Learning Objectives

After completing this lecture, you will be able to:

• Understand the key concepts of government ai policy landscape in a government context

• Connect government ai policy landscape to your agency's AI initiatives

• Identify next steps for applying these concepts in your role

Key Topics Covered

• Executive Orders (14110, 14179), OMB M-24-10, M-24-18, M-25-21, M-25-22
• What they mean for your daily work
• Government context for government ai policy landscape
• Practical applications and next steps

Why This Matters for Government

Government agencies face unique challenges when it comes to AI adoption. This lecture addresses these challenges head-on by providing all government employees with the knowledge and frameworks needed to navigate AI in the public sector responsibly and effectively.

As part of the L1 (AI Aware) curriculum, this lecture builds on the foundational principle that every AI system in government ultimately serves citizens. Whether you are working with AI tools daily or setting strategy for your agency, understanding government ai policy landscape is essential for responsible, effective government AI adoption.

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TRANSCRIPT: Government AI Policy Landscape

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What you will learn: Executive Orders and OMB guidance that govern AI use in government. What applies to your role. How to stay compliant.

The policy framework for government AI has changed dramatically. In 2023-2024, executive orders and OMB memoranda established clear requirements. This isn't optional guidance. It's regulatory. Understanding what applies to you is essential.

This lecture walks through key policy instruments and what they mean for your daily work. By the end, you'll know what you're required to do and what you need to ask your agency leadership about.

Purpose

Policy is how government translates principles into requirements. Understanding policy helps you know what's required versus optional, what resources you should demand, and what lines you shouldn't cross.

Why This Matters for Government

Non-compliance with executive orders and OMB guidance can result in audit findings, loss of funding, or worse. More importantly, these policies exist because past AI deployments caused harm. Understanding the policy landscape means understanding what lessons people learned the hard way.

Key Policy Instruments

Executive Order 14110: Safe, Secure, and Trustworthy AI (Late 2023)

This is the foundational executive order. It established:

• Risk-based approach: Different requirements depending on risk level. Using an LLM to draft emails (low-risk). Using AI to make benefit eligibility determinations (high-risk).

• Chief AI Officer requirement: Each federal agency must have a Chief AI Officer responsible for AI governance.

• Safety testing: Requirements for testing AI systems before deployment, especially for high-risk applications.

• Transparency: Government agencies using AI must inform the public about what decisions the AI is influencing.

• Bias testing: Specific requirements to test for and mitigate bias and discrimination.

What it means for you: Your agency should have an AI governance structure. If your agency is using or considering AI, ask: "Have we had this reviewed by the Chief AI Officer's office? Have we done bias testing?" If the answer is no, that's a problem.

Executive Order 14179 (Expected 2024-2025)

Focus on AI workforce development and ensuring government can attract and retain AI talent. Expected to include:

• Hiring flexibilities for AI professionals

• Funding for AI training

• Partnership with academic institutions

What it means for you: Likely that your agency will have more resources for AI training. This course is one example.

OMB M-24-10: Advancing Governance, Innovation, and Risk Management for Agency Use of AI (February 2024)

This is THE operational guidance. Every federal agency must comply. Key requirements:

• AI Governance Structure: Clear roles and responsibilities. Who approves AI use? Who oversees fairness? Who has authority to stop deployment?

• Impact Assessments: Before deploying AI that affects decisions about federal benefits, civil rights, civil liberties, or safety—agencies must conduct impact assessments documenting:

• What the system does

• Risk level

• Testing for bias and fairness

• Human oversight mechanisms

• Appeal processes

• Monitoring plans

• Transparency and Notification: Agencies must notify the public when AI is influencing decisions about them. Not "secretly" using AI.

• Human Review Requirement: For "high-impact AI," humans must review and approve decisions. AI provides input; humans decide.

• Compliance: OMB will audit agencies for compliance.

What it means for you: If your agency uses or proposes AI, you should expect impact assessments, governance reviews, and public notification. This is mandatory, not optional.

OMB M-24-18: Strengthening AI Governance (June 2024)

Focus on federal Chief AI Officers, coordination, and standards:

• Establishment of an AI community of practice across federal agencies

• Regular reporting on agency AI use and risks

• Development of shared standards

What it means for you: There's a community of AI governance experts across government. Your agency's Chief AI Officer should be part of this network. Knowledge and lessons are shared.

OMB M-25-21 and M-25-22 (Expected 2025)

These are forward-looking memoranda addressing:

• Emerging risks: Like prompt injection, model manipulation, and supply chain security

• Responsible AI innovation: Encouraging agencies to pilot new uses while maintaining safeguards

• International coordination: Alignment with other democracies on AI governance

What it means for you: Government is being thoughtful about both adopting AI and protecting against AI-related threats.

Non-Federal Context

While this course focuses on federal government, state and local governments have their own AI policies:

• California: Leading state-level AI governance. Proposed regulations on high-risk AI.

• EU: AI Act (2024-2025) will regulate AI sold to government. Stricter than federal US policy.

• NIST AI Risk Management Framework (AI RMF 1.0): Not a mandate, but a standard that federal and many state agencies align with. Provides structure for risk assessment.

