Challenge Question
How can we differentiate real videos from deepfake videos?
Project Source: Kaggle, via Lassonde
Project Summary
Deepfake techniques, which present realistic AI-generated videos of people doing and saying fictional things, have the potential to have a significant impact on how people determine the legitimacy of information presented online. These content generation and modification technologies may affect the quality of public discourse and the safeguarding of human rights—especially given that deepfakes may be used maliciously as a source of misinformation, manipulation, harassment, and persuasion. Identifying manipulated media is a technically demanding and rapidly evolving challenge that requires collaborations across the entire tech industry and beyond. AWS, Facebook, Microsoft, the Partnership on AI’s Media Integrity Steering Committee, and academics have come together to build the Deepfake Detection Challenge (DFDC). The goal of this challenge is to develop a new technology that can help detect deepfakes and manipulated media. Interested students might have experience in web/software development, computer science/engineering, AI/machine learning, and digital communication. This challenge originated from the Kaggle website, and team members will be working with a York University mentor rather than a mentor from the organization.
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Organizational Profile
Kaggle is an online data science and machine learning community that also serves as a repository of code and data. Users can find and publish high-quality data sets, write code and build models, ask questions and collaborate, and take data science and machine learning courses through the website. Kaggle also runs competitions, where users have the opportunity to apply their knowledge to real-world machine learning problems and solve a number of complex global challenges.
Partner Website
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Additional Resources
Key Words
- Deepfake
- Manipulated Media
- Information Integrity
- Artificial Intelligence