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ai-act-compliance

ai-act-compliance

【文档与办公】Check construction AI systems against the EU AI Act (Regulation 2024/1689): classify risk of estimation, scheduling, CV and agent tools, document transparency, keep human oversight. Use when deploying or auditing AI in construction.

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name: "ai-act-compliance" description: "Check construction AI systems against the EU AI Act (Regulation 2024/1689): classify risk of estimation, scheduling, CV and agent tools, document transparency, keep human oversight. Use when deploying or auditing AI in construction."

EU AI Act Compliance for Construction AI (2026)

Why it matters

The EU AI Act (2024/1689) is binding from 2025–2027 in phases. Construction AI — estimators, computer-vision site monitoring, agent assistants — mostly lands in limited or minimal risk, but misclassification or missing transparency is a compliance failure, and high-risk uses (safety-critical, worker monitoring, access decisions) bring real obligations.

Classification quick check for construction tools

SystemLikely tierObligations
Cost estimation assistant (BOQ, unit prices)limited / minimaltransparency (users know it is AI), basic logging
Schedule optimisationminimalnone beyond general law
Site camera CV for progresslimitedtransparency, data minimisation
CV for PPE/safety enforcementhigh risk (safety component?)full: risk management, data governance, human oversight, logs
Worker performance monitoringhigh risk (employment)prohibited or high-risk — treat carefully
AI agent that signs/submits binding documentsnot allowed without humanhuman oversight mandatory

Rule of thumb: if a human previously had to sign it, an AI must not sign it alone.

Practical compliance checklist (per tool)

  1. Classify — document the risk tier and reasoning.
  2. Transparency — users must know they interact with AI output; mark AI-generated estimates as such.
  3. Human oversight — a qualified human reviews binding estimates, contracts, safety decisions.
  4. Data governance — minimal personal data in site CV; no biometric identification.
  5. Logging — record model, inputs, outputs, version (the ERP usage-ledger pattern).
  6. Instructions for use — document limitations (e.g. early estimates ±30–50%).

Mapping to the DDC stack

  • oce-estimate-boq, cost-estimation-*, cost-prediction: limited risk — add AI-output labels.
  • progress-monitoring-cv, defect-detection-ai: limited — no personal data, transparency.
  • safety-compliance-checker enforcing PPE via CV: reclassify — keep a human in the loop, document.
  • ai-agent-orchestration: supervisor must be a human at decision gates.

Resources

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