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A year ago, if you’d asked me what would most renew my love of building software, I’d probably have given you a sensible answer: a cleaner architecture, a calmer backlog, a client who values craft as much as outcomes. I wouldn’t have said: pair-programming with a tireless, occasionally overconfident, astonishingly useful set of coding agents. And yet — here we are.
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When we think about Live Facial Recognition (LFR) technology, we often focus on its potential — enhancing public safety, streamlining law enforcement operations, and locating vulnerable individuals. But as with any tool of power, trust is the critical factor. Without trust, even the most advanced systems can undermine the very safety and equity they claim to protect.
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You’ve implemented Scrum, you’ve got you your sprints set up, you have a backlog, you have a scrum master, you have 15 extra hours of meetings, and…. You still have very little confidence your team will deliver…. or even struggle to know what they’re doing?“We’re sort of Agile…” means you’re probably not. I wish my customers would stop saying it. Implementing a framework without the foundation is akin to building a bridge... that no-one knows how to use.
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A friend and former colleague of mine recently brought to my attention the BBC’s coverage of Live Facial Recognition (LFR) technology being piloted in Hampshire. It stood out to me as its particularly close to home (well... it is my home, I live in Hampshire). This trial has sparked renewed conversations about privacy, surveillance, and trust — areas that deeply concern me, especially in the context of AI ethics.
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The concept of identity has always been central to human society. Traditionally, identity tracking began with simple records such as birth and death certificates.
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As artificial intelligence (AI) continues to evolve and integrate into various facets of our lives, the key to maximizing its potential lies in how we harness it to assist and enhance human capabilities rather than replace them. This approach not only aligns with preserving the intrinsic value of human thought but also paves the way for more reliable, consistent, and accurate outputs in various domains.
