, we can use our work in cognitive science and linguistics to explain why it is all too easy for humans to fall into the cognitive trap of thinking that an entity that can use language fluently is sentient, conscious or intelligent.Text generated by models like Google’s LaMDA can be hard to distinguish from text written by humans. This impressive achievement is a result of a decades-long program to build models that generate grammatical, meaningful language.
Today’s models, sets of data and rules that approximate human language, differ from these early attempts in several important ways. First, they are trained on essentially the entire internet. Second, they can learn relationships between words that are far apart, not just words that are neighbors. Third, they are tuned by a huge number of internal “knobs”—so many that it is hard for even the engineers who design them to understand why they generate one sequence of words rather than another.
But how did GPT-3 come up with this paragraph? By generating a word that fit the context we provided. And then another one. And then another one. The model never saw, touched or tasted pineapples—it just processed all the texts on the internet that mention them. And yet reading this paragraph can lead the human mind—even that of a Google engineer—to imagine GPT-3 as an intelligent being that can reason about peanut butter and pineapple dishes.
ConversationUS When an AI inexplicably gets public speaking anxiety, THEN I'll believe it's truly sentient.