AI Risk & Ethics Specialist

Work Role ID: 733  |  Workforce Element: AI / Data

What does this work role do? Educates those involved in the development of AI and conducts assessments on the technical and societal risks across the lifecycle of AI solutions from acquisition or design to deployment and use.

KSAT ID Description KSAT
22 * Knowledge of computer networking concepts and protocols, and network security methodologies. Knowledge
108 * Knowledge of risk management processes (e.g., methods for assessing and mitigating risk). Knowledge
1157 * Knowledge of national and international laws, regulations, policies, and ethics as they relate to cybersecurity. Knowledge
1158 * Knowledge of cybersecurity principles. Knowledge
1159 * Knowledge of cyber threats and vulnerabilities. Knowledge
6900 * Knowledge of specific operational impacts of cybersecurity lapses. Knowledge
6935 * Knowledge of cloud computing service models Software as a Service (SaaS), Infrastructure as a Service (IaaS), and Platform as a Service (PaaS). Knowledge
6938 * Knowledge of cloud computing deployment models in private, public, and hybrid environment and the difference between on-premises and off-premises environments. Knowledge
KSAT ID Description KSAT
537A Develop methods to monitor and measure risk and assurance efforts on a continuous basis. Task
765B Perform AI architecture security reviews, identify gaps, and develop a risk management plan to address issues. Task
942 Knowledge of the organization’s core business/mission processes. Knowledge
952 Knowledge of emerging security issues, risks, and vulnerabilities. Knowledge
963A Ensure risk mitigation plans of action and milestones are in place. Task
1000B Ensure that AI design and development activities are properly documented and updated. Task
5854 Collaborate with appropriate personnel to address Personal Health Information (PHI), Personally Identifiable Information (PII), and other data privacy and data resusability concerns for AI solutions. Task
5856 Communicate the results of AI risk assessments to relevant stakeholders. Task
5860 Coordinate with appropriate personnel to identify methods for users and developers to report concerns about the implementation of DoD AI Ethical Principles. Task
5863 Create and/or maintain processes to ensure data management efforts comply with AI ethical principles. Task
5873 Determine 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. Task
5878 Develop risk mitigation strategies to ensure enumerated risks are prioritized, mitigated, shared, transferred, and/or accepted. TAsk
5879 Direct and/or support organizational and project-level AI risk management activities. Task
5881 Ensure risk management responsibilities are clearly defined, assigned, and communicated to relevant stakeholders. Task
5889 Identify and submit exemplary AI use cases, best practices, failure modes, and risk mitigation strategies, including after-action reports. Task
5893 Implement 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. Task
5896 Maintain current knowledge of advancements in DoD AI Ethical Principles and Responsible AI. Task
5900 Measure the compliance of AI tools with DoD AI Ethical Principles. Task
5904 Perform risk assessment on AI applications to identify technical, societal, organizational, and mission risks. Task
5905 Perform 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. Task
6311 Knowledge of machine learning theory and principles. Knowledge
7003 Knowledge of AI security risks, threats, and vulnerabilities and potential risk mitigation solutions. Knowledge
7020 Knowledge of DoD AI Ethical Principles (e.g., responsible, equitable, traceable, reliable, and governable). Knowledge
7021 Knowledge of emerging trends and future use cases of AI. Knowledge
7024 Knowledge of how AI is developed and operated. Knowledge
7034 Knowledge of interactions and integration of DataOps, MLOps, and DevSecOps in AI. Knowledge
7036 Knowledge of laws, regulations, and policies related to AI, data security/privacy, and use of publicly procured data for government. Knowledge
7038 Knowledge of metrics to evaluate the effectiveness of machine learning models. Knowledge
7040 Knowledge of Personal Health Information (PHI), Personally Identifiable Information (PII), and other data privacy and data reusability considerations for AI solutions. Knowledge
7041 Knowledge of remedies against unintended bias in AI solutions. Knowledge
7044 Knowledge of testing, evaluation, validation, and verification (T&E V&V) tools and procedures to ensure systems are working as intended. Knowledge
7045 Knowledge of the AI lifecycle. Knowledge
7048 Knowledge of the benefits and limitations of AI capabilities. Knowledge
7051 Knowledge of the possible impacts of machine learning blind spots and edge cases. Knowledge
7052 Knowledge of the principles, methods, and tools used for risk and bias assessment and mitigation, including assessment of failures and their consequences. Knowledge
7056 Skill in assessing AI capabilities for bias or ethical concerns. Skill
7064 Skill in developing solutions and/or recommendations to minimize negative impacts of machine learning, especially for edge cases. Skill
7065 Skill in explaining AI concepts and terminology. Skill
7067 Skill in identifying low-probability, high-impact risks in machine learning training data sets. Skill
7068 Skill in identifying organizational and project-level AI risks, including AI security risks and requirements. Skill
7069 Skill in identifying risk over the lifespan of an AI solution. Skill
7075 Skill in testing and evaluating machine learning algorithms or AI solutions. Skill