The Innovators: How a Group of Inventors, Hackers, Geniuses, and Geeks Created the Digital Revolutio - Isaacson Walter (книги полностью .txt) 📗

This was the idea behind an alternative to the quest for pure artificial intelligence: pursuing instead the augmented intelligence that occurs when machines become partners with people. The strategy of combining computer and human capabilities, of creating a human-computer symbiosis, turned out to be more fruitful than the pursuit of machines that could think on their own.

Licklider helped chart that course back in 1960 in his paper “Man-Computer Symbiosis,” which proclaimed: “Human brains and computing machines will be coupled together very tightly, and the resulting partnership will think as no human brain has ever thought and process data in a way not approached by the information-handling machines we know today.”²⁰ His ideas built on the memex personal computer that Vannevar Bush had imagined in his 1945 essay, “As We May Think.” Licklider also drew on his work designing the SAGE air defense system, which required an intimate collaboration between humans and machines.

The Bush-Licklider approach was given a friendly interface by Engelbart, who in 1968 demonstrated a networked computer system with an intuitive graphical display and a mouse. In a manifesto titled “Augmenting Human Intellect,” he echoed Licklider. The goal, Engelbart wrote, should be to create “an integrated domain where hunches, cut-and-try, intangibles, and the human ‘feel for a situation’ usefully co-exist with . . . high-powered electronic aids.” Richard Brautigan, in his poem “All Watched Over by Machines of Loving Grace,” expressed that dream a bit more lyrically: “a cybernetic meadow / where mammals and computers / live together in mutually / programming harmony.”

The teams that built Deep Blue and Watson have adopted this symbiosis approach rather than pursue the objective of the artificial intelligence purists. “The goal is not to replicate human brains,” says John Kelly, the director of IBM Research. Echoing Licklider, he adds, “This isn’t about replacing human thinking with machine thinking. Rather, in the era of cognitive systems, humans and machines will collaborate to produce better results, each bringing their own superior skills to the partnership.”²¹

An example of the power of this human-computer symbiosis arose from a realization that struck Kasparov after he was beaten by Deep Blue. Even in a rule-defined game such as chess, he came to believe, “what computers are good at is where humans are weak, and vice versa.” That gave him an idea for an experiment: “What if instead of human versus machine we played as partners?” When he and another grandmaster tried that, it created the symbiosis that Licklider had envisioned. “We could concentrate on strategic planning instead of spending so much time on calculations,” Kasparov said. “Human creativity was even more paramount under these conditions.”

A tournament along these lines was held in 2005. Players could work in teams with computers of their choice. Many grandmasters entered the fray, as did the most advanced computers. But neither the best grandmaster nor the most powerful computer won. Symbiosis did. “The teams of human plus machine dominated even the strongest computers,” Kasparov noted. “Human strategic guidance combined with the tactical acuity of a computer was overwhelming.” The final winner was not a grandmaster nor a state-of-the-art computer, nor even a combination of both, but two American amateurs who used three computers at the same time and knew how to manage the process of collaborating with their machines. “Their skill at manipulating and coaching their computers to look very deeply into positions effectively counteracted the superior chess understanding of their grandmaster opponents and the greater computational power of other participants,” according to Kasparov.²²

In other words, the future might belong to people who can best partner and collaborate with computers.

In a similar fashion, IBM decided that the best use of Watson, the Jeopardy!-playing computer, would be for it to collaborate with humans rather than try to top them. One project involved using the machine to work in partnership with doctors on cancer treatment plans. “The Jeopardy! challenge pitted man against machine,” said IBM’s Kelly. “With Watson and medicine, man and machine are taking on a challenge together—and going beyond what either could do on its own.”²³ The Watson system was fed more than 2 million pages from medical journals and 600,000 pieces of clinical evidence, and could search up to 1.5 million patient records. When a doctor put in a patient’s symptoms and vital information, the computer provided a list of recommendations ranked in order of its confidence.²⁴

In order to be useful, the IBM team realized, the machine needed to interact with human doctors in a manner that made collaboration pleasant. David McQueeney, the vice president of software at IBM Research, described programming a pretense of humility into the machine: “Our early experience was with wary physicians who resisted by saying, ‘I’m licensed to practice medicine, and I’m not going to have a computer tell me what to do.’ So we reprogrammed our system to come across as humble and say, ‘Here’s the percentage likelihood that this is useful to you, and here you can look for yourself.’?” Doctors were delighted, saying that it felt like a conversation with a knowledgeable colleague. “We aim to combine human talents, such as our intuition, with the strengths of a machine, such as its infinite breadth,” said McQueeney. “That combination is magic, because each offers a piece that the other one doesn’t have.”²⁵

That was one of the aspects of Watson that impressed Ginni Rometty, an engineer with a background in artificial intelligence who took over as CEO of IBM at the beginning of 2012. “I watched Watson interact in a collegial way with the doctors,” she said. “It was the clearest testament of how machines can truly be partners with humans rather than try to replace them. I feel strongly about that.”²⁶ She was so impressed that she decided to launch a new IBM division based on Watson. It was given a $1 billion investment and a new headquarters in the Silicon Alley area near Manhattan’s Greenwich Village. Its mission was to commercialize “cognitive computing,” meaning computing systems that can take data analysis to the next level by teaching themselves to complement the thinking skills of the human brain. Instead of giving the new division a technical name, Rometty simply called it Watson. It was in honor of Thomas Watson Sr., the IBM founder who ran the company for more than forty years, but it also evoked Sherlock Holmes’s companion Dr. John (“Elementary, my dear”) Watson and Alexander Graham Bell’s assistant Thomas (“Come here, I want to see you”) Watson. Thus the name helped to convey that Watson the computer should be seen as a collaborator and companion, not a threat like 2001’s HAL.

Watson was a harbinger of a third wave of computing, one that blurred the line between augmented human intelligence and artificial intelligence. “The first generation of computers were machines that counted and tabulated,” Rometty says, harking back to IBM’s roots in Herman Hollerith’s punch-card tabulators used for the 1890 census. “The second generation involved programmable machines that used the von Neumann architecture. You had to tell them what to do.” Beginning with Ada Lovelace, people wrote algorithms that instructed these computers, step by step, how to perform tasks. “Because of the proliferation of data,” Rometty adds, “there is no choice but to have a third generation, which are systems that are not programmed, they learn.”²⁷

But even as this occurs, the process could remain one of partnership and symbiosis with humans rather than one designed to relegate humans to the dustbin of history. Larry Norton, a breast cancer specialist at New York’s Memorial Sloan-Kettering Cancer Center, was part of the team that worked with Watson. “Computer science is going to evolve rapidly, and medicine will evolve with it,” he said. “This is coevolution. We’ll help each other.”²⁸