2024/05/03 by Herbert L. Roitblat, Roitblat, Herbert L.
Computer Science · #Artificial Intelligence (cs.AI) #Computability, Logic, AI Algorithms #FOS: Computer and information sciences
paper · pdf · doi:10.48550/arxiv.2405.01840
openalex publication_date 2024/05/03 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Artificial intelligence systems exhibit many useful capabilities, but they appear to lack understanding. This essay describes how we could go about constructing a machine capable of understanding. As John Locke (1689) pointed out words are signs for ideas, which we can paraphrase as thoughts and concepts. To understand a word is to know and be able to work with the underlying concepts for which it is an indicator. Understanding between a speaker and a listener occurs when the speaker casts his or her concepts into words and the listener recovers approximately those same concepts. Current models rely on the listener to construct any potential meaning. The diminution of behaviorism as a psychological paradigm and the rise of cognitivism provide examples of many experimental methods that can be used to determine whether and to what extent a machine might understand and to make suggestions about how that understanding might be instantiated.