How State Leaders Can Put People First in AI Decision-Making is a framework to ask and answer the right foundational questions about artificial intelligence (AI) from the beginning. The public wants the government to take action to ensure the power of AI technology is used for good. In the current political climate, the work of state leaders is critical. The recommendations in this memo are focused on helping state leaders across the country ground decision-making about AI use in fairness, accountability, evidence-based inquiry, and inclusive governance so that AI can work for people.
Many state agencies have already deployed or are considering using AI in consequential decisions related to healthcare, housing, education, policing, finance, and other highly sensitive areas. While a few states have taken steps to implement decision-making mechanisms for certain AI systems, too many leaders are simply accepting narratives about AI’s purported public benefit at face value – jumping to the “how” of AI implementation before thoroughly vetting potential systems and deciding whether they are appropriate to use at all.
State officials may be eager, and even feel pressure, to tap into the potential benefits of AI in the hopes of better serving their constituents. But the personal, political, and operational risks of AI use should not be underestimated. People across the political spectrum are deeply concerned about the impact of AI on their lives and these concerns are well-founded. There have already been numerous examples where the failure to center people in AI decision-making and use has resulted in government systems that range from inefficient and wasteful to disruptive and downright dangerous, causing significant harm to, and backlash from, community members.
For AI’s potential benefits to be realized, state leaders need to implement consistent, inclusive people-first AI decision-making structures. Crucially, this process should ask the foundational question of whether to use AI in the first place. This policy memo provides timely guidance on:
Rather than offering a one-size-fits-all approach, this memo provides a suite of mechanisms for engaging thoughtful AI decision-making with examples of how different state governments have tackled emerging AI issues. We give recommendations for how state leaders can implement the AI decision-making process for whichever path they choose, including methods to promote accountability so that the decision-making process is followed and can truly work to put people first.
The use of AI by state agencies is growing. By 2024, 59% of state and local government employees reported that their agency had already made an AI application available for use and a majority of public sector employees reported using AI applications either several times a week or daily.
Generative AI (GenAI) systems and agentic AI systems are now joining machine learning and automated decision-making systems (ADS) that have been in use for many years – with the lines between the types of systems blurring as AI products become increasingly integrated.
AI is also being applied in many high-stakes situations where mistakes or bias can have life-altering ramifications. AI systems now make decisions that can affect the lives of tens of millions of low-income people in the United States, from determination of SNAP benefits, to Medicaid enrollment, to Social Security disability payments. Sixty percent of people in the United States live in a jurisdiction that employs some sort of pretrial risk assessment tool that uses AI. According to one AI surveillance vendor, thousands of police departments in the United States are using face surveillance.
While many policymakers may be enticed by the promise of AI, people across the country and political spectrum have deep concerns. As of 2025, only 17% of the general public believes AI will positively impact the United States. Americans broadly oppose AI being used in high-stakes decision-making, like health insurance, loan applications, and job screening. A 2025 poll of U.S. voters found that 82% said they do not trust technology leaders to tackle regulation independently. A supermajority – 69% – of the U.S. public does not think the government is doing enough to regulate AI.
More than 50% of people in the U.S, and 65% of low-income people, fear being left behind by AI. Only 4 in 10 people ages 18-34 in the U.S. say that they “trust” AI and only 23% of people in the U.S. over age 55 trust AI systems. As AI advances, public anxiety grows. Polling reveals that 77% of people in the U.S. want companies to “take AI creation slowly to get it right the first time.”
Public concerns with AI are well-founded. Former high-profile staffers at several AI companies have warned that companies are moving too fast and minimizing AI’s deficiencies, with new AI systems “generating more errors, not fewer.” While the technology industry is pushing the pedal on AI, the public would like to hit the brakes and for leaders to “do something before it goes too far.”
In the rush to adopt AI, some government officials have been making mistakes. The most impacted communities, including low income and communities of color, often end up excluded from public deliberation about government use of technology. There are already numerous examples of how these same communities bear the brunt when there is a lack of people-centered AI decision-making:
There are high costs for improper AI use – for the people whose lives are impacted, in the state dollars that are invested, and in how these actions can further undermine trust in government.
At their best, AI systems can help improve government functions. They have the potential to be used to triage community feedback, provide translation services that make government more accessible, facilitate emergency preparedness, or aid scientific research, among other uses. For example, Maryland’s Department of Labor is partnering with academic researchers to help test how AI can train staff and assist caseworkers with compliance regulations and other complex paperwork.
