Five Principles for Ethical AI Policy

As policymakers in Washington, Brussels, London, and at the UN grapple with how to govern artificial intelligence, they face a fundamental question: what values should guide our approach? At The ReformAItion Institute, we believe that ethically aligned AI policy must be grounded in principles that transcend partisan divides and reflect the inherent dignity of every human being.

These five principles, rooted in mainstream evangelical ethics but accessible to policymakers across the political spectrum, offer a framework for developing AI governance that serves the common good.

1. Imago Dei: Every Human Bears God's Image

The Principle: Human beings possess inherent, transcendent dignity that cannot be reduced to utility, productivity, or data points.

Policy Implications:

• Algorithmic Bias Prevention: AI systems must be designed and audited to prevent discrimination based on race, gender, disability, or socioeconomic status
• Data Rights: Personal data should be treated as an extension of personhood, not merely as a commodity
• Human-in-the-Loop Requirements: Critical decisions affecting human welfare (healthcare, criminal justice, employment) require meaningful human oversight
• Anti-Surveillance Protections: Restrictions on AI-powered surveillance systems that treat humans as subjects to be monitored and controlled

Example Legislation: Mandate algorithmic impact assessments for high-risk AI systems before deployment, similar to environmental impact statements.

2. Human Flourishing: Technology Must Serve the Common Good

The Principle: AI should enhance human capabilities, strengthen communities, and advance the common good rather than diminish human agency or fracture social bonds.

Policy Implications:

• Purpose-Driven Innovation: AI development incentivized toward solving pressing social challenges (disease, poverty, education) rather than purely profit-maximizing applications
• Community Impact Assessments: Major AI deployments should include public comment periods and community input mechanisms
• Democratic Access: Ensuring AI benefits are distributed equitably, not concentrated among the wealthy or powerful
• Quality of Life Metrics: AI policy success measured by human flourishing indicators, not just economic efficiency

Example Legislation: Create tax incentives for AI research addressing social determinants of health, climate adaptation, or educational access.

3. Stewardship: Responsible Development of Powerful Technologies

The Principle: Those who create and deploy AI systems have a moral obligation to ensure they are safe, reliable, and aligned with human values.

Policy Implications:

• Safety Testing Requirements: Mandatory evaluation of frontier AI systems for potential harms before public release
• Liability Frameworks: Clear accountability when AI systems cause harm, preventing manufacturers from hiding behind algorithmic complexity
• Transparency Standards: Public disclosure of training data sources, model capabilities, and known limitations
• Red-Teaming Mandates: Independent security researchers empowered to test AI systems for vulnerabilities

Example Legislation: Establish an AI Safety Institute (as the UK has done) with authority to evaluate advanced AI systems and recommend deployment restrictions.

4. Justice: Protecting Vulnerable Populations from AI Harms

The Principle: AI policy must prioritize protection of those least able to advocate for themselves—the poor, marginalized, elderly, disabled, and children.

Policy Implications:

• Vulnerable Population Protections: Special safeguards for AI systems affecting children, elderly, disabled individuals, or economically disadvantaged communities
• Global Impact Consideration: AI policy should account for exploitation risks in developing nations (data extraction, digital colonialism)
• Labor Protections: Worker retraining programs, transition support, and safety nets for AI-displaced workers
• Access to Justice: Legal aid and advocacy resources for those harmed by AI systems

Example Legislation: Prohibit use of AI systems in child welfare decisions without human social worker review, recognizing power imbalances.

5. Wisdom: Balancing Innovation with Prudence

The Principle: AI development should proceed with appropriate caution, recognizing both potential benefits and risks, avoiding both reckless acceleration and paralyzing fear.

Policy Implications:

• Risk-Proportionate Regulation: Light-touch oversight for low-risk applications, rigorous scrutiny for high-risk systems (autonomous weapons, critical infrastructure)
• Innovation Preservation: Avoid regulatory approaches that inadvertently concentrate AI power among a few large corporations
• International Cooperation: Coordinated governance frameworks across jurisdictions to prevent regulatory arbitrage
• Sunset and Review Clauses: Regular reassessment of AI policies as technology evolves

Example Legislation: Tiered regulatory framework distinguishing between consumer AI (chatbots), high-risk AI (hiring, credit), and critical AI (healthcare, criminal justice).

Putting Principles into Practice

These principles aren't abstract philosophy—they're actionable frameworks that can inform concrete policy decisions:

For Legislators: Use these principles to evaluate proposed AI bills. Does this legislation protect human dignity? Does it advance the common good? Does it hold AI developers accountable?

For Regulators: Design AI governance frameworks that balance innovation with safety, ensuring AI serves human flourishing rather than narrow commercial interests.

For Technologists: Build AI systems with these values embedded from the start, not as afterthoughts. Ethics isn't a constraint—it's a design requirement.

For Citizens: Demand that your representatives approach AI governance with wisdom, prioritizing human dignity and the common good over technological enthusiasm or corporate lobbying.

A Bipartisan Framework

Notably, these principles transcend traditional political divisions:

• Conservatives resonate with emphasis on human dignity, moral accountability, and protection of vulnerable populations
• Progressives align with focus on justice, equity, and preventing exploitation
• Libertarians appreciate innovation-enabling approaches and opposition to unchecked surveillance
• Communitarians value emphasis on common good and community impact

This bipartisan appeal is precisely why faith-informed policy frameworks are so valuable in today's polarized environment.

The Path Forward

Over the next three years (2026-2028), The ReformAItion Institute will work with lawmakers in the US, UK, EU, and UN to translate these principles into specific legislation and regulatory frameworks. Our Double Edged AI Study will provide the empirical foundation for policy recommendations grounded in these values.

The window for shaping foundational AI governance is narrow. Policy decisions made in 2025-2027 will determine whether AI serves human flourishing or becomes a tool of exploitation.

We invite policymakers, faith leaders, technologists, and concerned citizens to join us in this critical work.

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About The ReformAItion Institute: We advance ethically aligned, theologically sound AI policy that protects vulnerable populations and promotes human flourishing. Our work informs lawmakers in the US, UK, EU, and UN.

Get Involved: Support our policy development work or contact us to discuss partnerships and collaboration.