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AI Trade Offs: A Systems Lens on Decision-Making
Every AI deployment involves a trade-off; the question is whether decision-makers can see it. Maps seven real-world scenarios against the UN Sustainable Development Goals to argue for AI literacy and stakeholder engagement as core governance tools.
Why it matters: No AI deployment is a free win — every productivity gain has a cost somewhere in the system, and most governance conversations only look at one side of the ledger. I contributed to this piece, led by Dr. Melodena Stephens, because it's the conversation policymakers most need to have and least often do.
Key takeaways:
AI systems have to be evaluated as full systems — hardware, software, data, and the humans operating them — not just the model in isolation.
Maps seven real-world decision-making scenarios against the UN Sustainable Development Goals to make trade-offs, like productivity gains against job displacement, concrete rather than abstract.
Responsible governance depends on AI literacy for policymakers and the public, plus structured stakeholder engagement — not just technical fixes.
Published: Policy Paper · The Digital Economist · November 21, 2025
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