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Artificial intelligence is shaping our future—but how we govern it will shape its impact. As the UN Global Dialogue on AI gets underway, hear from United Nations Global Advocate for Human-centric Digital Governance, Joseph Gordon-Levitt (Joseph Gordon-Levitt), on why getting AI governance right matters. Because the future of AI...

19,855 просмотров • 1 месяц назад •via X (Twitter)

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Responsible AI should not feel like the path of most resistance. That was the strongest idea from my SAS Innovate conversation with Reggie Townsend, leading Data Ethics, Governance, and Social Impact at SAS Software. Reggie framed governance not as a compliance layer, but as a way to scale human judgment. Too often, we innovate first and govern later. Model selected. Agent deployed. Process built. Then governance arrives at the end and feels like friction. Bolt it on after the fact, and resistance is guaranteed. The opportunity: design responsible AI, so it becomes intuitive, action-oriented, and useful in the flow of work. That is what Reggie meant by making responsibility "irresistible." Second point: Use cases must lead. When everyone can access the same models, differentiation will not come from the technology. It will come from how leaders define outcomes, govern applications, and connect business value to institutional trust. The risk does not live in the model. The value does not live in the model. Both live in the use case. For CEOs and boards, this is the shift: from model-first oversight to outcome-first accountability. Better questions before scaling AI: - What human decision are we shaping? - What business outcome are we improving? - What risk are we containing? - What judgment are we extending? Responsible AI becomes strategic when it helps people make better decisions, faster, with greater confidence. Most leaders can't see where governance sits inside their AI operating model. SAS AI Navigator makes it visible: Design for the human. Not only the technology.

Sabine VanderLinden

835,838 просмотров • 3 месяцев назад