These ideas aim to advance the detailed policy solutions needed to foster public trust and implement fairness in the adoption of AI across diverse domains, from healthcare and government benefits to rural access, education, and worker protections.
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.
When properly structured — with specific numeric targets, secured financial obligations, independent monitoring, and meaningful enforcement — CBAs transform data center deals into durable community partnerships.
Protecting the public from the tech industry’s predatory business models and the next wave of AI harms is an enormous challenge, but we have the evidence that trying to build a healthier digital culture is absolutely worth the effort.
Opaque and insufficiently tested tools are increasingly shaping student outcomes without consistent transparency, civil rights review, or technical safeguards. States and the U.S. Department of Education can address these risks using procurement and oversight tools already within their authority.
Too often, affected patients, clinicians, and regulators cannot see how the system works, why a decision was made, or whether meaningful human oversight occurred.
Existing tools from other domains, such as existing robust public engagement processes in drug development, when applied to AI deployment can help strengthen public trust in these systems and enhance perceptions of their legitimacy and the decisions they produce.
With thoughtful policy action, it is still possible to build systems that are fair, transparent, and accountable, and to earn the public trust that will ultimately determine AI’s future. We hope policymakers are ready to act.
Responsible AI starts with who is in the data, who is at the table, whose needs shape the outcome, and who is responsible when it falls short.
As states take up AI regulation, they must prioritize transparency and build technical capacity to ensure effective governance and build public trust.
In the absence of guardrails and guidance, AI can increase inequities, introduce bias, spread misinformation, and risk data security for schools and students alike.
tudents in the 21st century need strong critical thinking skills like reasoning, questioning, and problem-solving, before they can meaningfully engage with more advanced domains like digital, data, or AI literacy.