AI in Practice: Tools, Ethics, Honest Tradeoffs
Move beyond AI basics to practical classroom applications while honestly confronting the ethical, environmental, and equity tensions of AI adoption — including the contradiction of promoting both environmental responsibility and energy-intensive AI tools.
What you'll walk away with
Evaluate AI tools against pedagogical, ethical, environmental, and equity criteria before adopting
Design AI-resistant assessments that surface genuine understanding rather than information retrieval
Construct a personal AI ethics framework grounded in student agency, data sovereignty, and environmental responsibility
Apply a structured decision tree to any proposed AI tool adoption, weighing benefits against honest tradeoffs
How a Learning Series works
Work through the snacks — short, evidence-based lessons that build your understanding. Each one gives you research, a classroom connection, and one thing to try or discuss.
Test your understanding in a low-stakes mini-experiment before you bring it to your classroom. Leverage our downloadable materials to support you in your teaching and classroom practice and let us know how it goes!
For credit towards an Accingo Course certificate, try something from this series in your own classroom, then complete a short, structured reflection on what you learned and what you would bring to your PLC and/or regular practice. You will see "Application Artifact" if required.
