wab
wab — yIlaD.
{study notes}
- Delegation-Diligence Loop: QaPla'! Qo'noS-style tlhIngan Hol - decide what task, tool, data hand off to AI, then verify and own result. Description and Discernment work between Delegation and Diligence.
- Privacy Concerns: Some {AI tools} use your inputs for training future models. Match tool to task - higher sensitivity data needs stricter privacy settings.
- Data Hygiene Strategy: Strip identifying details before sharing - replace names with "Customer A," remove exact figures if unnecessary, delete contact information entirely.
- Validation Process: Compare AI's findings against your own observations. Gap between what AI sees and what you know shows where your judgment as business owner is irreplaceable.
- Accountability Three Questions: Accuracy - does AI go beyond what data shows? Usefulness - what keep, edit, or cut? Accountability - would you put your name on this?
- Fast Response Protocol: If something goes wrong, act quickly - delete conversation and request data deletion from {AI system}.
- Document What Works: Build validated approaches, not blind trust. Record successful methods so you can replicate them next time.
- Clear Brief Creation: Before using AI, write specific goal, note 2-3 patterns you already noticed, define what useful output looks like. Clarity makes evaluation easier.
{flashcards} 10 {cards}
{question}
yI'ang · ←/→
{answer}
{flip}
{knowledge check} 6 {questions}