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You have twenty frameworks to comply with, two hundred use cases to govern, and a control checklist a thousand questions long for each. Multiply it out and you get millions of boxes. Tick them all and you still are not governed - you are just very busy. Governance that grows faster than the AI does not scale, and most of what passes for AI governance today is exactly that.
This short book compiles some thoughts on three moves that collapse twenty frameworks and hundreds of use cases into one backbone you can actually manage - and scale.
Govern to a common spine. Strip the packaging off twenty frameworks and they ask the same questions. Build one backbone and twenty columns collapse to one.
Govern with the unit that scales. "What are the use cases?" is the wrong first question - a use case is the least scalable thing to govern. Underneath sit units that repeat. Govern those once and every use case inherits.
Govern as a system, not a checklist. A thousand-question checklist passed box by box still fails, because the boxes do not talk to each other.
Some ideas on how to keep control of AI as the number of systems climbs - in a firm, a regulator, or a team of one - without a pricey consultant and without drowning in boxes. It is deliberately boring, because the parts that last usually are. I wrote Singapore's first AI risk management guidelines for the financial sector, and much of this is what I wish I could have said in the margins of them.
You get the PDF to download and keep.
You have twenty frameworks to comply with, two hundred use cases to govern, and a control checklist a thousand questions long for each. Multiply it out and you get millions of boxes. Tick them all and you still are not governed - you are just very busy. Governance that grows faster than the AI does not scale, and most of what passes for AI governance today is exactly that.
This short book compiles some thoughts on three moves that collapse twenty frameworks and hundreds of use cases into one backbone you can actually manage - and scale.
Govern to a common spine. Strip the packaging off twenty frameworks and they ask the same questions. Build one backbone and twenty columns collapse to one.
Govern with the unit that scales. "What are the use cases?" is the wrong first question - a use case is the least scalable thing to govern. Underneath sit units that repeat. Govern those once and every use case inherits.
Govern as a system, not a checklist. A thousand-question checklist passed box by box still fails, because the boxes do not talk to each other.
Some ideas on how to keep control of AI as the number of systems climbs - in a firm, a regulator, or a team of one - without a pricey consultant and without drowning in boxes. It is deliberately boring, because the parts that last usually are. I wrote Singapore's first AI risk management guidelines for the financial sector, and much of this is what I wish I could have said in the margins of them.
You get the PDF to download and keep.