Co-Designing a Trust Calibration Checklist for AI Practitioners: A Case Study on AI stakeholders · Final Review · Score 26/30Co-Designing a Trust Calibration Checklist for AI Practitioners: A Case Study on AI stakeholders · Final Review · Score 26/30Co-Designing a Trust Calibration Checklist for AI Practitioners: A Case Study on AI stakeholders · Final Review · Score 26/30Co-Designing a Trust Calibration Checklist for AI Practitioners: A Case Study on AI stakeholders · Final Review · Score 26/30Co-Designing a Trust Calibration Checklist for AI Practitioners: A Case Study on AI stakeholders · Final Review · Score 26/30Co-Designing a Trust Calibration Checklist for AI Practitioners: A Case Study on AI stakeholders · Final Review · Score 26/30
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Clear iterative logic: V1 literature prototype, Round 1 practitioners (P1–P3), Round 2 governance/QA (P4–P5), with a stated rationale for the insider-vs-oversight contrast.
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Excellent traceability: every revision is tied to a specific participant quote and mapped onto a named limitation, and the full interview transcripts are included for verification.
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The five-theme thematic analysis (active verification, plausibility-accuracy decoupling, reputation vs testing, time pressure, accountability/logging) is coherent and well-evidenced.
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The B/D/A timing markers (Before/During/After) are a genuinely useful operational addition that anchors items to workflow checkpoints.
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The worked use case applies V3 systematically and reaches a defensible conditional-trust verdict with explicit failure conditions (e.g., A4 or D3 failing blocks deployment).
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Only five participants, all in or adjacent to software engineering; the claim of a "governance/oversight" perspective is thin since P4/P5 are still technically fluent, limiting the diversity the design depends on.
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The abstract and introduction read informally and unevenly ("But 'Why do we have this gap?'", "System Reliability Gap" used without definition), and terminology drifts between "Impact Assessment Template" and "checklist".
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Internal inconsistency: the worked use case invokes item D5 ('Assisted by AI' tag) but the V3 checklist reproduced in the appendix stops at D4.
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Reference [1] is titled "...Autonomous Urban Drone Navigation System," which does not match the pedestrian-detection / software-developer framing used throughout — the provenance from Deliverable 1 is unclear.
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No participant demographics, no reporting of how representative or saturated the five interviews were, and generalizability claims exceed what five software-centric interviews can support.