The rise of artificial intelligence (AI) has brought with it a paradox: systems designed to help achieve greater clarity are, themselves, often opaque. Built to deliver speed and insight, they can just as easily accelerate harm or error. They promise personalization at scale and, in providing such, they threaten to blur the boundary between influence and manipulation.
At root, the challenge is not simply to manage AI’s capabilities, but to govern its integration into the core functions of institutions. This moment calls for something deeper than tool adoption. It requires an architecture of trust.
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