We have become incredibly good at turning people into data.
Customers become segments. Employees become metrics. Behaviour becomes signals. People become profiles, predictions and model inputs.
Useful? Absolutely.
Neutral? Not even close.
I speak and write about the human consequences of data decisions.
The technology can work perfectly. The decision can still be terrible.
A model can be accurate.
A system can be compliant.
The implementation can work exactly as planned.
And the outcome can still be wrong.
Because technology does not remove judgement. It moves it.
Someone still decides what data matters, what gets measured, what the system should optimise for and when humans should intervene.
And which consequences are acceptable.
That is the bit I care about.
Speaking
Data. AI. Privacy. And the decisions hiding underneath all three.
I speak about what happens when organisations use data and technology to understand people, evaluate them and make decisions about them.
That means AI adoption. Governance. Privacy. Human judgement. Accountability. Data use.
Not as six different topics but as one connected problem.
My talks & workshops challenge the assumptions people stop noticing.
More data means better understanding.
Accurate AI means good AI.
Compliance means the decision is fine.
Automation removes the human problem.
They don’t.
Things I think about a lot.
Every Data Decision Is a People Decision
What gets lost when people become rows, scores, segments and model inputs.
Governance Is Supposed to Improve Decisions
If your governance programme mainly produces meetings, policies and increasingly impressive spreadsheets, we may have missed the point.
What Happens When AI Meets Human Judgement?
Successful AI adoption is not about getting people to trust the machine more.
Sometimes they should trust it less.
Privacy Is Not the Finish Line
The law matters.
It just does not make the decision for you.
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How I got here
I started at the practical end of data.
Marketing. Analytics. Digital platforms. Tracking.
All the slightly questionable stuff organisations started doing once they realised how much they could learn about people online.
Privacy came next.
Then data governance.
Then AI.
The question was rarely just:
Can we do this?
It was:
What are we actually doing, who does it affect, and what happens if we get it wrong?
Technology keeps getting smarter.
That doesn’t mean the decisions do.
More data does not guarantee more understanding.
More automation does not guarantee better judgement.
And compliance does not guarantee you made a good decision.
The interesting bit is what we do about that.