Which two principles are fundamental for trust in Singapore's AI governance framework?

The principles of being human-centric and explainable are foundational for trust in Singapore's AI governance framework. A human-centric approach means that AI systems are designed and implemented with the user in mind, ensuring that they enhance human capabilities and prioritize human welfare. It emphasizes the importance of considering the societal impact of AI technologies, addressing ethical concerns, and ensuring that systems serve the needs and values of people.

Explainability is equally critical, as it allows stakeholders to understand how AI systems make decisions. When users can comprehend the reasoning behind AI actions and outcomes, it fosters transparency and accountability, essential components for building trust. Without explainability, users may feel skeptical or uncertain about AI decision-making processes, which can hinder adoption and acceptance.

In contrast, the other choices involve principles that do not align with the foundational elements of trust in AI governance. Profitability, efficiency, a lack of human oversight, and prioritizing speed over accuracy do not inherently promote transparency, accountability, or ethical considerations, which are vital for fostering trust in AI implementations.