This report is an all-encompassing analysis of the current state of the art of deepfakes and their underlying technology, the contexts in which deepfakes are and can be used, the impact of deepfakes in the various areas of application, as well as active initiatives and cutting-edge techniques used to detect them.
It focuses on artificial intelligence and its major subfields, identifies deepfakes creation and detection examples including use cases and provides a quick overview of the national initiatives developed to tackle deepfakes.
Key questions answered in the report:
- What are “Deepfakes” and what is the technology behind them?
- What are their areas of application?
- What techniques can spot them and who are the major players engaged in developing such techniques?
- What are countries doing to face the threats deepfakes bring to the societies?
List of Players and Solutions
- ANSAcheck: ANSA, Ernst & Young Advisory
- Avatarify
- DeepFaceLab
- Deepfakes web
- Deepnews.ai: Frederic Filloux
- Descript Lyrebird Overdub
- FaceApp
- Facebook: Facebook’s AI tool
- Faceswap
- Face Swap Live
- FakeApp
- FANDANGO: Ingegneria Informatica Spa, EU Commission
- Gfycat AI tool: Gfycat
- Google News Initiative: Google, 11+ newborn startups
- InVID & WeVerify: AFP, DW, MediaLab, ITI-CERTH, EU Commission
- Make me old
- Microsoft: Microsoft Video Authenticator
- Modulate.ai
- My Heritage
- Parodist
- Project Origin: BBC, CBC Radio Canada, The New York Times, Microsoft
- Reface
- Rephrase.ai
- ResembleAI
- Sensity’s AI technologies: Sensity
- SocialTruth: Greek Institute of Communication and Computer Systems, EU Commission
- The News Provenance Project: IBM - The New York Times
- VoiceApp: AI voice changer
- Zao
Table of Contents
1. Key findings
2. What deep learning has changed
2.1. Introduction of concept
- Artificial Intelligence
- Machine Learning, a branch of Artificial Intelligence
- Deep Learning, a branch of Machine Learning
- Deep Learning, an AI game changer
2.2. Impact of deep learning
3. Explaining deepfakes
3.1. Deepfakes
3.2. Implications of deepfakes
3.3. Deepfakes areas of applications
3.4. Positive and neutral impacts of deepfakes
3.5. Deepfakes software
3.6. Conception of deepfakes
3.7. Deepfakes creation offering
4. AI, generating disinformation
4.1. Benchmark of deepfakes creation
4.2. Deepfakes web - face-swap
4.3. REFACE - face-swap
4.4. Modulate.ai - voice cloning
4.5. Rephrase.ai - deepfake videos speaking any new text
5. AI, Detecting deepfakes
5.1. Major national initiatives that tackle misinformation
5.2. The common techniques of deepfake detections
5.3. Deepfakes detection techniques
- Facebook’s AI tool
- Microsoft Video Authenticator
- InVID & WeVerify
- Project Origin
- The News Provenance Project
5.4. Benchmarking of active initiatives on detecting deepfakes and disinformation
Samples
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Methodology
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