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Leadership guide/Institutional decisions
The reviewed policies share many recurring principles, but they do not agree on every rule. Use that common ground as a starting point. Concentrate your deliberation where approaches differ.
Permissions, decision authority, faculty discretion and disclosure are among the choices that vary. Shape these choices, and the wider policy, around your institution’s mission, culture and operating context.
Choose a topic below for a recommended position, local choices and language to adapt. Print individual pages for your team’s discussions.
DirectionSet purpose and responsibility.SafeguardsSet the boundaries for useful AI.LearningProtect learning and build capability.StewardshipKeep the policy working.All topicsThe twelve decision areas
All twelve decisions are available below.
What should AI help your institution accomplish?
What exactly does an approval authorize?
What information can enter which AI systems?
When may AI assist, recommend or act?
What must students learn to do, with and without AI?
How should the institution handle concerns about AI-assisted work?
Can the people affected participate and obtain effective help?
When should someone know AI is involved?
Who recommends, who decides and who remains accountable?
What do people need to be able to do responsibly?
What happens when an AI-supported service gets something wrong?
What should trigger a new decision?
A concrete use makes the decision easier to see. Follow the route that matches your next conversation.
We are buying or enabling an AI tool.Risk and approval →An assistant could access protected records.Information and security →A service will take actions on our behalf.Authority and recovery →Faculty need clear course expectations.Teaching and learning →Our team disagrees about the policy.Prepare a recommendation →
Work with HumanSkills on AI policy, governance and the decisions your institution needs to make.