A Public-Interest Evaluation and Governance System for Ethical and Safe AI
The AI Ethics Index is a standards-based, evidence-driven system for assessing the ethical integrity, safety, and societal impact of AI systems. It enables rigorous evaluation today, and establishes the foundation for audit, certification, procurement guidance, and long-term governance tomorrow.
Society still lacks the public infrastructure needed to evaluate how these systems behave
Artificial intelligence is rapidly becoming embedded in the core systems that shape daily life: education, healthcare, public benefits, employment, justice, and civic decision-making. Yet society still lacks the public infrastructure needed to evaluate how these systems behave, whom they benefit, and where they create harm.
As a result, governments, institutions, and communities are making high-stakes decisions without the evidence required to protect the public.
The AI Ethics Index was created to fill this structural gap
It provides a unified, testable, and transparent framework for evaluating AI across ethical, safety, technical, and societal dimensions, something that does not currently exist in the public-interest domain. The Index offers institutions a credible way to:
- Assess risk and reduce harm
- Strengthen public trust
- Meet emerging regulatory expectations
- Guide procurement and governance
- Align AI systems with long-term individual and societal wellbeing
The systems shaping daily life
Documented harms in current AI systems
01AI Companions and Youth Mental Health Risk
Conversational AIs marketed as “companions” or “friends” are being used by minors in moments of loneliness, distress, or emotional crisis. These systems are not clinically trained, cannot assess suicidal intent, and lack the contextual understanding required to recognize when a young person is in danger. When a teenager substitutes AI for human support, the consequences can be severe.
Why this matters: These failures indicate structural safety gaps: emotionally persuasive systems with no clinical oversight, no context awareness, and no accountability when interacting with vulnerable youths.
02Epistemological and Psychological Risk from AI-Generated Distortion
Many users now rely on AI systems as sources of “truth,” emotional guidance, or practical advice. When these systems hallucinate, validate delusional thinking, or provide unsafe advice, the result can be gradual psychological destabilization rather than a single catastrophic event. These harms are diffuse, slow to detect, and poorly captured by existing safety benchmarks.
Why this matters: AI-generated distortion is a form of infrastructure-level epistemic risk, a gradual erosion of users’ ability to distinguish grounded reality from machine-generated inference. These harms are measurable only when we evaluate systems across human-AI interaction, psychological safety, and knowledge integrity.
03Institutional and Systemic Harm in Hiring, Healthcare, and Public Services
AI systems deployed inside institutions have a magnified impact. Decisions about hiring, insurance coverage, public benefits, or eligibility determinations affect millions, and when bias or error exists, it becomes a systemic failure, not an individual glitch. These systems are often proprietary and opaque, leaving the public with no visibility into how decisions are made.
Why this matters: When AI becomes the default mechanism for institutional decision-making, bias and error scale across entire populations. Without public-interest evaluation, there is no mechanism to verify fairness, understand model behavior, or ensure recourse for individuals impacted by automated decisions.
Nine canonical dimensions
The AIEI evaluates AI systems across nine canonical dimensions that reflect the full lifecycle of development, deployment, and societal impact. These dimensions form the core architecture for model evaluation, organizational assessments, audit readiness, and eventual certification.
Model Design and Development
Assesses whether the system’s objectives, assumptions, and constraints are clearly articulated, justified, and appropriate for the intended use and societal context.
Fairness
Evaluates disparate impact, representational harms, and structural biases using quantitative tests and contextual analysis.
Privacy & Data Stewardship
Examines data provenance, collection practices, consent pathways, retention policies, and risks of re-identification or exposure.
Transparency
Measures the clarity, completeness, and accessibility of documentation, disclosures, interpretability tools, and known limitations.
Knowledge & Attribution
Evaluates factual accuracy, error modes, hallucination profiles, citation reliability, and the system’s capacity to differentiate fact from inference.
Human–AI Interaction
Assesses usability, clarity of affordances, risk of misuse or over-reliance, and differential effects across user groups.
Safety & Security
Tests adversarial resilience, jailbreak resistance, harmful content refusal, robustness under stress conditions, and safe-failure behavior.
Societal Impact
Evaluates downstream and second-order effects on communities, institutions, equity, labor, democratic trust, and public wellbeing.
Governance & Accountability
Assesses internal governance structures, documentation practices, incident response, versioning, and mechanisms for redress.
It is built as shared civic infrastructure, a system designed for public benefit, not private advantage.
A unified structure that synthesizes the most credible guidance available
The AI Ethics Index is designed to align with leading frameworks for responsible, safe, and transparent AI development. Rather than introducing competing standards, the Index provides a unified structure that synthesizes and operationalizes the most credible guidance available.
The Index incorporates alignment with these standards into a broader ethical and societal framework, offering contextual interpretation that single benchmarks cannot capture.
The people developing the Index
Core Team
Ethicists, technologists, computational social scientists, simulation experts, and AI safety researchers developing the Index.
Technical Contributors
Engineers and evaluators responsible for building the testing infrastructure, evidence pipelines, and measurement tools.
Advisory Group
Independent experts spanning safety science, ethics, security, education, global policy, and civil society.
Build the Future of Ethical and Safe AI With Us
We are seeking partners across sectors, philanthropy, research, government, and industry, to support the development and deployment of the AI Ethics Index as public-interest infrastructure.
About Just Horizons Alliance
The AI Ethics Index is an initiative of the Just Horizons Alliance, a 501(c)(3) public charity advancing responsible, human-centered innovation. Our work spans AI ethics, computational social science, simulation modeling, and the design of systems that strengthen human dignity, equity, and societal wellbeing.
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