Measuring artificial intelligence depends on what one wants to evaluate: accuracy, efficiency, or its ability to act more like a human. The commonly used criteria are: how accurate, adaptable, and speedy it is. Tools include benchmark datasets, performance metrics such as precision, recall, F1 score, and Turing Tests.

But I would ask, in return, is it enough to benchmark only technical performance, or should it involve how well AI aligns with human values and solves real-world problems?

Dear Rahul Khurana

Measuring artificial intelligence indeed extends beyond mere technical performance indicators like accuracy, efficiency, and human-like behavior. While metrics such as precision, recall, F1 score, and Turing Tests provide valuable insights into the capabilities of AI systems, they do not fully capture the broader impact of AI on society.

Therefore, incorporating ethical considerations and impact assessments into AI evaluation frameworks is vital for the responsible development and deployment of AI technologies.

Best regards