exploration, and further confirmation and expert consultation are needed.
Although I researched deepfake-related technologies, mobile AI backend detection and Dynamic Island permissions. This was only a preliminary exploration, and further confirmation and expert consultation are needed.
Although I researched deepfake-related technologies, mobile AI backend detection and Dynamic Island permissions. This was only a preliminary exploration, and further confirmation and expert consultation are needed.
User flows & features
User flows & features
Due to time limitations, not all flows and functions were fully developed. Future work should refine the various scenarios within real usage to ensure a seamless and logically consistent user experience.
Due to time limitations, not all flows and functions were fully developed. Future work should refine the various scenarios within real usage to ensure a seamless and logically consistent user experience.
Due to time limitations, not all flows and functions were fully developed. Future work should refine the various scenarios within real usage to ensure a seamless and logically consistent user experience.
Feedback & growth
Feedback & growth
Sharing the project more widely and collecting feedback from experts, peers, and potential users will help strengthen the concept and shape it into a more robust and impactful solution.
Sharing the project more widely and collecting feedback from experts, peers, and potential users will help strengthen the concept and shape it into a more robust and impactful solution.
Sharing the project more widely and collecting feedback from experts, peers, and potential users will help strengthen the concept and shape it into a more robust and impactful solution.
