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...
7 days ago • 1 min read
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...
11 days ago • 1 min read
If you read the news or follow just about any of the tech bosses on social media, you could be forgiven for thinking that all knowledge workers will become unemployed sometime between now and next Christmas. For example, Microsoft's AI CEO Mustafa Suleyman recently warned that most tasks in white-collar fields will be fully automated by AI within the next 12-18 months. And Anthropic's CEO Dario Amodei spent most of last year predicting AI could eliminate up to 50% of all entry-level...
14 days ago • 1 min read
I once freaked out a room full of executives with a table showing insurance premium increases. One or two of the increases were massive. Think 78% or 92%. I remember the CFO seeing it and immediately exclaiming: “This is terrible. We’ve got clients getting a 78% increase in premium?! We can’t approve these.” What it actually translated to was a really low base. The clients in question had taken on their policies late in the year, so had a part-year premium for the previous year but a...
18 days ago • 1 min read
I had to see an ophthalmologist recently. Before I went in, I was pretty sure I knew what was wrong. I'd had what I believed to be a similar issue years earlier. I was half-expecting to walk in, describe my symptoms and walk out again with a prescription for antibiotics. That's not what happened at all. Instead, the specialist listened to my self-diagnosis - then ran me through his formal diagnostic process, anyway. He systematically worked through all the possible causes, before announcing...
21 days ago • 1 min read
Recently, I’ve been approached on more than one occasion by consulting clients asking me to review statistical methodologies developed with AI assistance. In all cases, my clients came from non-technical backgrounds. And what they’ve managed to produce is impressive: detailed statistical specifications that would otherwise have required years of study to develop. Their work is living proof of just how far AI has come. But on reviewing the work, one thing I invariably notice is that while on...
25 days ago • 1 min read
“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...
28 days ago • 1 min read
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%...
about 1 month ago • 1 min read
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:...
about 1 month ago • 1 min read