The Trump Administration’s recent release of its comprehensive AI Action Plan and three accompanying executive orders has generated significant attention across the AI governance landscape. While much of the initial media coverage has focused on headlines about deregulation and “anti-woke” measures, a closer examination of the specific language and requirements reveals a more complicated picture for criminal justice.
The coming months will be critical as implementation details emerge. Stakeholders should monitor agency responses and look for opportunities to engage constructively in shaping how these broad principles translate into practical requirements for criminal justice AI systems.
What Was Released
The administration unveiled a comprehensive 23-page AI Action Plan seeking to accelerate AI innovation, build American AI infrastructure, and lead international AI diplomacy and security, alongside three executive orders:
- Promoting Export of American AI Technology – establishing federal support for AI industry exports
- Accelerating Federal Permitting of Data Center Infrastructure – streamlining AI infrastructure development
- Preventing Woke AI in Federal Government – mandating procurement of “unbiased” AI systems.
Some Critical Ambiguities
The plan contains several underspecified goals, creating both risks and opportunities for thoughtful engagement. Key terms like “American leadership,” “truth-seeking,” “unbiased,” and “burdensome regulations” lack clear operational definitions, leaving their implementation open to interpretation.
The documents themselves reveal significant internal tension. In some places, they suggest disincentivizing regulatory oversight altogether. For example, the Action Plan declares that “AI is far too important to smother in bureaucracy at this early stage” and calls for agencies to “consider a state’s AI regulatory climate when making funding decisions and limit funding if the state’s AI regulatory regimes may hinder the effectiveness of that funding.” At the event announcing these policy plans, President Trump said, “America must once again be a country where innovators are rewarded with a green light, not strangled with red tape so they can’t move, so they can’t breathe.”
But in other sections, the documents emphasize the need for robust safeguards and evaluation systems. The Action Plan calls for agencies to “invest in AI interpretability, control, and robustness breakthroughs” and “evaluate frontier AI systems for national security risks in partnership with frontier AI developers.” The plan also dedicates significant attention to “building an AI evaluations ecosystem” with standards, testing, and robust evaluation frameworks.
This creates space for two competing interpretations:
Interpretation 1 (Concerning): The plan aims to remove all barriers to AI deployment, treating any governance framework as an impediment to innovation while privileging a particular viewpoint and using speed of deployment as the primary success metric.
Interpretation 2 (Constructive): The plan seeks to ensure U.S. AI systems are the most powerful, safe, secure, fair, and reliable globally, using thoughtful guardrails to enhance democratic accountability through superior quality and trustworthiness.
The positive reception from both AI safety advocates and industry accelerationists suggests the plan is meaningfully uncertain. Whether this represents genuine policy balance remains to be determined through implementation.
Criminal Justice Implications
Several aspects of the plan directly impact criminal justice AI governance:
Federal Procurement Standards
The “Preventing Woke AI” executive order affects how federal agencies procure AI systems, requiring they be “truthful” and “ideologically neutral.” The executive order seems to allow for transparency measures to satisfy the “Unbiased AI” requirements, rather than positive proof of a particular ideological viewpoint or training methodology. How these requirements are interpreted will be very important in criminal justice contexts where substantial empirical research has documented disparities, inequities, and concerns about AI system fairness.
Funding Leverage
The Action Plan recommends limiting AI-related funding “if the state’s AI regulatory regimes may hinder the effectiveness of that funding.” The critical question of how “effectiveness” gets defined remains unanswered and will significantly impact state and local jurisdictions.
Standards Development Opportunities
The plan calls for NIST to launch domain-specific efforts to accelerate national standards development. While criminal justice isn’t explicitly mentioned, this creates an opening for advocating its inclusion as a priority domain.
Deepfake Evidence Standards
The plan directly addresses synthetic media concerns, directing NIST to develop formal guidelines for deepfake evaluation and DOJ to issue guidance on adopting standards for computer-generated or other electronic evidence.
Moving Forward
The plan includes some language that seems dismissive of concerns about responsibility, safety, and reliability, but there are notable gaps between the slogans and specific policy recommendations. The documents accommodate interpretations focused on American AI leadership through robust standards, evaluation frameworks, and safe and reliable systems.
For criminal justice practitioners, this creates both challenges and opportunities. There’s a narrow window to influence how these goals are operationalized, particularly in demonstrating that responsible AI governance can serve federal objectives better than a “move fast and break things” approach.
States and localities will need guidance on navigating federal requirements while ensuring they don’t deploy AI systems that are biased, unreliable, or violate rights. AI governance approaches that are clear-eyed about risks around discrimination, civil and human rights violations, and democratic control in the criminal justice can align with the federal objectives. A key challenge is now demonstrating that fair, safe, and reliable systems are necessary in order to actually elicit technological progress and leadership.
This analysis reflects initial interpretations of recently released documents. As implementation guidance develops, continued monitoring and engagement will be essential to understand the full implications for criminal justice AI governance.
