Collect Quick 2-second Video Selfies for $75 (Caucasian and Latin American ONLY) -- 2

We are looking for people from European, American and Latin American descent who can work as “video selfie collectors” for our project. The task of each collector would be to reach out to friends and family and to have 50 unique people record a 2-second video selfie on our app (Webcam or Mobile phones). When you complete 50 unique faces, you will be paid $75. This project is for a startup that aims to detect identity fraud attempts, developing a software that detects fraudsters who would try to open bank accounts by showing somebody else’s picture for verification. Each collector would receive a unique link that they will have to send to their friends and family. The link to the camera tool is secure and connected to our cloud database. The videos collected will be protected from loss, theft, and misuse as well as unauthorized access, disclosure, alteration or destruction. Please note that we, and none of our representatives would ask for personal information like name, email or contact details of people in the video selfies. We simply need as many and as diverse facial samples we could gather, in order to train our liveness detection solution which will be used to detect a spoof attempt (a fraudster trying to impersonate another person) by determining whether the source of a biometric sample is a live human being or a fake representation (photo, mask, etc.). The video goes into our private cloud hosted in Europe and will only be used for R&D purposes. The User’s personal data processed by our client for detecting facial liveness and identifying and authenticating the User are stored during the necessary period to enable our client to populate, train and improve its facial recognition and facial aliveness detection algorithms. After which, such data is deleted. We respect high standards in terms of data security and data privacy. Your videos won't be sold or shown to anyone outside our organization. They are only used to train and test our models on real-life data. Your contribution to the project will help a great deal in building a robust solution to identity fraud!