Industries from education to retail to transportation must increasingly rely on automated age verification systems to comply with policy and product performance demands. Creating automated age verification systems with high performance and minimal privacy or misidentification risks is a technological challenge for experts in artificial intelligence.
During this webinar, you will hear from two experts in the field of facial analysis address the performance and policy demands of age verification and discuss what they anticipate for the future of this technology.
- Facial Age Analysis Explained in Plain English, by Julie Dawson, Director of Regulatory & Policy, Yoti. (slides)
- Improving the performance of age verification algorithms and facial analysis by Dr. Karl Ricanek, Professor of Computer Science at University of North Carolina at Wilmington. (slides)
- Risk and policy solutions in facial analysis. Hodan Omaar, Policy Analyst, Information Technology and Innovation Foundation. (slides)
This webinar is part of our Applied Privacy Research Collaboration Network. This project was funded by the National Science Foundation to facilitate dialogue between the academic community and industry on topics related to data protection and privacy.