The New Face of Biometrics In The Era of Hacks, Fakes, Bans, and GANs
The New Face of Biometrics In The Era of Hacks, Fakes, Bans, and GANs


Despite expanding regulations, surveillance tech and Face ID deployments continue to grow geometrically. Countries such as the US, China, and the UK are leading the way, while the rest of the world is not far behind. Biometric data and algorithms are at the epicenter of a perfect storm, as rapid technological advances meet rising privacy concerns. At the one end, identification technology like face recognition can provide consumers both convenience and secure authentication. At the other end, biometric databases and infrastructure have become attractive targets for hackers. In a new twist, open source AI tools are now available that can help malicious actors manipulate face and voice data to create deep fakes. These fakes can be weaponized by rogue nation states for disinformation campaigns - to destabilize financial markets or manipulate elections.

Our panel will take a data-centric perspective on these topics. We will review the state of the art in face recognition technology and discuss where biometrics is headed. We will look at novel ways to secure biometric data, such as homomorphic encryption and leveraging the blockchain. And we will explore the role that deep learning is playing in both improving identification accuracy as well in fake news and cybersecurity.


Michael Gormish is Head of Research at Clarifai. His team works on bringing image and language understanding to Clarifai's platform. Recent projects have invovled custom face recognition, object detection, tracking, visual search, and image classification. Previously he was responsible for two search engines which connected images from mobile phones to AR experiences. Work at Ricoh included considerations of document and image authenticity including precursors to blockchain technologies. His research as a computer vision scientist included inventing algorithms used in video games, digital cinema, satellite and medical image acquisition. He led several aspects of the JPEG 2000 standardization and provided key inventions used in photocopiers, digital cameras, tablets and imaging services. Michael was named Ricoh Patent Master for being a co-inventor of over 100 US patents. He earned a PhD degree in Electrical Engineering dealing with image and data compression from Stanford University and has served the research community as an Associate Editor of the IEEE Signal Processing Magazine, and the Journal of Electronic Imaging. Currently he is interested changing the world via image understanding.

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