With the growth of AI applications there is renewed interest in the measurement of intelligence. Writing in Venture Beat, Sri Ambati discusses the evolving options for assessing the capabilities of various AI offerings. The available approaches discussed by Ambati include MMLU, ARC-AGI, Humanity’s Last Exam, and GAIA.
Each of these approaches has strengths and limitations. Work on the development of assessments for AI models raises a few questions for those who have long conducted research on intelligence testing. For example, what can the community of researchers whose work focuses on the measurement of human intelligence contribute to the development of assessments and benchmarks for AI systems? And, of course, what can that same community of researchers learn from the latest efforts to measure artificial intelligence?
A less obvious question is whether the measurement of artificial intelligence and the measurement of human intelligence should be aligned. Does such alignment risk missing the unique capacities of two very different entities?
Be the first to comment