What This Policy Means in Practice

If your agency proposes a new AI system:

• Chief AI Officer reviews and approves

• If high-impact (affecting federal benefits, civil rights, etc.):

• Impact assessment required

• Bias testing required

• Public notification required

• Human review required

• Ongoing monitoring required

• Annual reporting to OMB

If you identify an AI problem (biased outcomes, errors affecting people, security breaches):

• Report to your Chief AI Officer or equivalent

• Document the issue

• You have protections against retaliation (whistleblower protections)

If your agency is shadow-AIing (using unapproved AI tools):

• Not compliant with policy

• Puts the agency at risk

• Puts you personally at risk if sensitive data leaks

Anti-Patterns / Misuse Risks

Anti-Pattern 1: Governance Theater

Agencies conducting impact assessments just to check a box, not actually addressing risks. Lesson: Governance must be genuine.

Anti-Pattern 2: Avoiding Impact Assessments

Agencies deliberately classifying AI systems as "low-risk" to avoid impact assessment requirements. Lesson: Honesty about risk level is essential.

Anti-Pattern 3: No Appeals Process

Deploying AI-influenced decisions without meaningful appeals processes for people affected. Lesson: People harmed by AI decisions have a right to appeal.

Practice / Reflection Prompts

• Policy Mapping: Is your agency subject to these federal policies? If yes, who is your Chief AI Officer?

• Governance Audit: Does your agency have AI governance? If so, review it against OMB M-24-10. What's missing?

• Impact Assessment Exercise: If your agency were to deploy AI for a high-stakes decision, draft what the impact assessment should cover.

• Compliance Timeline: When do you need to be compliant with these policies? When should audits happen?

• Accountability Mechanism: If you identified an AI problem in your agency, what's the reporting process?

Key Takeaways

• Executive Order 14110 established the foundational framework for safe, secure, trustworthy AI in government.

• OMB M-24-10 is mandatory operational guidance requiring governance, impact assessments, and transparency for high-risk AI.

• Chief AI Officers are now required in federal agencies and responsible for oversight.

• Impact assessments, bias testing, and human review are now mandatory for high-impact AI systems.

• Public notification is required when AI influences decisions about federal benefits, civil rights, or safety.

• Agencies must have appeals processes for people affected by AI-influenced decisions.

• Non-compliance can result in audit findings, loss of funding, and reputational damage.

Terms / Glossary Items

Impact Assessment: Documentation of what an AI system does, its risks, testing, and safeguards. Required before deployment of high-impact systems.

Chief AI Officer: Designated leader responsible for AI governance in a federal agency.

High-Impact AI: AI systems affecting federal benefits, civil rights, civil liberties, or safety. Subject to strongest requirements.

Human Review: Requirement that humans examine AI decisions before they're final for high-impact cases.

Compliance: Meeting regulatory requirements.

Bias Testing: Systematic evaluation of whether an AI system performs differently for different demographic groups.

Public Notification: Requirement to inform citizens when AI is influencing decisions about them.

You now know the policy framework. When your agency makes decisions about AI, this framework applies. Use it. Reference it. Hold your agency accountable to it.

Next: specific principles that translate policy into values. The "Blueprint for an AI Bill of Rights."

Find your agency's Chief AI Officer or AI governance point of contact. If they don't exist, that's a problem. Draft an email asking about your agency's AI governance structure.

Policy is how principles become mandatory. These policies exist because past mistakes taught hard lessons.

Understanding policy helps you navigate AI adoption responsibly.

Next: the values underneath the policy.

Government AI CLUB Certification Program

Level 1: AI Aware | Government AI Policy Landscape | Lecture 1.2.1

A GOVT.CLUB initiative.

<- 1.1.6 The AI Timeline: Expert Systems to LLMs 1.2.2 Data Sensitivity and Classification ->

Start Your CLUB Certification

This lecture is part of L1: AI Aware—8 hours of comprehensive government AI training.

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Related Lectures

L1 1.2.2—Data Sensitivity and Classification 15 min - Video + Checklist

L1 1.2.3—PII and AI: The Bright Red Lines 15 min - Video + Scenarios

L1 1.2.4—The Blueprint for an AI Bill of Rights 20 min - Video + Reading

Frequently Asked Questions

What will I learn in Government AI Policy Landscape?

In this 20 min video + reading lecture, you will Executive Orders (14110, 14179), OMB M-24-10, M-24-18, M-25-21, M-25-22. What they mean for your daily work

What level is Government AI Policy Landscape?

This is a Level 1 (AI Aware) lecture, part of Chapter 1.2 \u2014 Responsible AI Use. It is designed for all government employees.

How long is lecture 1.2.1?

Lecture 1.2.1 (Government AI Policy Landscape) takes 20 min. It is delivered as a video + reading format.

Do I need prerequisites for Government AI Policy Landscape?

This lecture is part of L1 (AI Aware). Prerequisites: None.

What is the CLUB Certification?

CLUB (Community Leading Unified Benchmarks) is a maturity-based AI certification for government professionals with 5 levels (L1-L5), 215 lectures, and 25 chapters aligned with NIST AI RMF, OMB, and GAO frameworks.