Twice weekly, I share proven strategies to help data scientists get noticed, promoted, and valued. No theory — just practical steps to transform your technical expertise into business impact and the freedom to call your own shots.
Your Model Is Making a Caricature of Your Data
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Biased machine learning models don’t just produce poor predictions. They damage reputations, derail projects, and in high-stakes fields like healthcare, they can potentially cause real harm. Yet most data scientists don’t check for bias until it’s too late - missing the opportunity to address it at its source. Serg Masis, author of Interpretable Machine Learning with Python, puts it bluntly: “Models magnify bias just simply by the way they are. It’s like when you make a caricature of someone - you’re gonna enhance some features that are not necessarily flattering. It’s the same thing with models.” Your training data has bias. Your model amplifies it. By the time you’re making predictions, the problem is much worse. In this week’s Value Boost episode of Value Driven Data Science, Serg joins me again to share practical techniques for detecting and mitigating bias before it becomes a major problem. In just 10 minutes, you’ll discover:
Don’t let model bias make a caricature of your data. Listen now on Apple Podcasts or Spotify, or click the link below: Episode 99: Preventing ML Bias Before it Becomes a Problem Talk again soon, Dr Genevieve Hayes |
Data Science Impact Algorithm
Twice weekly, I share proven strategies to help data scientists get noticed, promoted, and valued. No theory — just practical steps to transform your technical expertise into business impact and the freedom to call your own shots.
When I started my career, data science didn’t exist as a field. I trained as an actuary and statistician and those were the tools I relied on in my earliest roles. Then, around 10 years ago, I started hearing about the wonders of machine learning and became worried that my traditional training was no longer enough. So, despite already having a PhD in Statistics, I went back and completed a Masters in Machine Learning. Then came the AI wave – ChatGPT, large language models, generative AI – and...
The most valuable lessons I’ve learned in my data science career weren’t learned in a classroom. They came from conversations with people who’d already figured things out the hard way. My podcast has been a more valuable learning tool for me than all of my university degrees combined. Over 100 episodes, I’ve had the chance to speak one-on-one with some of the sharpest minds in the industry - CEOs, best-selling authors and leading researchers - on everything from cutting-edge AI to what it...
In 2015, I fell in love with a job I would never have. I’d just attended a conference where people were talking about machine learning and data science as the way of the future. I returned to the office eager to learn more and started down the data science rabbit hole - where I stumbled across an article about the recently established NYC Mayor’s Office for Data Analytics. They were using data science to locate illegal cooking oil dumping in the city’s sewers. To coordinate emergency services...