Which principle focuses on fairness, ethics, and human accountability in AI governance?

The principle that emphasizes fairness, ethics, and human accountability in AI governance is centered around the concept of AI Ethics. This principles guides organizations to ensure that their AI systems are developed and deployed in a manner that respects human rights, promotes justice, and avoids bias or discrimination. It involves the creation of frameworks and guidelines that dictate how AI technologies should be designed and used to protect individuals and society from harm.

AI Ethics encompasses several key factors, including transparency in AI decision-making processes, the necessity to address and mitigate biases, and ensuring that AI systems operate within a set of ethical boundaries that stakeholders can trust. This principle is foundational in fostering responsible AI development, as it directly addresses the moral implications and social impact of AI technologies, pushing for solutions that prioritize human well-being and ethical standards.

In contrast, the other principles - Purpose Specification, Quality and Integrity, and Accountability - focus on different aspects of AI governance. While they certainly play important roles in ensuring that AI systems function correctly and serve their intended purposes, they do not directly address the ethical considerations and human-centric values as comprehensively as AI Ethics does.