For the thousands of secondary school students who take Japan’s university entrance exams each year, test days are long-dreaded nightmares of jitters and sweaty palms. But the newest test taker can be counted on to keep its cool: AIs don’t sweat.Not yet, but soon...
At Japan’s National Institute of Informatics (NII), in Tokyo, a research team is trying to create an artificial intelligence program that has enough smarts to pass Japan’s most rigorous entrance exams. The AI will start by taking the standardized test administered to all secondary school students; once it masters that test, it will move on to the more difficult University of Tokyo exam.
“Passing the exam is not really an important research issue, but setting a concrete goal is useful,” says Noriko Arai, the team leader and a professor at NII. And by having the AI answer real questions from the exams, “we can compare the current state-of-the-art AI technology with 18-year-old students,” she says. The latest results show that her protégé is coming along well in subjects like history and reading comprehension.
The project began in 2011, when the director of NII challenged his professors to come up with a problem that was “stupendously big and stupendously difficult,” as Arai describes it, but could be easily understood by the general public. The University of Tokyo, known locally as Todai, has a legendarily difficult entrance exam, and the problem came to Arai in an elevator: “Could a robot get into the Todai?” she wondered. Thus the Todai Robot was born.
By 2016, the team hopes its AI will achieve a high score on the national standardized test, which includes multiple-choice questions in subjects such as physics and world history and requires students to solve math problems. But the machine-learning and natural-language-processing tools Arai’s team is developing for that test won’t prepare it for the Todai exam, which includes written essays. The team hopes the AI will pass the Todai exam by 2021, although they don’t yet know how it will accomplish that goal. “The generation of text from information has not been studied very much,” says NII associate professor Yusuke Miyao, another member of the team.