Navigating the Responsible Adoption of Equitable AI: Forging an Alternative Selection Framework

Artificial intelligence (AI) has accelerated the speed of pattern recognition algorithm development. As a result, there has been a rapid increase in the number of AI companies providing object recognition, biometrics, optical character recognition and video analytics algorithms to the marketplace and an explosion in the number of algorithm options for a wide range of AI-empowered capabilities.

While AI has accelerated progress in the field of biometric algorithm development, it has also created new challenges for technology developers and end-user organizations to overcome. One challenge in particular, is algorithm bias. The impact of this bias places an undue burden placed on the individual to overcome the challenges caused by failures in the AI-enabled technology. This session will introduce a qualification framework that extends beyond technical considerations to support your organization's selection of identification and biometric technologies.