Age assurance
French regulator Arcom introduces age checks for online adult content
In October 2024, Arcom, the French regulator responsible for online porn, announced that adult operators and platforms with pornographic content need to introduce age checks, ensuring only adults can access the content. These rules are effective from 11th January 2025. There will be a three month transitional period, where temporary methods like bank card verification can be used as a preliminary age filter, but they must include strong authentication to ensure that the user is the cardholder. After the transitional period ends on 11 April 2025, adult site operators will need to have taken the following steps: Age checks
Understanding age assurance in the Online Safety Act
The Online Safety Act 2023 is a piece of UK legislation that aims to protect children and adults online. It covers a wide range of issues including minimising the risk of children seeing harmful and age-inappropriate content, removing illegal content like child sexual abuse material (CSAM), criminalising fraudulent and scam ads, and introducing age verification for certain online services. This blog looks at some of the age requirements in the Online Safety Act and what this means for tech companies, adult sites, gaming companies, social media platforms and dating sites. What is the purpose of the Online Safety
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’
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
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
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