Responsible data stewardship. Disciplined AI governance.
Data governance and AI oversight ensure that institutional information assets and AI capabilities are managed with the discipline, transparency, and ethical responsibility that aerospace operations demand.
All institutional data is classified by sensitivity level with defined handling requirements. Classification ensures appropriate protection for controlled unclassified information (CUI), proprietary data, and operational information.
Data access is managed through role-based controls aligned with need-to-know principles. Access privileges are reviewed periodically and adjusted based on role changes and organizational requirements.
AI and machine learning models used in institutional processes are subject to defined oversight including validation, bias assessment, performance monitoring, and periodic review by qualified personnel.
AI-generated outputs affecting engineering decisions, compliance determinations, or capture activities require human review and approval before implementation or submission.
Controlled Unclassified Information is handled in accordance with NIST SP 800-171 and DFARS 252.204-7012 requirements, with defined marking, storage, transmission, and disposal procedures.
AI usage is governed by defined ethical principles including transparency, accountability, fairness, and alignment with institutional values. AI governance is aligned with the institution's AI Governance framework.