AI, Job Seeking, and Machine Bias with Kendra Vant

On this episode of AI Australia, we're excited to be speaking with Kendra Vant. Kendra is currently the principal data scientist at SEEK, and has had an extensive and diverse career in AI/ML and data science (among other things) across insurance, banking, telecommunications, government, gaming, the airline industry, and the job board market. With SEEK being one of the leading Australian companies in the field of AI, Kendra really is someone to pay attention to as the AI landscape unfolds. We're honoured to have had the opportunity to speak with her about the past, present, and future of AI for the Australian technology community. We discuss a wide range of topics, including: What is involved in Kendra's role as principal data scientist at SEEK Some of the results Kendra and her team have seen by applying AI to their job search functions How Kendra got into the world of data science and software engineering The role of ethics in AI, and how it plays into the work Kendra is doing with her team at SEEK Some of the issues with bias in the hiring process, and where Kendra sees the main opportunities are for removing bias using AI and ML The importance of keeping humans in the loop when it comes to AI initiatives. This helps humans keep machine bias at bay, and vice versa How SEEK goes about finding tried and true machine learning algorithms, implementing them, and scaling them. Rather than being the research and development ground for new algorithms, they are more focused on making tested algorithms scale better Kendra's rule of thumb for data scientists and engineers working together - how many engineers per data scientist, what kind of engineers, etc. How Kendra views the state of data science and machine learning adoption and usage. There's a lot of hype, and Kendra helps us cut through a lot of that in explaining what's really going on in the Australian business community Kendra's thoughts and concerns on the National Health Record The best communities and conferences to be involved with as a data scientist or AI/ML enthusiast  

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