Removing bias within facial biometric algorithms with more diverse data
Type of service
Unissey is an innovative startup based in Paris, providing solutions in the field of identity confirmation by facial biometrics, allowing users to access daily services via facial recognition in a matter of seconds. Their solution is based on liveness detection and facial recognition algorithms to ensure the true identity of the user while preventing identity theft. With a team of more than 20 experts in the field, they have created an intuitive, secure, and accessible experience to access the digital world. Unissey focuses on critical issues such as the fight against biometric discrimination, data protection, and the fluidity of the customer experience.
The issue of conscious or unconscious bias is often brought up when considering facial biometric algorithms – a big reason for this being the lack of dataset diversity. The focus was to ensure the creation of an unbiased algorithm that would not be created in a controlled environment, but rather to have data similar to that of the end customers – with all the challenges it encompasses – diversity of acquisition devices, variety of luminosity, environment, and others.
The main challenges revolved around:
1) outsourcing the task to a partner who could deal responsibly with personal and sensitive data
2) to create the most diverse and representative dataset possible – gathering participants from a wide range of ethnicity, geography, religion, age, and gender.
Image of Unissey’s solution in action
A real differentiator with HITL is that whatever field you may be working in, you can be confident collaborating on your project as they will know how to adapt.
Sophie Finet, Product Manager
Unissey recognised Humans in the Loop as the right partner for 3 main reasons:
1) the expertise in data acquisition on a global scale thanks to their international outreach
“One of Humans in the Loop’s strength was to have data samples from all around the world, which was crucial for the development of our solution – our need for a diverse dataset offering a broad spectrum of faces and video acquisition conditions was met, with each obstacle paired with a quick and thorough solution – from finding sources, to managing data protection requirements”
2) the annotation expertise demonstrated and a strong ethical and committed approach to the end application
The flexibile approach to adapt to Unissey’s in-house annotation platform allowed Unissey to work more efficiently by reviewing annotations and validating the output quality. The smooth, responsive communication maintained throughout ensured success to a global process.
3) The ability to comply fully with GDPR regulations along with a transparent, responsible work flow
“We found ourselves on the same page on this subject – we saw a real commitment to the fight against bias which resonated with the one we lead against biometric bias. HITL did a great job explaining the purpose of the collection and its boundaries, as such we were confident that explicit and freely given consent had been obtained during the data collection process”
A partnership formed in the span of a year thanks to the ability to continuously generate data and provide a high standard of consistent annotation ouput. Initial scope targeted predominantly the collection of data from various types of devices (mobile and desktop) along with a variety of background/environment (indoor, outdoor). This later expanded to include data collected from various geographic regions, age categories, and gender.
Unissey and Humans in the Loop have since worked together on three separate projects, achieving a milestone of over 26,000 seconds of video footage and 22,400 different annotations done, with data collected from over five continents, pushing forward the mission of having an unbiased and representative facial biometric system.