Final Jeopardy (Alexandra Cooper Mysteries) - Linda Fairstein [61]
Lots of the train wreck categories raised questions about the roots of Watson’s misunderstandings. One category, for example, that appeared to confuse it was Books in Español. Watson didn’t come close to identifying Ernest Hemingway’s Adios a las Armas, Harper Lee’s Matar un Ruiseñor, or Stephen King’s La Milla Verde. It already held rudimentary foreign words and phrases in its tool kit. But would it benefit from greater detail? As it turned out, Watson’s primitive Spanish wasn’t the problem. The issue was simpler than that. From the name of the category and the bare-bones phrasing of the clues—Stephanie Meyer: Luna Nueva—the computer did not know what to look for. And unlike human contestants, it was deaf to the correct answers. If IBM and Jeopardy ironed out an arrangement to provide Watson with the answers after each clue, it might orient itself in puzzling categories. That way, it could move on to the real challenge of the clue, recognizing titles like To Kill a Mockingbird and A Farewell to Arms in Spanish.
As the season of sparring sessions progressed, people in the observation room paid less attention to the matches as they were being played. They talked more and looked up at the big monitor when they heard laughter or when Watson found itself in a tight match. The patterns of the machine were becoming familiar. For them, much of the excitement came a day later, when they began to analyze the data and saw how the smarter version of Watson handled the troublesome clues. Ferrucci occasionally used the time during the matches to explain Watson’s workings to visitors, or to give interviews. One March morning, he could be heard across the room talking to a documentary producer. Asked if he would be traveling to California for the televised final match, Ferrucci deadpanned: “I’ll be sedated.”
David Gondek, sitting across from Ferrucci, his fingers on his laptop keyboard, said that pressure in the War Room was mounting. He had largely abandoned his commute from Brooklyn and now spent nights in a small apartment he’d rented nearby. It was only ten minutes by bike to the War Room or a half hour to pedal to the Yorktown labs, where the sparring sessions took place.
From the very beginning, Gondek said, the Jeopardy challenge differed from a typical software project. Usually, software developers are given a list of functions and applications to build. And when they finish them, test, tweak, and debug them, they’re done. Building Watson, however, never ended, he said. There was always something it failed to understand. The work, he said, “is infinite.”
In graduate school, Gondek had focused on data mining. His thesis, on nonredundant clustering, involved programming machines to organize clusters of data around connections that the users might not have considered. By answering some preliminary questions, for example, an intelligence officer might inform the system that he’s all too familiar with Osama bin Laden’s connections to terrorism. So the system, when sorting through a batch of intelligence documents, would find other threads and connections, perhaps leading to fresh insights about the Al Qaeda leader. Machines, much like humans, follow conventional patterns of analysis. Gondek had been thinking about this since listening to a recent talk by a cognitive psychologist. It raised this question: If a machine like Watson fell into the same mental traps as humans, was it a sign of intelligence or just a cluelessness that it happened to share with us? He provided an example.
“What color is snow?” he asked.
“White,” I said.
“A wedding dress?”
“White.”
“Puffy clouds?”
“White.”
“What do cows drink?”
“Milk,” I said, falling obediently into the trap he’d set.
Cows, of course, drink