Artificial Intelligence Ethics Framework for the Intelligence Community
This document provides an ethics guide and framework for United States Intelligence Community personnel on how to procure, design, build, use, protect, consume, and manage artificial intelligence and related data. It outlines considerations for understanding goals and risks, addressing legal obligations, incorporating human judgment, mitigating undesired bias, testing models, and maintaining transparency and accountability. The framework serves as a living document to promote ethical design and use consistent with the principles of the Intelligence Community.
Summary and content fields are drawn from the document text and are pending editorial review.
Who issued it
Who it governs
This guide is for United States Intelligence Community personnel involved in procuring, designing, building, using, or managing AI systems.
What the document contains
This document covers operational, legal, and ethical considerations across the entire AI lifecycle for U.S. Intelligence Community personnel. It addresses risk assessment, data governance, human oversight, bias mitigation, testing standards, version control, documentation requirements, explainability, and periodic review.
The document does not provide specific technical algorithms, detailed legal statutes, or binding enforcement mechanisms outside of agency-specific procedures.
- AI in the Intelligence Community must align with legal obligations, respect civil liberties, and avoid undesired bias while fulfilling its specific mission purposes.
- Personnel must evaluate potential goals, benefits, and risks before developing or deploying AI systems.
- Human judgment and accountability must be incorporated at appropriate stages of the AI lifecycle, especially for sensitive decisions.
- Comprehensive testing, version control, and documentation of data provenance and model limitations are required for auditing and oversight.
- AI systems require periodic reviews and ongoing stewardship to ensure continued accuracy and alignment with ethical standards.
· Purpose: Understanding Goals and Risks · Legal Obligations and Policy Considerations Governing the AI and the Data · Human Judgment and Accountability · Mitigating Undesired Bias and Ensuring Objectivity · Testing Your AI · Accounting for Builds, Versions, and Evolutions of an AI · Documentation of Purpose, Parameters, Limitations, and Design Outcomes · Transparency: Explainability and Interpretability · Periodic Review · Stewardship and Accountability: Training Data, Algorithms, Models, Outputs of the Models, Documentation
How it scores
Each score is backed by a quote verified against the document text. Editorial review has not yet confirmed them.
Accountability
4/5Clear responsibility for AI outcomes
Who should be the accountable human(s)? Do they know that they are designated as the accountable human(s)? What qualifications are required to serve in that role?
3 Human Judgment and Accountability
screening score · 2026-10-23
Fairness
4/5Non-discrimination and equitable treatment
Taking steps to discover bias throughout the lifecycle of an AI, mitigate undesired bias, and to document and communicate known biases and how they were addressed, are critical
Mitigating Undesired Bias and Ensuring Objectivity
screening score · 2026-10-23
Human Dignity
4/5Respect for the inherent worth of persons
If the AI could result in significant consequences such as an action with the potential to deprive individuals of constitutional rights or the potential to interfere with their free exercise of civil liberties, how will you ensure individual human involvement and accountability
3 Human Judgment and Accountability
screening score · 2026-10-23
Human Oversight
4/5Humans remain in control of consequential decisions
Given the purpose of the AI and potential consequences of its use, at what points, if any, are a human required as part of the decision process?
3 Human Judgment and Accountability
screening score · 2026-10-23
Privacy
4/5Protection of personal data and private life
What legal or policy restrictions exist on the use of data under this authority/agreement/ contract? (For example, data subject to the Privacy Act should be used for a purpose that is compatible with that for which the data was collected).
2 Legal Obligations and Policy Considerations Governing the AI and the Data
screening score · 2026-10-23
Transparency
4/5Openness about how AI systems work and are used
Consistent with the Principles of Intelligence Transparency for the Intelligence Community, use methods that are explainable and understandable, to the extent practicable
Transparency: Explainability and Interpretability
screening score · 2026-10-23
Enforcement
2/5Consequences and compliance mechanisms with real force
If anyone believed that the AI no longer meets this ethical framework, who will be responsible for receiving the concern and as appropriate investigating and remediating the issue?
Stewardship and Accountability
screening score · 2026-10-23
Impact Assessment
4/5Required assessment of an AI system's risks/impacts before or during use
What benefits and risks, including risks to civil liberties and privacy, might exist when this AI is in use? Who will benefit? Who or what will be at risk?
1 Purpose: Understanding Goals and Risks
screening score · 2026-10-23