No AI-approved structure
The site and product do not describe AI as an independent safety authority.
Evidence, approval and outcome governance
Responsible Industrial AI
Responsible AI at PDICON means bounded tasks, evidence-linked outputs, qualified human approval, explicit data consent, reproducible model lineage, monitored behavior and outcome-based learning.
StatusMandatory design principle
Reviewed2026-08-20
Direct answer
Responsible AI at PDICON means bounded tasks, evidence-linked outputs, qualified human approval, explicit data consent, reproducible model lineage, monitored behavior and outcome-based learning.
Design boundary
What the system will not pretend to be.
No hidden training use
Consent and purpose are recorded before data enters a dataset.
No unversioned production model
Every runtime resolves to approved lineage and evaluation.
01Bounded task
Define what the model may and may not decide.
Every application has a task schema, approved evidence sources, output contract and escalation path.
02Human authority
Recommendation is not approval.
Qualified professionals remain accountable for engineering, procurement, safety and project decisions.
03Operational accountability
Trace output to model, evidence and outcome.
Model version, context, recommendation, expert correction and later result form one audit record.
Operating matrix
Evidence moves through explicit controls.
| Subject | Input | Intelligence operation | Human / policy control | Output |
|---|---|---|---|---|
| Grounding | Controlled project evidence | Source-linked generation | Citation check | Reviewable claim |
| Authority | Model recommendation | Human review | Qualified approver | Recorded decision |
| Accountability | Version and execution log | Audit linkage | Governance review | Traceable outcome |
Questions answered
Precise answers for technical evaluation.
Who approves engineering decisions?
Qualified and authorized professionals approve engineering and safety-critical decisions.
How does the system learn from correction?
The expert’s acceptance, rejection or modification, rationale and eventual project outcome become a governed workflow episode.