Ten years ago Responsible AI meant building responsibly. Today, with generative AI in every profession, responsibility rests with each of us as adopters. The Artificiality Institute’s Become More Essential with AI course reframed my approach, from boundary questions to adaptation states, helping me model exemplar collaboration and guide others.
What does it look like to teach with AI, not just about it? In redesigning my undergraduate course, I treated AI as a responsible teaching assistant. Guided by Anthropic’s 4D framework for AI Fluency, I explored how to delegate tasks, craft ethical prompts, embed discernment into student work, and maintain full human oversight. This post shares the strategies, safeguards, and surprises behind building an AI-integrated course without compromising critical thinking or student agency.
Many treat AI councils as risk shields that slow things down. They should be your greenlight. Good councils protect you from what can go wrong and unlock what can go right. They tie ambition to accountability, strategy to trust, and guardrails to growth. Here’s how to build one that keeps AI aligned, practical, and trusted.
Many HR teams have started AI literacy efforts—but struggle with what comes next. This post offers a practical playbook to move from curiosity to action, using jobs-to-be-done thinking, strategic pilot scoring, and a 90-day implementation engine to build trust, drive adoption, and scale GenAI responsibly within the HR function.
Frontier firms, Agent bosses and a re-imagined future of work are on the horizon. But scaling AI responsibly will require human-centered literacy, cultural change and leadership evolution. Will your organization transform with intention or struggle to keep up?
At a recent AI/ML leadership summit, executives rated AI literacy as highly important but acknowledged a significant gap in their workforce’s current capabilities. This post explores strategies to bridge this gap effectively.