HI, I’M Colette AND BIT OF A NERD

THE SHORT VERSION

First computer at 12, a ZX81 plugged into the family telly. Ever since, I’ve worked in tech for investment banks, several UK government departments, London Underground, the Metropolitan Police. Every one of those jobs put me in the same spot: where people, technology, and data collide, and someone has to work out why the collision keeps going wrong.

For six years, my whole job boiled down to one habit: running desk-side tests, watching someone normal use a system, then working out why it let them down even when it matched the requirements document perfectly on paper. The system was fine. The data behind it was fine. The person using it, tired, rushed, not reading the manual, was where it actually broke.

That’s the question I’ve been asking for forty years, just pointed at different technology each decade. Now it’s AI’s turn.

AI is the area where humans, machines, and data overlap more than any technology before it. Not just using a tool. Handing it judgement calls, personal information, and decisions that used to need a person in the loop. That overlap is exactly where I’ve spent my career, so I have opinions, and receipts.

Since 2022, I’ve been working specifically with AI. Not because I think it changes everything, I’ve lived through enough technology cycles to know that’s almost never true. But because it changes some things significantly, and most people are getting terrible advice about which things those are.

As well as being nerdy, I like to help people understand the wider issues we all face with AI. I am a member of the National Association of Press Agencies (NAPA) and a contributing journalist for Newspage Media, covering AI adoption and ethics, the impact of big tech, and small business economics for the UK national, regional and trade press. 

WHAT I ACTUALLY THINK ABOUT AI

I’m not an AI evangelist. I’m not an AI doomer. I’m the person in the room asking “yes, but does it actually work, for the human and the data involved, not just on the slide?” Simple question. Harder to answer once you factor in the personal, professional, economic, and social angles all at once, which is most of the time.

Some of what AI can do is extraordinary. Accessibility tools that genuinely change lives. Research that saves hours of real drudgery. Writing partners that help you think, not just produce words.

Some of it is appalling. Copyright theft dressed as innovation. Personal data handled by systems nobody properly audited. Environmental costs nobody wants to talk about. Confident nonsense presented as expertise, from an entire industry of people selling AI courses who’ve never built a system that had to survive contact with reality, or real human data, or real consequences for getting it wrong.

I’m interested in the space between those two things. Where people, the tech, and the data they generate together actually meet, the practical, honest, sometimes uncomfortable middle ground where most of society lives and works.

The Truth About AI (That Nobody Else Will Tell You)

There is a lot of BS out there and it annoys me. Things like this…

Template prompts? Break the moment your situation, or your data, isn’t identical to their toy example.

“Set it and forget it” automation? Goes spectacularly wrong when you least expect it, usually at the worst possible moment, often because nobody checked what data it was actually working from.

Generic AI advice? Written by marketers who’ve never had to explain to a real person why the system used their information the way it did.

Most AI consultants? Discovered ChatGPT last year, immediately started selling courses to people who know more about running businesses, and handling their clients’ data responsibly, than they do.

“AI will fix everything” thinking? Ignores who actually pays the price when it doesn’t, the person whose data leaked, the worker quietly replaced, the community whose water and electricity went to a data centre instead of them.

“Neutral technology” framing? A convenient excuse. The choices about whose data trains it, whose job it threatens, and who’s accountable when it’s wrong are made by people, not the algorithm.

I don’t sugar-coat tech problems. I explain them warts and all. Just like I have for years. And where I can, I put forward solutions.

What Keeps Me Energised After All These Years

Curiosity. I’m still that 12-year-old figuring out how things work, just with better tools and much higher stakes for getting it wrong.

I’m endlessly fascinated by systems, musical, mechanical, human, digital, and what happens where they meet real people and real information. Whether it’s why a guitar riff hits differently live than on record (172 gigs in 2025, a personal best), finding the most scenic route through the Scottish Highlands in Snowball (my campervan), or helping someone build an AI system that actually thinks with them and respects what it’s been handed, instead of quietly working against both.

This curiosity drives my standards: if I don’t understand how something works, including what data it touches and why, how can I make it work better? If I can’t explain why a solution will hold up under pressure, why would I recommend it?

Same Standards Everywhere

No tolerance for BS that wastes people’s time, energy, money, or trust.

I don’t promise magical transformations. I deliver AI systems that work when you need them most, and handle the people and data behind them properly, built to the same standards I applied to systems where lives depended on getting it right.

I don’t indulge pointless AI trends or jump on bandwagons. I focus on what actually works for real businesses, run by real humans, dealing with real data, under real pressure.

If you value quality, curiosity, and honest answers over flashy promises, we’re probably kindred spirits.

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