Using human skills taxonomies and tests as measures of artificial intelligence
Ernest Davis · Educational research and innovation · 2021
This chapter looks at using human skills taxonomies and tests as measures of artificial intelligence (AI). It examines the strong points of computers, such as their ability to store enormous memories and access them reliably and quickly. It also reflects on weaknesses of AI systems compared to humans related to vision and manipulation, and use of natural language. It pays special attention to the limited capacity of AI to use common sense reasoning and world knowledge. In addition, the chapter looks at the ability of AI to detect subtle patterns in data as a double-edged sword. With all this in mind, the chapter proposes four consequences for testing, and looks ahead to building trustworthy AI systems.