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Define AI responsibilities, human judgment, review, decision authority, escalation, and learning in a recurring workflow. Use when human-AI collaboration is vague or unreliable.
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SOC 職業分類に基づく
SKILL.md を表示中
| name | human-aipom-work-contract |
| description | Define AI responsibilities, human judgment, review, decision authority, escalation, and learning in a recurring workflow. Use when human-AI collaboration is vague or unreliable. |
| type | component |
| category | product-team-workflows |
| phase | 1 |
| status | active |
| operating_level | ["product-team","initiative"] |
| audience | ["Product Operations","Product Manager","Team Lead","Design","Engineering","Operations","AI Governance"] |
| best_for |
| ["Introducing AI into a consequential recurring workflow","Fixing vague human-in-the-loop responsibilities","Clarifying review, handoffs, and accountability"] |
| evidence_required | ["Current workflow and decision points","Roles, inputs, outputs, and failure evidence","AI behavior and evaluation evidence","Existing authority and escalation policies"] |
| produces | ["Human-AI work contract","Review and escalation rules","Workflow measures and learning cadence"] |
| assessment_questions | ["WFL-02","WFL-03","WFL-04","WFL-05","GOV-01"] |
| maturity_move | {"from":"emerging","to":"repeatable"} |
| estimated_time | 45-75 min |
| group_size | 3-8 |
| depends_on | ["aipom-behavior-contract-builder"] |
| combine_with | ["aipom-autonomy-boundary-designer","aipom-productive-motion-map","aipom-workflow-playbook-builder"] |
| sources | ["https://www.nist.gov/publications/artificial-intelligence-risk-management-framework-ai-rmf-10"] |
Define how humans and AI collaborate in one recurring workflow: what AI may prepare or perform, where human judgment enters, who reviews, who decides, who remains accountable, and how failures improve the work.
AI adoption often adds hidden review labor, ambiguous authority, and brittle handoffs. A work contract makes the operating design explicit. Its existence is not maturity; observed use and improved workflow evidence are.
Use after understanding the current workflow and before production adoption or expanded autonomy. Revisit after incidents, role changes, model changes, or workload evidence.
Include people who perform the work, the Team Lead, Product Manager, Product Operations where present, technical owner, decision owner, and accountable operational leader. Add affected-user and governance perspectives as consequences require.
Bring workflow observations, cycle time, rework, decisions, current roles, AI evaluations, operator capacity, exceptions, and incidents. Do not design solely from a process diagram.
Use for discovery synthesis, support, portfolio analysis, content review, knowledge retrieval, decision support, and agentic workflows.
Use aipom-behavior-contract-builder for behavior, aipom-autonomy-boundary-designer for authority, and later workflow mapping and playbook skills for deeper redesign and reuse.
