Responsible AI Use

Core Principles

• Alignment with human values and societal benefits
• Transparency and explainability of AI systems
• Fairness and mitigation of bias
• Accountability and oversight mechanisms

Key Challenges

• Balancing innovation with ethical considerations
• Ensuring cross-cultural applicability of AI ethics
• Addressing the “black box” problem in complex AI models
• Establishing clear legal frameworks for AI accountability

Implementation Strategies

• Developing sector-specific governance frameworks
• Integrating ethics into AI development lifecycle
• Creating interdisciplinary oversight bodies
• Promoting public awareness and literacy about AI

Related Concepts

• ai ethics
• ai-oversight
• ai regulation
• ai bias

Healthcare Applications

• New AI technologies are being rapidly adopted by healthcare professionals
• Existing organisational governance often lacks processes for safe and responsible use
• Previous frameworks focused on high-level ethics principles without practical implementation
• Need to translate principles into practice, assess risk, and embed AI oversight
• Study aimed to develop and validate a practice-oriented AI governance framework

Backlinks

• 2026 04 14 BMJ Review