AI Risk and Ethics Specialist

• 537ADevelop methods to monitor and measure risk and assurance efforts on a continuous basis.Core
• 765BPerform AI architecture security reviews, identify gaps, and develop a risk management plan to address issues.Core
• 963AEnsure risk mitigation plans of action and milestones are in place.Core
• 1000BEnsure that AI design and development activities are properly documented and updated.Core
• 5854Collaborate with appropriate personnel to address Personal Health Information (PHI), Personally Identifiable Information (PII), and other data privacy and data reusability concerns for AI solutions.Core
• 5856Communicate the results of AI risk assessments to relevant stakeholders.Core
• 5860Coordinate with appropriate personnel to identify methods for users and developers to report concerns about the implementation of DoD AI Ethical Principles.Core
• 5863Create and/or maintain processes to ensure data management efforts comply with AI ethical principles.Core
• 5873Determine methods and metrics for quantitative and qualitative measurement of AI risks so that sensitivity, specificity, likelihood, confidence levels, and other metrics are identified, documented, and applied.Core
• 5878Develop risk mitigation strategies to ensure enumerated risks are prioritized, mitigated, shared, transferred, and/or accepted.Core
• 5879Direct and/or support organizational and project-level AI risk management activities.Core
• 5881Ensure risk management responsibilities are clearly defined, assigned, and communicated to relevant stakeholders.Core
• 5889Identify and submit exemplary AI use cases, best practices, failure modes, and risk mitigation strategies, including after-action reports.Core
• 5893Implement Responsible AI best practices and standards within AI solutions according to the DoD AI Ethical Principles, Responsible AI Guidelines, and/or any other pertinent laws.Core
• 5896Maintain current knowledge of advancements in DoD AI Ethical Principles and Responsible AI.Core
• 5900Measure the compliance of AI tools with DoD AI Ethical Principles.Core
• 5904Perform risk assessment on AI applications to identify technical, societal, organizational, and mission risks.Core
• 5905Perform risk assessment whenever an AI application or AI-enabled system undergoes a major change, when emergent behaviors are detected, and/or unintended consequences are reported.Additional

• 22* Knowledge of computer networking concepts and protocols, and network security methodologies.Core
• 108* Knowledge of risk management processes (e.g., methods for assessing and mitigating risk).Core
• 942Knowledge of the organization's core business/mission processes.Additional
• 952Knowledge of emerging security issues, risks, and vulnerabilities.Core
• 1157* Knowledge of national and international laws, regulations, policies, and ethics as they relate to cybersecurity.Core
• 1158* Knowledge of cybersecurity principles.Core
• 1159* Knowledge of cyber threats and vulnerabilities.Core
• 6311Knowledge of machine learning theory and principles.Core
• 6900* Knowledge of specific operational impacts of cybersecurity lapses.Core
• 6935* Knowledge of cloud computing service models Software as Service (SaaS), Infrastructure as a Service (IaaS), and Platform as a Service (PaaS).Core
• 6938* Knowledge of cloud computing deployment models in private, public, and hybrid environment and the difference between on-premises and off-premises environments.Core
• 7003Knowledge of AI security risks, threats, and vulnerabilities and potential risk mitigation solutions.Core
• 7020Knowledge of DoD AI Ethical Principles (e.g., responsible, equitable, traceable, reliable, and governable).Core
• 7021Knowledge of emerging trends and future use cases of AI.Core
• 7024Knowledge of how AI is developed and operated.Core
• 7034Knowledge of interactions and integration of DataOps, MLOps, and DevSecOps in AI.Core
• 7036Knowledge of laws, regulations, and policies related to AI, data security/privacy, and use of publicly procured data for government.Core
• 7038Knowledge of metrics to evaluate the effectiveness of machine learning models.Core
• 7040Knowledge of Personal Health Information (PHI), Personally Identifiable Information (PII), and other data privacy and data reusability considerations for AI solutions.Core
• 7041Knowledge of remedies against unintended bias in AI solutions.Core
• 7044Knowledge of testing, evaluation, validation, and verification (T&E, V&V) tools and procedures to ensure systems are working as intended.Additional
• 7045Knowledge of the AI lifecycle.Core
• 7048Knowledge of the benefits and limitations of AI capabilities.Core
• 7051Knowledge of the possible impacts of machine learning blind spots and edge cases.Core
• 7052Knowledge of the principles, methods, and tools used for risk and bias assessment and mitigation, including assessment of failures and their consequences.Core
• 7111* Knowledge of Zero Trust Security Model Principles.Core

• 7056Skill in assessing AI capabilities for bias or ethical concerns.Core
• 7064Skill in developing solutions and/or recommendations to minimize negative impacts of machine learning, especially for edge cases.Core
• 7065Skill in explaining AI concepts and terminology.Core
• 7067Skill in identifying low-probability, high-impact risks in machine learning training data sets.Core
• 7068Skill in identifying organizational and project-level AI risks, including AI security risks and requirements.Core
• 7069Skill in identifying risk over the lifespan of an AI solution.Core
• 7075Skill in testing and evaluating machine learning algorithms and/or AI solutions.Core

The DCWF Tool lists no abilities for this work role.