Age assurance is becoming an essential component of creating safer digital experiences—but misconceptions about facial age estimation continue to shape public perception. Many people mistakenly associate it with facial recognition, raising concerns about privacy, surveillance, and data collection.

In this episode of Trust Talks & Digital Dives, we sit down with Yoti’s Julie Dawson, Chief Regulatory & Policy Officer, and Jason Martyres, Product Engineer, to separate fact from fiction surrounding facial age estimation. Together, they explain how the technology works, why it does not identify individuals or store personal data, and how it enables organizations to verify age while protecting user privacy.

From accuracy and fairness to regulation and the future of reusable age assurance, this conversation explores how facial age estimation is helping organizations build trusted, privacy-preserving digital experiences.

Featured Guests

Moderator

Key Discussion Topics & Questions

  1. What is facial age estimation, and how does it differ from facial recognition?
  2. Why is facial age estimation often misunderstood, and what are some of the biggest myths surrounding the technology?
  3. How is facial age estimation built, and how does it protect user privacy without storing personal information or relying on a central database?
  4. How accurate is facial age estimation, and what do independent benchmarks, such as those conducted by NIST, tell us about its performance?
  5. How has Yoti worked to ensure facial age estimation is inclusive, fair, and trusted by consumers?
  6. How have regulators in jurisdictions such as the UK, Germany, and Australia evaluated facial age estimation?
  7. What are age buffers, and how can organizations determine the right approach for their age assurance needs?
  8. How could reusable age assurance through digital wallets, tokens, and passkeys shape the future of digital identity?

References & Resources

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