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Ask candidates to name the rule they would support, the level of government that would enforce it, the agency or official responsible, and the public evidence that would show whether it worked. Broad promises about “responsible AI” are not enough. The questions below turn a campaign talking point into a testable policy position and make answers easier to compare.
Start with four follow-ups for every AI answer
Use the same four follow-ups regardless of the candidate’s party or preferred technology. They expose whether a proposal is operational or merely rhetorical.
- What would you do first? Ask for a specific bill, executive action, regulation, budget item, procurement rule, or agency instruction.
- Who would be responsible? The answer should identify Congress, a federal agency, state officials, local election administrators, courts, or another body rather than “government” in the abstract.
- Which systems and uses are covered? A rule for a chatbot is different from a rule for an eligibility decision, a campaign video, or an election database.
- What public evidence would show success or failure? Look for audits, incident reports, appeal outcomes, accuracy measures, civil-rights testing, security findings, or other information that the public could inspect.
Then ask what happens when the policy fails: who can investigate, how quickly can a system be paused or corrected, and what remedy is available to an affected person?
Rules and jurisdiction: who should make AI policy?
Federal rules versus state rules
Ask: “Which AI rules would you support at the federal level, and which should remain with states?” Follow up with: “If you want one national standard, what protections must it guarantee, and how would the public hold the federal government accountable?”
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This question is especially important after Executive Order 14365, dated December 11, 2025. The order directs federal actions toward a uniform national AI policy framework, including challenges to certain state laws, work on federal reporting and disclosure standards, and a legislative recommendation. It is an administration directive, not proof that Congress enacted a comprehensive federal AI statute. A candidate should explain the constitutional or statutory mechanism they would use and what role states would retain.
Ask for the legal status of the proposal
Use this follow-up: “Which specific law, executive action, or agency policy would you change or support, and what is its current legal status?” A candidate who cites an introduced bill should say that it is introduced; one who cites an executive order should distinguish an agency direction from a statute; and one who cites a court case should identify whether a decision is final, stayed, or limited to a particular jurisdiction.
Accountability for agencies and vendors
Ask: “What reporting, audits, and public records would your policy require from agencies and contractors?” A useful answer should cover procurement, testing before deployment, incident reporting, retention of decision records, and consequences for vendors that misrepresent system performance or conceal material failures.
Elections and democratic participation
Permitted uses inside election offices
Ask: “What uses of AI by election offices should be allowed, restricted, or prohibited?” Request examples such as translation, voter-information chat services, document processing, list maintenance, ballot design, risk analysis, or public communications. Ask whether a human must review an output before it affects a voter and whether officials must disclose that AI was used.
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The introduced Preparing Election Administrators for AI Act offers a concrete agenda for this discussion. Its text would direct the Election Assistance Commission, in consultation with the National Institute of Standards and Technology, to issue voluntary guidelines addressing benefits and risks, cybersecurity, accurate election information, and AI-generated disinformation. It also proposes a study of AI use and impacts in the 2024 federal elections. The cited text is a proposal, not an enacted obligation; candidates should state whether they support it, would amend it, or would pursue a different approach.
Security and accurate election information
Ask: “How should election offices secure AI-assisted systems and correct inaccurate election information?” Press for operational details: access controls, vendor security requirements, independent testing, a process for taking a compromised system offline, and a public correction channel when an automated message gives voters wrong information. Ask how officials would distinguish a technical error from a coordinated disinformation campaign without suppressing lawful criticism.
Campaign media, labels, and enforcement
Ask: “Should campaigns disclose realistic AI-generated or materially altered political media? Who would enforce the rule, and what exceptions would protect satire, parody, and ordinary political speech?”
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Protecting the ability to form opinions freely
The Council of Europe convention on artificial intelligence frames democratic-process safeguards around institutional integrity, public participation, and people’s ability to form opinions freely. Its Article 5(2) states: “Each Party shall adopt or maintain measures that seek to protect its democratic processes in the context of activities within the lifecycle of artificial intelligence systems, including individuals’ fair access to and participation in public debate, as well as their ability to freely form opinions.” This is an international framework, not a US rule. Ask candidates which parts of that principle they would translate into domestic policy and how they would protect political expression while addressing manipulation.
Transparency: when should people be told AI is involved?
Notice during an interaction
Ask: “When should people be told that they are interacting with an AI system or viewing AI-generated or altered content?” The candidate should distinguish a low-stakes drafting aid from a system speaking directly to a constituent, making a recommendation about benefits, or generating a realistic image or voice of a public figure.
Disclosure standards and accessibility
Follow up: “What must a notice say, where must it appear, and how would it work for people using screen readers, translation services, or low-bandwidth connections?” Ask whether notices must identify the responsible organization, provide a way to reach a human, and remain available after content is shared or modified.
Use the EU as a clearly labeled comparison
European Commission guidance on Article 50 of the EU AI Act provides a comparison point: its transparency obligations apply from August 2, 2026, to specified providers and deployers within the European Union’s legal framework. That guidance does not govern US candidates, campaigns, or voters merely because it exists. Ask a US candidate whether they would adopt a similar disclosure requirement, a narrower one, or no mandatory label, and why their proposed scope would be workable.
