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ethical AI

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A practical framework for responsible AI in communication (Part 3 of 3)

How do you develop both layers needed to use AI responsibly in communication? This practical framework addresses foundational professional skills first, then layers on AI augmentation skills. The path forward is clear: either rush into adoption without support and watch work quality decline, or commit to strong foundations and use AI to amplify genuine expertise. Leading organizations like Amazon and IBM model this approach, ensuring baseline competence before advanced AI capabilities.

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Inclusive leadership
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The baseline skills needed for responsible AI use (Part 2 of 3)

Most AI training programs overlook a fundamental truth: teaching prompt engineering won’t help people use AI responsibly without foundational skills to recognize what good communication looks like. AI operates like Michelangelo’s chisel. It didn’t make him a master sculptor, it allowed him to execute expertise he’d already developed. The principle is simple: strong baseline skills multiplied by AI equals enhanced productivity. Weak baseline skills multiplied by AI equals scaled problems. Effective AI upskilling requires two distinct layers: foundational professional skills first, then AI augmentation skills. You cannot skip Layer 1.

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Inclusive leadership
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Responsible AI in communication starts with the right foundation (part 1 of 3)

As an inclusive leadership and communication consultant, I believe in “communication for good”. Communication that creates understanding, builds bridges, and breaks barriers. Workslop is the opposite. Recent research shows 40% of workers received low-quality AI content last month, costing nearly two hours per incident to fix. But we’re diagnosing the wrong disease. This isn’t about the tool. It’s about the skills gap. The real conversation we should be having isn’t “Is AI good or bad?” but “How do we support everyone in using it well?”

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Inclusive leadership
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