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?
|
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.
The number one piece of advice I give to data professionals is to have more conversations. Conversations lead to good things. Things like job offers and stronger relationships. But more importantly, the opportunity to deepen your knowledge through learning from the wisdom of others. I owe many of the best opportunities I’ve encountered in my career to proactively seeking them out wherever I can. My podcast is a weekly example of the power of conversation. But if there’s one thing all these...
While working as a data scientist in a large organisation, I was once called on to attend a meeting with representatives of a big tech company and multiple senior leaders from my business area. The tech reps were there to sell us a new product. The data scientists had been invited because we were the intended users. Although there were a dozen or more people in the room, I was the only person who came prepared with any questions - 2 1/2 pages of them, to be precise. I let everyone else have...
Like many readers of this newsletter, I identify as a data expert. It took me years of study and hard work to build this expertise, and it’s something that I’m not willing to lose. This is not just because of everything it took to get here, but because my expertise forms an integral part of my identity. And the idea of losing it feels, in many ways, akin to losing a part of who I am. So, when I recently started hearing from data professionals who spoke of slowly losing skills as they...