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Data safety with AI

For Anyone who pastes work material into AI tools and wants to know — before pasting — what's safe, what needs masking, and what never goes in. · 15 days · Concepts

A 15-day course
One short lesson a day · go at your own pace
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The days
  1. 1See where your paste goesBy the end you can explain why putting information into an AI tool is a form of sending and decide when to stop before you paste.
  2. 2Know your company's rulesBy the end you can distinguish approved workplace AI from shadow AI and choose a safe next step when the policy is unclear.
  3. 3Never paste peopleBy the end you can recognize information that identifies or describes a person and keep it out of unapproved AI workflows.
  4. 4Never paste the keysBy the end you can recognize credentials and high-value company information that must stay out of unapproved AI tools.
  5. 5Handle customer conversations with careBy the end you can prepare a customer conversation for an approved AI summarization workflow without carrying unnecessary identity or sensitive detail into it.
  6. 6Anonymize like you mean itBy the end you can test whether masked information remains linkable to a person and choose aggregation or synthetic data when masking is too weak.
  7. 7Mind the documentsBy the end you can inspect a document for hidden sheets, comments, metadata, and embedded content before using it in an approved AI workflow.
  8. 8Watch the outputs tooBy the end you can inspect AI-generated output for sensitive echoes, inferences, and disclosures before reusing or sharing it.
  9. 9Know the tool's settingsBy the end you can distinguish conversation history, retention, training use, account controls, and organizational approval without treating one setting as proof of safety.
  10. 10Paste the minimumBy the end you can reduce an AI task to the smallest approved facts, pattern, or aggregate needed to produce a useful result.
  11. 11Respect the partner boundaryBy the end you can recognize data entrusted by a partner, separate access from permission, and identify the owner who can authorize a new AI use.
  12. 12Spot a leak, report a leakBy the end you can recognize a possible AI-data incident, stop further sharing, preserve useful facts, and report it through the right internal route.
  13. 13Set the team normsBy the end you can define a short team paste-policy that names approved routes, red lines, minimum-input habits, review, and escalation.
  14. 14Build your before-you-paste checklistBy the end you can assemble a five-question checklist that catches destination, permission, sensitivity, minimum need, and recovery before any paste.
  15. 15Audit a real week of promptsBy the end you can audit one week of your AI use, identify an unnecessary or unsafe disclosure pattern, and redesign the workflow using your checklist.