SAN FRANCISCO — Google placed an engineer on paid leave recently after dismissing his claim that its artificial intelligence is sentient, surfacing yet another fracas about the company’s most advanced technology.
Blake Lemoine, a senior software engineer in Google’s Responsible A.I. organization, said in an interview that he was put on leave Monday. The company’s human resources department said he had violated Google’s confidentiality policy. The day before his suspension, Mr. Lemoine said, he handed over documents to a U.S. senator’s office, claiming they provided evidence that Google and its technology engaged in religious discrimination.
Google said that its systems imitated conversational exchanges and could riff on different topics, but did not have consciousness. “Our team — including ethicists and technologists — has reviewed Blake’s concerns per our A.I. Principles and have informed him that the evidence does not support his claims,” Brian Gabriel, a Google spokesman, said in a statement. “Some in the broader A.I. community are considering the long-term possibility of sentient or general A.I., but it doesn’t make sense to do so by anthropomorphizing today’s conversational models, which are not sentient.” The Washington Post first reported Mr. Lemoine’s suspension.
fired a researcher who had sought to publicly disagree with two of his colleagues’ published work. And the dismissals of two A.I. ethics researchers, Timnit Gebru and Margaret Mitchell, after they criticized Google language models, have continued to cast a shadow on the group.
neural network, which is a mathematical system that learns skills by analyzing large amounts of data. By pinpointing patterns in thousands of cat photos, for example, it can learn to recognize a cat.
Over the past several years, Google and other leading companies have designed neural networks that learned from enormous amounts of prose, including unpublished books and Wikipedia articles by the thousands. These “large language models” can be applied to many tasks. They can summarize articles, answer questions, generate tweets and even write blog posts.
But they are extremely flawed. Sometimes they generate perfect prose. Sometimes they generate nonsense. The systems are very good at recreating patterns they have seen in the past, but they cannot reason like a human.