A couple of months ago, I sat across from my nine-year-old daughter’s teachers at a parent-teacher conference. They were kind but concerned. She takes her time on assignments, they said—often deep in thought. How would she do on timed tests next year? I told them I wasn’t worried. What they described as a problem is, to me, one of the most important things she can learn: the ability to take a hard problem and reason through it from beginning to end. In a world optimized for efficiency, qualities like patience, perseverance, and attention to detail are not deficiencies. They are the foundation of sound judgment, which will become the skills we need most. The more time I spend working with AI, the more convinced I become: the question that matters for her future isn’t how quickly she can answer. It’s whether she has the judgment to know when an answer can be trusted. I’ve spent decades at Microsoft watching this tension play out: first building tools for other developers, then working across AI as models moved from research curiosities to systems deployed at scale. Now we’re building Microsoft IQ, where we’re exploring how an organization’s collective intelligence can become its greatest advantage. Through every one of those chapters, one thing has remained true: it’s never enough for a system to be powerful, it must also be trustworthy. Trust is what turns assistance into delegation. When we can trust an agent to do what we intend, within the limits we set, we can hand off the work we never wanted to spend our lives on: the repetitive tasks that drain attention, the…
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