IEEE Queensland Section

Co-sponsored by: Feifei BaiVirtual: https://events.vtools.ieee.org/m/416642

Dear IEEE Queensland Section members,The nomination period for the upcoming Griffith University IEEE Power & Energy Society (PES) Student Branch Committee (2024-2025) elections is now officially open. This is a formal call for nominations for the pivotal executive committee positions:- Chair- Vice Chair- Secretary- Treasurer- Web MasterThe success and efficacy of our committee rest heavily upon the dedicated service of individuals who fill these roles. We invite you to participate actively in shaping the future of our community by nominating suitable candidates.Nomination Period: to Kindly submit nominations via email to our Election Chair, Dr Feifei Bai at with the following details:- Full Name of Nominee- Desired Position- A Brief Bio of the Nominee (if available)- Contact Information of the NomineeEligibility Criteria:- Nominees must be registered members of the IEEE PES and currently working or studing at Griffith University.- Nominees should exhibit a palpable commitment to the furtherance of our society.Your active participation in the nomination process is crucial for forming a steadfast executive team that will sustain and enhance the prosperity and functionalities provided by the GU IEEE PES SBC.Best regardsYue QuGriffith University, Brisbane 4111, Australia, Brisbane, Queensland, Australia, 4111

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