Build responsibility into problem validation, data rights, product testing, user remedies, and launch decisions from the start.
Mississippi communities do not have identical needs, infrastructure, histories, or access. Use the evidence and tools as a starting point, then let local people shape the purpose, examples, pace, safeguards, and measures of success.
Does this problem genuinely require AI?
Who could be misrepresented, excluded, or harmed?
Do we have rights to every dataset and content source?
How will representative users test likely failures?
What incident, remedy, or result would require delaying launch?
The primary sources converge on three duties: test risk throughout the product lifecycle, understand rights in training data and outputs, and support every public claim with evidence.
National Institute of Standards and Technology
NIST turns risk principles into actions across governance, context mapping, measurement, management, monitoring, and decommissioning.
We use it to structure the product checklist, impact assessment, representative testing, launch threshold, and incident plan.
U.S. Copyright Office
The Copyright Office is examining digital replicas, the copyrightability of AI-generated outputs, and the use of copyrighted material in AI training.
We use it to require documented data and content rights, careful ownership claims, and qualified review when the product depends on protected material.
Federal Trade Commission
The FTC warns that existing law still applies to automated systems and that companies must not make unsupported performance claims or automate unlawful discrimination.
We use it to require evidence for product claims, testing across affected groups, honest limitations, and remedies for customers.
Sources and requirements can change. Check the publication date, read the original material, and confirm the rules that apply locally before making a consequential decision.
Use these four areas to challenge the problem, data, product behavior, and launch plan before customers carry the risk.
Establish the user need before choosing AI. Compare the proposed system with simpler workflows and non-AI product approaches.
Name intended users, non-users who may still be affected, likely inaccuracies, discriminatory outcomes, abuse cases, privacy failures, and unsafe reliance.
Record rights, licenses, consent, sensitive information, third-party content, intellectual property, and every external model or service dependency.
Evaluate with representative users, especially people likely to be underserved. Explain material limitations and do not claim objectivity, reliability, or guaranteed performance without evidence.
Define incident reporting, human escalation, correction, user notice, rollback, compensation or other remedies, and the conditions that stop or delay release.
✓ A bounded prototype that tests one risky assumption
✓ User research with transparent mock outputs
✓ Documented evaluation before expanding access
× Treating a polished demo as evidence of safety or demand
× Making unsupported claims of objectivity or guaranteed performance
× Connecting an experimental agent to money or production systems
Use these tools in product reviews, customer discovery, investor conversations, and launch decisions.
Review the product from discovery through deployment.
Make the launch decision reviewable and evidence-based.
Prepare before a user reports harm.
Pressure-test a proposed AI product before launch.
Describe the product, intended user, and decision or action it influences.
Identify an inaccurate response, discriminatory result, privacy failure, and misuse case.
For each, name the affected person and severity of harm.
Add a safeguard, evaluation method, accountable owner, and user remedy.
Write one concrete condition that would delay or stop launch.
What evidence would make you confident enough to launch—and what evidence would tell you not to?
Innovate Mississippi works directly with technology entrepreneurs and emerging companies across the state.
Share the plan with the people responsible for the work and the people who may be affected. Confirm local rules, protect private information, and name the person who can answer questions or correct a problem.