AI Ethics Framework Library
The comprehensive resource for choosing and applying ethical frameworks to AI systems.
IntentBound
The control layer for autonomous AI. Explicit constraints through declared intent, authorization boundaries, drift detection, and verification gates.
Utilitarian AI Ethics
Maximize overall wellbeing and minimize harm. AI decisions evaluated by their consequences for the greatest number of people.
Deontological AI Ethics
Rules and duties guide AI behavior regardless of outcomes. Certain actions are inherently right or wrong.
Virtue Ethics for AI
Focus on cultivating good character in AI systems. What traits should AI embody? Honesty, fairness, wisdom, courage.
Care Ethics in AI
Relationships, context, and particular needs matter. AI should attend to vulnerability and respond to specific circumstances.
Rights-Based Frameworks
Fundamental rights must be protected: privacy, autonomy, non-discrimination, dignity. AI cannot violate these regardless of benefits.
Capabilities Approach
AI should enhance human capabilities and freedoms, not diminish them. Focus on what people are able to do and be.
Environmental AI Ethics
Account for AI's environmental impact: energy consumption, carbon footprint, resource use, e-waste.
Indigenous AI Ethics
Relationality, sovereignty, and collective rights. Data as sacred. Community consent and benefit.
Consequentialist Approaches
Actions judged solely by outcomes. Flexible, pragmatic, optimization-focused. Foundation for RL reward functions.
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