IEEE Queensland Section

Although AI is solving real-world challenges and transforming industries, there are serious concerns about its ability to behave and make decisions in a safe responsible way. To address the responsible AI (RAI) challenges, a number of RAI principles frameworks have been published recently, which AI systems are supposed to conform to. However, without further best practice guidance, practitioners are left with nothing much beyond truisms. In addition, significant efforts have been put on model-level solutions which mainly focus on a subset of mathematics-amenable RAI principles (such as privacy and fairness). However, issues can occur at any step of the development lifecycle crosscutting AI, non-AI and data components of systems beyond AI models. To close the gap in operationalising responsible AI and make the adoption of AI safe and responsible AI, in this talk, we will introduce an end to end responsible AI engineering approach including best practices, methods and tools.Speaker(s): , QinghuaVirtual: https://events.vtools.ieee.org/m/417183