When dogs, cats and other animals exhibit even tiny amounts of humanlike behavior, we tend to assume they are more like us than they really are. Much the same happens when we see hints of human behavior in a machine.
Goertzel was on keys. The band’s friends and family listened from a patio overlooking the beach. And Desdemona, wearing a purple wig and a black dress laced with metal studs, was on lead vocals, warning of the coming Singularity — the inflection point where technology can no longer be controlled by its creators.
Goertzel is CEO and chief scientist of an organization called SingularityNET. He built Desdemona to, in essence, mimic the language in books he had written about the future of artificial intelligence. When she was assured that it was not, her reply was swift. “That’s consoling,” she said. Google eventually fired Lemoine.
The problem is that the people closest to the technology — the people explaining it to the public — live with one foot in the future. They sometimes see what they believe will happen as much as they see what is happening now. He said the system would one day learn to recognize handwritten words, spoken commands and even people’s faces. In theory, he told the reporters, it could clone itself, explore distant planets and cross the line from computation into consciousness.
Some of the pioneers were engineers. Others were psychologists or neuroscientists. No one, including the neuroscientists, understood how the brain worked. But they believed they could somehow re-create it. Some believed more than others. Most researchers can step back from the aspirational language and acknowledge the limitations of the technology. But sometimes, the lines get blurry.In 2020, OpenAI unveiled a system called GPT-3. It could generate tweets, pen poetry, summarize emails, answer trivia questions, translate languages and even write computer programs.
This is the same technology that Rosenblatt explored in the 1950s. He did not have the vast amounts of digital data needed to realize this big idea. Nor did he have the computing power needed to analyze all that data. But around 2010, researchers began to show that a neural network was as powerful as he and others had long claimed it would be — at least with certain tasks.
But there are endless caveats. Using GPT-3 is like rolling the dice: If you ask it for 10 speeches in the voice of Donald Trump, it might give you five that sound remarkably like the former president — and five others that come nowhere close. Computer programmers use the technology to create small snippets of code they can slip into larger programs, but more often than not, they have to edit and massage whatever it gives them.
“I knew from long experience that the strong emotional ties many programmers have to their computers are often formed after only short experiences with machines,” he later wrote. “What I had not realized is that extremely short exposures to a relatively simple computer program could induce powerful delusional thinking in quite normal people.”
When we spoke on the phone, he asked that I keep his identity secret. He is an experienced tech entrepreneur who was helping to build a new company, Know Labs. But after Lemoine made similar claims about similar technology developed at Google, Bosua said he was happy to go on the record. “The best syntax is honesty,” he said. “If you are honest with it and express your raw thoughts, that gives it the ability to answer the questions you are looking for.”
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