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Privacy, civil rights, and discriminatory outcomes
Limits on data collection and use
Ask: “What personal data should AI systems be allowed to collect or use, for which purposes, and for how long?” Require a position on sensitive information, data purchased from brokers, biometric data, children’s information, and data gathered from public sources. Ask whether people could access, correct, delete, or challenge information used about them.
Testing for unequal effects
Ask: “How would you test for discriminatory outcomes, and what should happen when testing identifies them?” A meaningful answer addresses testing before deployment and after significant model or data changes, disaggregated results where lawful, independent review, documentation of known limitations, and a deadline for correction or suspension. Ask which civil-rights authority would investigate and whether affected people could obtain an explanation.
Reliability and context-specific safeguards
The Council of Europe convention identifies transparency and oversight, privacy and personal-data protection, equality and non-discrimination, and reliability as governance principles. It calls for safeguards tailored to the context and risks rather than a single rule for every system. Use that distinction in questioning: a public-facing translation tool, a hiring screen, and a criminal-justice risk assessment should not receive identical controls.
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High-impact decisions: oversight, appeals, and remedies
Human review before rights are affected
Ask: “Which AI uses in public services or decisions affecting people’s rights require meaningful human review?” Clarify whether the reviewer can reject the system’s recommendation, has enough time and information to do so, and must record the reason for the final decision. Ask whether some uses—such as fully automated denial of a benefit or liberty—would be prohibited.
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Monitoring throughout the system’s life
Ask: “Who should document and monitor risks after an AI system is deployed?” Look for named duties: maintaining a system inventory, tracking performance drift, logging incidents, reviewing vendor updates, publishing impact assessments, and notifying oversight bodies when a threshold is exceeded. Ask how often reports would be released and whether the public could inspect non-sensitive portions.
Explanation, appeal, correction, and compensation
Ask: “If an AI-assisted decision harms someone, what explanation, appeal, correction, or remedy should be available?” Candidates should address notice of the system’s role, access to relevant records, a human appeal route, deadlines, correction of inaccurate data, restoration of lost benefits where appropriate, and compensation or other relief when harm is established. The convention’s accountability and remedy provisions are useful comparison dimensions, but they do not themselves create a US legal right or remedy.
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Evidence before scaling
Ask: “Where should government adopt AI to improve services, and what evidence should be required before scaling a system?” Request a pilot plan, a baseline for comparison, measurable service goals, error tolerances, independent evaluation, and a stop or rollback condition. Ask whether the evidence must be published and who decides that a pilot has met its standard.
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Procurement safeguards
Ask: “What privacy, civil-rights, security, and procurement safeguards should apply when agencies buy or use AI?” Probe contract terms for data ownership, training-data restrictions, audit access, breach notification, model updates, subcontractors, accessibility, portability, and termination assistance. Ask how an agency could leave a vendor without losing records or becoming unable to operate a critical service.
Balancing speed with dependence and error
The White House announcement of April 7, 2025 described revised federal AI-use and procurement policies as encouraging adoption while maintaining protections for privacy, civil rights, and civil liberties. Those statements express the administration’s policy approach; they are not independent evidence that safeguards work in every deployment. Ask candidates what evidence they would require, how they would measure vendor dependence and error costs, and who could pause a system when protections prove inadequate.
How to compare candidates’ answers
Use the same scoring sheet for every candidate. Record the answer in the following dimensions rather than grading confidence or technical vocabulary.
| Comparison dimension | What to listen for |
|---|---|
| Level of government and legal mechanism | Federal statute, executive action, agency rule, state law, local policy, or a clearly stated division of authority. |
| Covered systems and uses | Specific technologies, decisions, sectors, campaigns, election offices, providers, deployers, or risk categories. |
| Transparency and notice | When notice is required, what it contains, where it appears, and how exceptions are handled. |
| Privacy and civil-rights safeguards | Data limits, impact testing, accessibility, nondiscrimination checks, and protection for sensitive groups. |
| Human oversight and appeal | Who reviews decisions, whether they can override the system, and how people challenge an outcome. |
| Election security and information integrity | Cybersecurity, correction procedures, campaign-media disclosure, enforcement, and speech protections. |
| Accountability and enforcement | Audits, records, incident reporting, penalties, responsible officials, and independent oversight. |
| Evidence of benefits and harms | Baseline measures, pilot results, error rates, disparate-impact findings, and a public timeline for review. |
For each answer, write down three final items: the first action, the accountable institution, and the evidence that would demonstrate success. If any of those is missing, ask the candidate to supply it before moving to the next topic.
Quick Recap
A compact question list for a town hall or debate
- Which AI rules belong at the federal level, and which should remain with states?
- What uses of AI by election offices would you allow, restrict, or prohibit?
- How would you secure AI-assisted election systems and correct inaccurate voter information?
- Should realistic AI-generated campaign media carry a disclosure, and who would enforce it?
- When must people be told they are interacting with AI or viewing altered content?
- What personal data may AI systems collect or use, and what rights would people have over it?
- How would you test for discriminatory outcomes, and what happens after a failed test?
- Which high-impact decisions require human review, and can the reviewer override the system?
- What explanation, appeal, correction, or remedy would be available after harmful AI-assisted decisions?
- What evidence must a government agency produce before expanding an AI pilot?
- What procurement terms would protect privacy, security, civil rights, and the public’s ability to change vendors?
- What would you do first, who would be responsible, and what public evidence would show whether it worked?
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