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The debate about whether AI will replace human workers has already been settled - not by academics or futurists, but by the organisations that fired their humans, discovered AI couldn't do what they needed, and quietly hired them back. The future isn't AI replacing humans. It's humans and AI working together in ways that neither could manage alone.
In this episode, Vict...
AI hallucinations get all the attention. But hallucinations are relatively easy to catch because the output is obviously wrong. The failure mode that should worry data scientists more is when the agent uses facts that are true to draw conclusions that are false, producing outputs that look perfectly fine. This is known as silent correctness.
In this Value Boost episode,...
The shift to agentic AI doesn't make data science skills obsolete. But it does require data scientists to rewire how they think about familiar concepts, such as uncertainty, model evaluation and accountability, in their work.
In this episode, Jia Huang joins Dr Genevieve Hayes to explore what that rewiring actually looks like, and why data scientists are better placed t...
A well-written blog post gets you noticed. But for data scientists who want to build authority that compounds over time, it's just the beginning. Every piece of writing is a potential stepping stone to something bigger - a conference talk, a book deal, or an opportunity you couldn't have anticipated.
In this Value Boost episode, Cynthia Dunlop joins Dr Genevieve Hayes t...
For data scientists who want to build authority beyond their organisation, writing is one of the most powerful tools available. But in a world flooded with AI-generated content, simply publishing is no longer enough. The data scientists who stand out are the ones writing things no AI could have written.
In this episode, Cynthia Dunlop joins Dr Genevieve Hayes to share p...