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The more confident AI sounds, the more careful we should be. We often describe these systems as “intelligent.” But that word carries weight, as it implies understanding, judgment, even intent. Large language models don’t have those things, as they generate statistically coherent responses. They are very good at sounding authoritative, but that’s not the same as knowing what’s true or taking responsibility for outcomes. When we start treating AI like it thinks or understands, we subtly shift trust toward the machine and away from human judgment. There’s also a growing narrative that AI will remove human flaws, eliminate bias, optimise decisions, and make better calls than we can. That belief risks encouraging over-delegation in environments where accountability still sits with people. And whoever controls the tools and interfaces through which we access information inevitably shapes how we reason. Used well, AI should: • Assist, not decide • Accelerate, not replace judgment • Operate within clear governance and accountability frameworks Do you think we’re being precise enough about what AI actually is, and what it isn’t?

Half of Gen Z don't know their credit score. The instinct is to blame them, but the real problem is the scoring model. According to Zuto, almost half of 20–29-year-olds in the UK don’t even know their credit score, and more than half experience “credit score anxiety.” It’s tempting to frame this as a generational problem, but I don’t think it is. The reality is that the economic model Gen Z is entering looks very different from the one most credit systems were designed around: a world of stable, long-term employment, predictable income, long address histories, and traditional credit products that build repayment records over time. That’s what most scoring models still reward, but today’s reality (particularly for young people) looks very different. But the scoring model wasn't built for how Gen Z actually lives. Three structural mismatches stand out: 1. BNPL usage is high: If managed well, it can help build credit, but it can also damage scores quickly if repayments are missed. 2. Rent is often their largest monthly expense. And in most markets, paying it perfectly for five years counts for nothing on your credit file. 3. Many live at home longer: Meaning fewer bills in their own name to demonstrate repayment behaviour. In some markets, the issue is amplified by easy access to revolving credit. In others, like the Netherlands, credit scores are barely part of everyday financial life. So context matters. But if the way people earn, spend, and live evolves, credit models must evolve too. Otherwise, you end up misclassifying risk. There’s also a second issue: financial education. Many young adults are navigating complex credit products without ever being taught how they work, and banking apps are often more transactional than educational. Gen Z isn’t disengaged from credit. They’re just engaging with it differently. The question I keep coming back to: are we building credit models for the economy we have, or the one we used to have? Because right now, I'm not sure we know the answer.