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 Terminator, The Big Short or Neither?
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After the latest wave of headlines about the pending AI apocalypse, I spent an afternoon trying to work out whether I should panic. I watched videos explaining how AI could destroy us all, and others arguing that AI is a scam that will collapse the economy once everyone realises. It felt a lot like watching The Terminator and The Big Short back to back. Both of these scenarios can't simultaneously be true, and after hearing them out, I don't think either is. AI's value has already been proven across multiple use cases, so it's certainly not a scam. And the doom scenarios typically rest on a chain of assumptions I don't find convincing. But the exercise got me thinking about a third possibility that gets far less airtime. What if AI isn't a scam, but under-delivers nonetheless? Ten years ago, data science was seen as the magic bullet that would solve every problem. Then came the headlines: We are already seeing these same headlines again, just with "AI" replacing "data science": Last time, the technology wasn't the problem. Rather, organisations and data scientists alike prioritised the technology (machine learning, in that case) ahead of the business problem it was meant to solve. My fear is we're doing it again. The good news is that because we've already seen this film before, we know how to avoid the worst of it: understand the business problems at hand and let it drive the choice of technology. Fail to do that, and the result won't be dramatic. It will just be a lot of money spent with not much to show for it. 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.
Suppose you asked AI to design an engine that pulls static electricity from the atmosphere so the engine can run without any other fuel, whatsoever. It would certainly give you a result and that result would sound very convincing. In fact, it might read like a mash-up of your high school physics text and the plots from various science fiction stories - because that’s exactly what it would be. Designing such an engine would literally involve creating a new branch of physics and AI can’t create...
Last month, Anthropic CEO Dario Amodei published an essay calling for stronger AI regulation and a slower pace of AI development. Since then, two incidents have made his case for him. In the first, the US military almost started a war based on the contents of a confidently wrong AI-generated intelligence report. In the second, OpenAI disclosed that its agent hacked into Australia's Medicare website during training and accessed data that, although not sensitive, had yet to be publicly...
I once met a data scientist who was so good at his job that he automated his way out of it. He systematically built automations to handle his team’s work and once those automations were in place, the team no longer needed as many people. So, his role was ultimately made redundant. He’d built those automations because he believed they’d create business value for his employer - and they did. The problem was that the value ended up residing in the code, not in him. And because his employer owned...