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Current AI metrics focus heavily on technological advancement and economic competitiveness, often overlooking ethical and societal concerns. A study highlights the misalignment between AI evaluation frameworks and National Artificial Intelligence Strategies, emphasizing the need for recalibrated metrics. This gap raises questions about whether AI is being developed in ways that genuinely benefit society.
The study advocates for integrating ethical and social considerations into AI metrics, addressing issues like bias and privacy. It calls for multidimensional metrics that balance technological performance with social impact, aligning AI policies with global development goals. By updating AI metrics to reflect values such as fairness and accountability, AI can be harnessed for a more equitable future.
• Current AI metrics neglect ethical governance and public trust.
• AI policies risk reinforcing inequalities without comprehensive metrics.
AI metrics are used to evaluate the performance and impact of AI technologies.
Ethical AI refers to the development and deployment of AI systems that prioritize fairness and accountability.
SDGs are a set of global goals aimed at addressing social, economic, and environmental challenges.
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