Positive Excellence Mo's Wayfinding Kiosk

The position

Responsible AI, or none at all.

The technology is arriving faster than the rules that should govern it. My work is to close that gap.

Only when AI is used responsibly and held to unchallengeable standards will our children, and their children, feel safe in a place they can call home. The standard I work to

I did not arrive at this from policy. I arrived at it from twenty years of building systems in banking, retail, international development and healthcare — industries where a wrong answer has a name and an address attached to it.

What I see now is a familiar pattern moving faster than it ever has. Capability ships. Governance follows, eventually, usually after something breaks. With machine learning the gap between those two moments is wider than anything I have worked through before, and the consequences land on people who never agreed to the experiment.

So I teach. I speak. And I argue, wherever it will be heard, that responsible use of AI has to be enforceable rather than aspirational — that the standards should be ones a company cannot quietly opt out of when they become inconvenient.


What I argue for

Three commitments

Literacy before adoption

An organisation that cannot explain what its model does has not adopted AI — it has outsourced a decision. I teach the explanation first.

Standards that cannot be waived

Voluntary principles fail at exactly the moment they matter. Responsible AI needs rules with consequences attached.

Regulation written with builders in the room

Rules drafted without engineers are unenforceable; rules drafted only by engineers are unaccountable. Both parties have to sit at the table.

On stage

What I speak about

I am a frequent guest speaker at trade conferences and deliver top-to-bottom workshop training to attendees — not a keynote that leaves the room impressed and unequipped.

Responsible AI in regulated industries

What changes when a model’s output touches a patient, a claim, or a credit decision.

Prompt engineering and vibe coding

A working session, not a lecture. Delivered most recently at IEOM Orlando.

Machine learning, deep learning and generative AI

The foundations, pitched at leaders who have to fund the work without being able to review the code.

Harnessing AI for holistic healthcare

The keynote delivered at the IEOM World Congress, Lawrence Tech University.

Invite me to speak.

Conferences, universities, and internal leadership programmes. Tell me the audience and how long you have, and I will tell you honestly whether I am the right person for it.

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