FAVES AI Ethics Framework

A FAVES AI Ethics Framework is a healthcare-focused principle-based responsible ai governance framework that can support ethical ai deployment tasks.

• AKA: Fair-Appropriate-Valid-Effective-Safe Framework, FAVES Principles, FAVES AI Guidelines.
• Context:
  • It can (typically) ensure AI Fairness through bias detection mechanisms.
  • It can (typically) verify AI Appropriateness via use case evaluations.
  • It can (typically) establish AI Validity using validation methodologys.
  • It can (typically) measure AI Effectiveness through outcome assessments.
  • It can (typically) guarantee AI Safety via risk mitigation protocols.
  • ...
  • It can (often) guide Healthcare AI Development through ethical design principles.
  • It can (often) inform AI Governance Policy via structured frameworks.
  • It can (often) support AI Audit Processes using assessment criteria.
  • It can (often) facilitate Stakeholder Communication through shared vocabulary.
  • ...
  • It can range from being a High-Level FAVES AI Ethics Framework to being a Detailed FAVES AI Ethics Framework, depending on its implementation specificity.
  • It can range from being a Domain-Specific FAVES AI Ethics Framework to being a General-Purpose FAVES AI Ethics Framework, depending on its application scope.
  • ...
  • It can incorporate Fairness Metrics for bias quantification.
  • It can define Appropriateness Criteria for use case selection.
  • It can establish Validity Thresholds for model acceptance.
  • It can specify Effectiveness Indicators for performance monitoring.
  • It can implement Safety Guardrails for risk prevention.
  • ...
  • It can be Healthcare Industry Adopted demonstrating sector relevance.
  • It can be Regulatory Aligned supporting compliance requirements.
  • It can be Stakeholder Endorsed indicating broad acceptance.
  • ...
• Examples:
  • FAVES Framework for Clinical Decision Support ensuring ethical diagnostic ai.
  • FAVES Framework for Drug Discovery guiding responsible pharmaceutical ai.
  • FAVES Framework for Patient Monitoring governing safe health tracking ai.
  • ...
• Counter-Examples:
  • Generic AI Ethics Principles, which lack healthcare-specific considerations.
  • Technical-Only AI Guidelines, which miss ethical dimensions.
  • Post-Hoc Ethics Review, which lacks proactive governance.
• See: AI Ethics, Responsible AI, Healthcare AI Governance, AI Bias Mitigation, AI Safety Framework, Ethical AI Development, AI Accountability, Healthcare Technology Ethics, AI Risk Management, Trustworthy AI.

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