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.
Is AI Making You Smarter or Just Faster?
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Earlier this year, entrepreneur Mark Cuban posted the following on X: “There are generally two types of LLM users: those that use it to learn everything, and those that use it so they don’t have to learn anything.” As this quote suggests, AI has the potential to dramatically expand what data scientists can do. But used without care, it also has the potential to quietly erode the expertise that makes them valuable in the first place. Given my expertise took over 20 years for me to build, I’ve been thinking about this a lot lately. How can I use AI to make me better at my work, not just faster? That’s the question I keep coming back to. Tim Dietrich, a software developer with over 100 virtual AI specialists on his team, has been thinking about the same tension. In a recent blog post, he wrote about what he calls the mindful use of AI, after noticing he’d started looking for problems to solve with AI rather than reaching for it when a genuine problem arose. In this Value Boost episode, Tim joins me to explore how to stay on the right side of that line and what mindful AI use actually looks like in practice. In just 10 minutes, you’ll discover:
The goal isn’t to use AI more. It’s to use it in a way that makes you more. Listen now on Apple Podcasts or Spotify, or click the link below: Episode 108: How to Use AI Without Losing Your Edge 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.
“AI destroys jobs but creates businesses.” That one statement crystallised what I’ve long believed about building a data science career. The statement was made by best-selling author and futurist Peter H. Diamandis in a recent post. Diamandis argues that while AI will lead to the destruction of white-collar jobs, as organisations replace human workers with AI, AI has made it easier than ever for entrepreneurs to launch one-person companies. The jobs that AI creates, therefore, won’t look like...
Quick quiz: If you randomly sampled just 5 people from a population of 20,000 or more, could you use that data to tell your stakeholders anything useful? For most data scientists, the answer is probably no. But according to Douglas Hubbard, author of How to Measure Anything, “you need far less data than you think.” Here’s the proof: If you randomly sample just five people from an organisation of any size and record the lowest and highest values of whatever you’re measuring, there’s a 93.75%...
I learned the true meaning of accountability on a Sunday morning, many years ago, when I had to go into the office to fix a calculation mistake made by a member of my team. I was an insurance pricing manager at the time. My team performed premium calculations that brought in $2 billion of revenue. It was complex work, spread across multiple staff, and the margin for error was incredibly low. When my boss spotted an error in a table my team had produced, it was all I could do not to say:...