People want government leaders to take action to ensure AI technology is used for the public good. As the current administration has undermined safeguards at the federal level and issued executive orders attempting to stifle state action on AI, the continuing work of state leaders to safeguard rights and center people in AI decision-making has become even more critical.
A few states have already taken some steps to implement process mechanisms for AI decision-making and potential use. These include: Connecticut’s Act Concerning Artificial Intelligence, Automated Decision-Making and Personal Data Privacy and AI Responsible Use Framework; California’s State Guidelines for Evaluating Impacts of Generative AI on Vulnerable and Marginalized Communities; Maryland’s Responsible AI Policy; New York State’s 2024 LOADinG Act; and Texas’ Responsible Artificial Intelligence Governance Act.
While these steps are an important start, more needs to be done given what is at stake with AI use and its potential impact on people’s rights, livelihoods, and personal safety. For the potential benefits of AI to actually be realized for community members, strong state leadership in this moment is needed to pierce through the hype. This memo lays out a plan of action for state leaders to implement consistent, inclusive people-first AI decision-making structures that do not skip over the foundational questions of why and whether to use AI in the first place.
State leaders should establish a people-centered decision-making process that consistently and thoughtfully considers why and whether to use AI before jumping to use policies or other safeguards. This process should be followed whenever a state is considering the acquisition or use of an artificial intelligence system, whether through formal procurement, partnerships, in-kind donations, or other means. This decision-making process should be utilized when considering any AI system that has the potential to impact people’s rights, opportunity, well-being, safety, and security.
In the following section we provide:
State leaders should ensure that the first step in decision-making about any existing or potential use of an AI system is for an agency to articulate a specific and inclusive “why” that centers the interests and voices of a wide range of community members. Particular attention should be paid to historically marginalized communities. This community engagement should happen pre-procurement or use of any AI system.
Key considerations for centering diverse community members include, but are not limited to:
Inclusivity and representation: Use multiple strategies to support participation from diverse stakeholders, including funding and support for state agency outreach. Develop potential partnerships with trusted local organizations such as community groups, faith-based organizations, schools, and neighborhood associations who can help spread the word, organize meetings, and share information and surveys with diverse community members.
Accessibility: Make it possible for diverse community members to be actively engaged through a combination of in-person and remote engagement mechanisms. Also provide asynchronous paper and online surveys distributed in multiple languages in easy-to-understand formats. Information about any proposed AI systems should describe how a system would work and what it would do in ways that the general public can understand. Schedule any in-person meetings in places and times when diverse community members will be able to attend and provide necessary support for participation, like childcare and transportation. Remote meetings should also be scheduled at a time in the day when working people and people with families can attend.
Power sharing: Centering diverse voices means meaningful collaboration, not token consultation. Community members should have genuine influence on determining what are the most important issues facing them and how they should be addressed. You should listen to community members about any non-AI solutions that they would prefer and why.
Transparency and Accountability: Be clear about the engagement process and ensure it allows for serial feedback. Make sure materials are publicly published and easily accessible on a government website in a timely manner to allow public engagement with the process. Articulate how community input will be incorporated and have a mechanism to report back to the community on how their input influenced the ultimate decision.
California took important steps to promote effective community consultation when it issued the State Guidelines for Evaluating Impacts of Generative AI on Vulnerable and Marginalized Communities. Authored by the state Government Operations Agency, Office of Data and Innovation, and California Department of Technology, the guidelines recognize the need for a systematic approach that leads with meaningful engagement with diverse communities and how critical it is to specifically consider potential impacts on vulnerable and marginalized communities. Appendix B of California’s guidelines provides some additional helpful guidance on key principles, structures, activities, and focus questions for community consultation.
Technology vendors often tout the benefits and downplay costs and risks. It is crucial that amidst the hype state leaders create the structures and processes to support evidence-based decisions about a potential system’s public benefit and risks and avoid AI “snake oil” that wastes state resources and does more harm than good.
State leaders should ensure that there is an AI Impact Assessment (AIIA) to evaluate and explain how the proposed AI system will work, the evidence for its effectiveness and potential public benefit, and its potential for harm (for implementation advice, see below section, “Mechanisms to Operationalize People-Centered AI Decision-Making”). The process should include a public comment period for engagement with the AIIA so people can bring up additional information and concerns. Leaders should also ensure that any company they potentially contract with provides them with the necessary information to conduct an AIIA. Don’t let vendor claims, including claims about potential trade secrets, prevent meaningful review of its products and services.
