Responsible AI
Principles for applying artificial intelligence within PATMOS678™ operating environments.
1. Human Accountability
AI can assist with analysis, prediction and workflow coordination, but responsibility for consequential decisions should remain with appropriately authorised people.
2. Appropriate Automation
Automation should be bounded by defined permissions, escalation paths and intervention points rather than treated as unrestricted autonomy.
3. Uncertainty
AI outputs may be probabilistic or incomplete. Systems and users should distinguish recommendations and predictions from verified facts.
4. Data Governance
AI should use information only where access, purpose and handling are appropriately authorised.
5. Higher-Risk Contexts
Clinical, care, employment, financial and other consequential contexts require stronger review, governance and applicable legal assessment.
6. Monitoring
Production AI should be evaluated for performance, errors, inappropriate outputs and changes in operating conditions as part of ongoing governance.