Co-Designing a Reflective Checklist for AI Task Delegation · Final Review · Score 30/30Co-Designing a Reflective Checklist for AI Task Delegation · Final Review · Score 30/30Co-Designing a Reflective Checklist for AI Task Delegation · Final Review · Score 30/30Co-Designing a Reflective Checklist for AI Task Delegation · Final Review · Score 30/30Co-Designing a Reflective Checklist for AI Task Delegation · Final Review · Score 30/30Co-Designing a Reflective Checklist for AI Task Delegation · Final Review · Score 30/30
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Ten substantive V2 → V3 changes are each traced to specific participant(s), which is exemplary co-design documentation.
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Appendix H provides full verbatim participant feedback, making every claimed revision independently checkable.
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Stakeholder groups (software, business, legal/compliance) are deliberately separated to avoid seniority effects, and the rationale is well argued.
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The two-tier design (5-item quick check plus full checklist) with explicit decision rules and four delegation outcomes is genuinely actionable.
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Three worked tasks (low-risk coding, high-risk coding, non-technical HR letter) test the checklist's generality beyond software.
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Self-aware methodology: items retained against feedback are flagged, and a visibility/reconstruction test is reported.
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Items 4.4 and 4.5 still overlap (responsible person vs who reviews/approves/documents), the exact redundancy P2 flagged.
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Decision-rule thresholds (e.g., "3+ PA → escalate") are arbitrary and unexplained.
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V1 → V2 is documented only as an in-class peer session, with no traceable change list.
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P1 explicitly argued item 5.2 was unnecessary, yet it was retained without a stated retention rationale.
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Worked-case item judgments (pass/fail) are asserted rather than shown via a filled status column.
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Literature grounding is thin (4 references) for the strong overtrust/automation-bias framing.