Description: Qualitative metrics in artificial intelligence (AI) ethics are tools that focus on assessing the quality of experiences and outcomes generated by AI systems. Unlike quantitative metrics, which focus on numerical data and statistics, qualitative metrics seek to understand more subjective and contextual aspects, such as user perception, fairness in outcomes, and the social impact of automated decisions. These metrics are essential to ensure that AI systems operate ethically and responsibly, considering not only efficiency and accuracy but also the well-being of individuals and communities affected. The implementation of qualitative metrics allows developers and policymakers to identify biases, improve transparency, and foster trust in AI technologies. In a world where AI plays an increasingly important role, these metrics become an essential component for addressing ethical and social concerns, ensuring that technology benefits everyone equitably and fairly.
