Articles
Articles
Oct 01, 2024
How accurate is facial age estimation?
“How accurate is it?” is the first question regulators, businesses and users tend to ask about facial age estimation. To date, we have mainly presented the technology’s Mean Absolute Error (MAE) as a proxy for accuracy. It’s an intuitive way to understand how accurate a model is. We can say it’s accurate to 1.3 MAE for those aged between 13 and 17 years or 2.5 MAE for those aged between 6 and 70 years. However, the answer is slightly more complicated. Following the COVID-19 pandemic, many people will be more aware of the terms ‘true positive’ and ‘false negative’
Articles
Sep 27, 2024
Thoughts from our CEO
In this blog series, our CEO Robin Tombs will be sharing his experience, whilst focusing on major themes, news and issues in the world of identity verification and age assurance. This month, Robin chats about the popularity of digital right to work checks, the new Teen Accounts on Instagram, why facial age estimation is effective for children, intimate image abuse and responds to another misleading Crikey article. 34% of people choose Digital ID to prove their identity for DBS checks Since June 2022, Yoti has completed over 1.6 million right to work (RTW) checks and over 0.93 million
Articles
Sep 25, 2024
Understanding the Kids Online Safety and Privacy Act (KOSPA)
From the UK’s Online Safety Act to Europe’s Digital Services Act, we’re in an era of increasing online safety regulation. In the US, the Kids Online Safety and Privacy Act (KOSPA) is a landmark piece of legislation, passed in the Senate on 30th July 2024. KOSPA is a legislative package that merges two bills – the Kids Online Safety Act and the Children’s and Teens Online Privacy Protection Act (also known as COPPA 2.0). This blog looks at some of the requirements of KOSPA and what this means for companies. What is the purpose of KOSPA? KOSPA is the
Articles
Sep 24, 2024
How Yoti’s facial age estimation is used across different industries
Checking users’ ages has never been more critical for businesses catering to diverse audiences. However, they’re faced with the challenge of effectively verifying the ages of their users whilst maintaining seamless and user-friendly experiences. Yoti’s facial age estimation is a secure, privacy-preserving way to do just that. Our technology is used across a variety of industries, both online and in-person. This includes retail, social media, dating, gaming, gambling and financial services. In this blog, we explore how businesses are using facial age estimation to create safer, more positive experiences for their users. What is facial age estimation? Facial
Articles
Sep 17, 2024
Helping Instagram to create safer online experiences with new Teen Accounts
From today, Meta is introducing new ‘Teen Accounts’ on Instagram for users under the age of 18. This change aims to help parents keep their teens safe online, by including features that have built-in protections. These include the ability to set daily usage limits, restrict access during certain hours and monitor their child’s interactions, such as the accounts they are messaging and the types of content they’re engaging with on the platform. New users under the age of 18 are, by default, given the strictest privacy settings. Under the new guidelines, teens aged between 16 and 18 will be
Articles
Sep 11, 2024
Why Yoti’s facial age estimation is not facial recognition
There’s quite a bit of confusion about the differences between facial age estimation and facial recognition. While both types of technology work with images of faces, they’re used for different reasons and are trained in different ways. To help clear up some of these misconceptions, we’ve explained some of the key ways that our facial age estimation is not facial recognition. Facial age estimation vs. facial recognition: designed to give two different outcomes. Facial age estimation delivers an estimated age result. Facial recognition delivers a match (or no match) between images of a person. [vc_column_text