David Pfau, a research scientist at DeepMind, the London-based A.I. company that is also owned by Google-parent Alphabet, tweeted that, “One day we'll tell stories about how people thought language models were intelligent with the same incredulity of people thinking that cameras steal your soul, or that the train in the movie was actually going to crash into people.”

Erik Brynjolfsson, an economist at Stanford University’ Institute for Human-Centered AI who studies the economic impact of increasing levels of autonomy, tweeted that Lemoine’s claims are the modern equivalent of a dog who hears a voice from a gramophone and is convinced his master is inside the machine. (Marcus picked up on this image to illustrate his blog post.)

Lemoine’s claims and the uncanny conversational abilities displayed by LaMDA in the transcripts Lemoine has leaked to the press highlight what many A.I. ethicists say is the importance for companies that deploy A.I. systems that can hold such dialogues to always make it clear to people interacting with such software that they are not speaking to a real person.

In 2018, Google was widely condemned by technology ethicists for conducting demonstrations of its voice-enabled A.I. assistant “Google Duplex,” in which the software—which creates very natural sounding speech, including pauses and filler words and sounds such as “hmm,” and “um”—called a restaurant and made reservations without the person on line being aware they were speaking to an A.I. system. Since then, many A.I. ethicists have redoubled their calls for companies using chatbots and other “conversational A.I.” to make it crystal clear to people that they are interacting with software, not flesh-and-bone.

Who's responsible?

In the Twitter dustup over Lemoine’s case, while the A.I. researchers all agreed LaMDA isn’t sentient, they quickly fell out with one another over who, if anyone, bore partial responsibility for Lemoine’s misapprehension.

Some faulted companies that produce A.I. systems known as ultra-large language models, one of which underpins LaMDA, for making inflated claims about the technology's potential. Some of scientists working at these companies have suggested that ultra-large language models are a step towards human-like artificial general intelligence. But some critics question whether Google and other companies should continue to pursue such ultra-large language model research.

There was also debate over whether the Turing Test—a famous thought experiment about a machine that could conduct a dialogue with a person so convincingly that the person would not know they were conversing with a machine—should continue to serve as a guiding benchmark for many in A.I. research.

Marcus is among those who points out that the Turing Test has no long ceased to be a useful benchmark for progress towards artificial general intelligence, which is variously defined as a single A.I. system that can perform many different, economically-useful tasks as well or better than a human, or a machine system that exhibits traits normally associated with human intelligence, including adaptable and flexible learning, creativity, logical reasoning, and common sense. He notes that as far back as the mid-1960s software called ELIZA, which was supposed to mimic the dialogue of a Freudian psychoanalyst, convinced some people it was a person. And yet ELIZA did not lead to AGI. Nor did “Eugene Goostman,” an A.I. program that in 2014 won a Turing Test competition, by fooling some judges of the contest into thinking it was a 13-year old boy.

“It has made zero lasting contribution to AI,” Marcus wrote.

Miles Brundage, who researches governance issues around A.I. at OpenAI, the San Francisco research company that is among those pioneering the commercial use of ultra-large language models similar to the one that Google uses for LaMDA, called Lemoine’s belief in LaMDA’s sentience “a wakeup call.” He said it was evidence for “how prone some folks are to conflate” concepts such as creativity, intelligence, and consciousness, which he sees a distinct phenomenon, although he said he did not think OpenAI’s own communications had contributed to this conflation. OpenAI's chief scientist, Ilya Sutskever, has often said he thinks these large language models may be the path to AGI and even tweeted in February that today's large language models "may be slightly conscious."

Brundage's comments—and in particular his view that OpenAI's own comments and tweets were not responsible for Lemoine's confused belief in LaMDA's sentience—drew a sharp reply from Emily Bender, a professor of computational linguists at the University of Washington who is highly critical of the ultra-large language models. In an exchange with Brundage over Twitter, she implied that OpenAI and other companies working on this technology needed to acknowledge their own responsibility for hyping the technology as a possible path to AGI.

“Senior research at organization that claims to be making progress towards ‘AGI’ by building bigger and bigger LMs doesn't believe they have any impact on people thinking that LM driven chatbots are sentient. Got it,” she wrote.

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