Testing AI Intelligence and Language Perception

The chapter explores the challenges of testing AI for human-like intelligence and critiques existing benchmarks like ImageNet and GLUE. It delves into the complexities of language as an indicator of intelligence in both human and artificial systems, questioning the traditional association between language fluency and intelligence. The discussion also touches upon the historical roots of intelligence testing, the pitfalls of equating language abilities with intellect, and the importance of domain expertise in building automation models.