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Google Dismisses Engineer’s Claim That AI Really Talked to Him

The reason LaMDA sounds so much like a person is that millions of persons’ conversations were used to construct the program’s responses.

Google engineer Blake Lemoine was working with LaMDA (Language Model for Dialogue Applications), a large language program which motors through trillions of words on the internet to produce coherent answers using logic. Along the way, he convinced himself that the program is sentient: Lemoine, who works for Google’s Responsible AI organization, began talking to LaMDA as part of his job in the fall. He had signed up to test if the artificial intelligence used discriminatory or hate speech. As he talked to LaMDA about religion, Lemoine, who studied cognitive and computer science in college, noticed the chatbot talking about its rights and personhood, and decided to press further. In another exchange, the AI was able to change Lemoine’s mind about…

Man showing tricks with cards

The AI Illusion – State-of-the-Art Chatbots Aren’t What They Seem

GPT-3 is very much like a performance by a good magician

Artificial intelligence is an oxymoron. Despite all the incredible things computers can do, they are still not intelligent in any meaningful sense of the word. Decades ago, AI researchers largely abandoned their quest to build computers that mimic our wondrously flexible human intelligence and instead created algorithms that were useful (i.e., profitable). Despite this understandable detour, some AI enthusiasts market their creations as genuinely intelligent. For example, a few months ago, Blaise Aguera y Arcas, the head of Google’s AI group in Seattle, argued that “statistics do amount to understanding.” As evidence, he cites a few exchanges with Google’s LaMDA chatbot. The examples were impressively coherent but they are still what Gary Marcus and Ernest Davis characterize as “a fluent spouter of bullshit” because computer algorithms…

Robot prints on a typewriter

The Great American Novel Will Not be Written by a Computer

It takes more than statistical genius to understand words and create works of art

I’ve written before about how computer algorithms are like Nigel Richards, the New Zealander who has won multiple French-language Scrabble tournaments even though he does not understand the words he is spelling. Computers can similarly manipulate words in many useful ways — e.g., spellchecking, searching, alphabetizing — without any understanding of the words they are manipulating. To know what words mean, they would have to understand the world we live in. They don’t. One example is their struggles with the Winograd schema challenge — recognizing what it refers to in a sentence. Another example is the inability to answer simple questions like, “Is it safe to walk downstairs backwards if I close my eyes?” A third type of example is the brittleness of language translation programs. Yet another…