An AI Impact Assessment (AIIA) should include:
Decisions about why and how to deploy AI should be driven by the real needs and interests of impacted communities. Using the AI Impact Assessment and the input and preferences of potentially impacted communities, the agency or department should apply a public benefit standard, assessing whether such a purpose for the AI has been demonstrated and whether the evidence-based benefits of the particular use of AI substantially outweigh the potential harms.
This decision-making standard should give strong weight to the opinions of those who will be impacted by the technology, especially historically marginalized communities. Steps to accomplish this include:
Decisions should clearly articulate what quantitative and qualitative evidence was relied on for the decision. These considerations should be memorialized in a publicly accessible document.
If a state entity moves forward with use of a particular AI system, state leaders should require timely review that centers impacted communities in the qualitative and quantitative evaluation of whether the system is achieving the intended public benefit. This review should also identify any harms arising from the AI use. If public benefits of the particular use of AI do not continue to substantially outweigh the harms, the AI use should end.
The review and evaluation processes should ensure:
Putting people first in AI also means proactively prohibiting uses of AI systems and applications that are simply incompatible with democratic, civil, and human rights. Numerous evaluations from government leaders, academics, technologists, civil rights organizations, and groups representing vulnerable and marginalized communities have found that the threats stemming from the below applications of AI significantly outweigh the benefits. Your AI decision-making process should preclude the following:
Many prudent city and state government officials have already preemptively taken some dangerous AI uses off the table. Maryland’s AI policy prohibits AI that violates fundamental rights, such as social scoring and emotional recognition. Montana’s AI law bans using AI for cognitive behavioral manipulation and sets hard limits on dragnet mass surveillance. And many cities have prohibited government use of face surveillance.
How to best implement the AI decision-making framework depends on the particular needs, opportunities, and structure of each state government. States that have taken steps to create a consistent process for AI evaluation and adoption have done so through different legal and legislative mechanisms. Which option to pursue – executive action, legislation, agency guidelines, or a combination of the three – is a decision that should be made by those most familiar with the contours of their particular state.
Executive Action – A Governor can issue an executive order requiring all executive agencies to follow a people-centered AI decision-making process. This executive order can identify an agency, or a subset of existing agencies, to develop the process itself and coordinate among different department leaders and staff to provide expertise and oversight that ensures compliance. If relying on an existing agency or state department, state leaders may find that an agency or department already focused on technology, information services, operations, or administrative service might be most well-suited to this role. Or an executive order can create a new entity to provide support.
Legislation – State lawmakers can enact legislation to require state entities to create and follow an AI decision-making process, either through direct statutory language or by tasking a state agency to develop policy and implementation guidelines.
State leaders should ensure that there are structures to support state agencies to operationalize the people-centered decision-making process, including conducting diverse community outreach, evidence-based AI Impact Assessment, and quantitative and qualitative evaluation.
This support can come from a variety of sources. State leaders should provide funding for existing staff or agencies to serve as point people, creating a diverse AI board, partnering with academic institutions to provide expertise, or a combination of these strategies.
It is also essential for state leaders to make sure the decision-making process does not just work on paper, but truly translates into people-centered transparency, accountability, and oversight of AI systems.
Any legislation, executive order, or agency guidelines should provide for public and private enforcement mechanisms so people can take action if rules are not followed. State leaders should also require a public inventory, updated at least annually, of all AI systems so the public knows what is in use. As discussed earlier, all assessment materials need to be publicly published in a timely manner during the process.
After the decision-making process is completed, state leaders should ensure that any agency that moves forward with an AI system is required to establish a robust use policy that will help protect people from abuse, misuse, and mistakes, with ongoing evaluation of the benefits and harms of the AI system. Developing a robust use policy is outside the scope of this memo, but please see the FAQ section for some resources.
State leaders can make AI work for people.
The future of government use of AI is still being written, and state governments have a powerful role to play. What we do now will help determine whether the power of AI will work for or against people’s rights and dignity.
If AI is to serve rights, justice, and democracy, leaders at the state level must act to implement a people-first process that centers diverse community members and asks and answers foundational questions about “why” and “whether” to use AI before skipping to the “how” of AI implementation. The recommendations in this memo help state leaders meet this moment and ground decision-making about AI use in fairness, accountability, evidence-based inquiry, and inclusive governance.
There have already been marked gaps in how “high risk” is interpreted. California enacted a law mandating annual inventory reports on all high-risk automated decision systems in use by the state. The report that the California Department of Technology issued identified no high-risk systems in use, despite publicly available examples of potentially worrisome ADS systems employed by different California agencies.
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