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Fighting Fake News With AI and Crowdsourcing

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Discover how the Wall Street Journal is using advanced technologies to combat fake news. You’ll hear about ultra-realistic voice and video cloning technologies that will make you question the legitimacy of recordings. You’ll also hear how machine learning, artificial intelligence and the crowd are being deployed to defend against this threat and others.

Published in: News & Politics
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Fighting Fake News With AI and Crowdsourcing

  1. 1. FIGHTING FAKE NEWS WITH AI AND CROWDSOURCING
  2. 2. RAJIV PANT CTO & CPO, The Wall Street Journal @rajivpant
  3. 3. DEEPFAKE Videos, images, or audio files are generated or altered to dupe an audience into thinking they are real.
  4. 4. FACESWAP § Most common form of Deepfake § Accessible to amateur users § Minimal difference between professional editing and Faceswap
  5. 5. LIP SYNC FROM AUDIO § Converts audio files into realistic mouth shapes § Mouth shapes grafted to existing videos § Can be used to fake speech/video 1. Recurrent Neural Network INPUT AUDIO 2. Mouth Synethesis SPARSE SHAPE 3. Re-timing TARGET VIDEO 4. Final Composition FINAL OUTPUT
  6. 6. FACIAL REENACTMENT § Transfers facial expressions § Algorithm tracks and adjusts movements § New versions can detect head/body movements SOURCE SEQUENCE UNMODIFIED TARGET SEQUENCE RESULT
  7. 7. VIDEO ALTERATION § Algorithm can change the weather or time of day in a video § Micro-edits to remove details within video § Harder to spot than more blatant fakes
  8. 8. AI GENERATED IMAGES § Whole parts of pictures can be replaced § Could make spotting fakes even harder § Images can be edited to look more natural
  9. 9. APPLICATIONS OF DEEPFAKE TECHNOLOGY
  10. 10. WHICH OF THESE CELEBRITY HEADSHOTS IS FAKE?
  11. 11. HOW ARE DEEPFAKES CREATED? § Cat-and-mouse game between two neural networks § Generative Adversarial Networks (GAN)
  12. 12. 3 REASONS WHY EXPERIENCE MATTERS
  13. 13. CREDIBILITY IS ESSENTIAL TO THE WSJ BRAND
  14. 14. READERS TRUST THE WSJ TO BE ACCURATE
  15. 15. READERS RELY ON THE WSJ’S WEB AND MOBILE APPS
  16. 16. 3 WAYS TO FIGHT DEEPFAKE
  17. 17. TESTING WITH DEEP LEARNING § FaceForensics § Fight fire with fire § Dataset could be used to actually improve fakes
  18. 18. TECHNOLOGIES TO DETECT DEEPFAKE § Image artifacts § Blink detection § Pulse and sound detection
  19. 19. CROWDSOURCING DEFENSE AGAINST DEEPFAKE § Think critically § Examine the source § Find out if it is somewhere else online § Slow down footage/audio
  20. 20. RESULTS Progress defending against deepfake Examples of deepfake caught Research Partnership with Cornell University
  21. 21. QUESTION & ANSWER Thank you for attending! Please rate this session through the event app. #digitalxchange

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