AI's achilles' heel: Ambiguity

Many years ago, I was touring a working orchard with a friend. His son, who was the orchard's manager, was describing his work. His father and I, being engineers, got into a discussion about how a robot might be instructed to pick the fruit. • The son stopped and stared at us in consternation. "What are you guys talking about!? It's simple—you see it, you pick it." · Not so simple: It's only now, decades later, that commercial fruit-picking robots are on the radar. There are many everyday tasks that seem trivial yet are difficult to describe and structure for automation. Humans have the advantage of common-sense reasoning, which is much more deep and profound than most people would believe. · In my February column, I wrote about our success in creating computer programs that can master games like chess and poker. By their descriptions, these games are extraordinarily simple—a small number of immutable rules involving a few elements, whether they be chess pieces or playing cards. But there is a paradox, because underneath this simplicity is an enormous complexity. Nonetheless, that complexity is precisely defined, and that's what we engineers are good at. · However, life is fuzzy and often ill defined. (If only real-life tasks could be modeled as board games, we'd be in business.) I love the idea of fuzzy logic, but on reflection, I actually do want my computer to be precise.