Have you ever spent any time with Eliza? You can reach her at this link. Eliza was one of the earliest attempts at artificial intelligence and natural language processing: building a computer program that can use language and interact in a conversation, more or less like a human. (The ultimate test of artificial intelligence, as posed by Alan Turing, is the creation of a computer that can carry on a conversation so well that its human interlocutor can’t tell the difference).
The program was written in the 1960s at MIT and embedded with a script following humanistic Rogerian psychotherapy. While Eliza is simply parsing your inputs and coming back with canned responses, (“I feel lonely.” “Why do you say that you feel lonely?”) interacting with it can often feel startlingly authentic, even therapeutic. New versions of Eliza are in use today for customer service.
Today AI is progressing, most visibly in voice recognition and assistance software like the Siri app for the iPhone. Siri was built to answer questions. Some of the scientists behind Siri are currently working for an educational gaming company, Kuato Studios, on a sort of universal tutoring platform: a computer teacher.
To do this they’ve enlisted the services of a real teacher, David Miller, a Scotsman who was Teacher of the Year in the UK in 2008. Miller has a background in music and English and was known in the classroom for orchestrating elaborate multimedia experiences to bring a poem or work of literature to life.
“For me real learning is a mano a mano, eye to eye event,” he says. “But we’re working really hard, myself and my learning team, with the AI people, in order to create an intelligence that in some ways is mimicking a teacher: offering encouragement, intelligent responses, feedback, even a bit of humor.”
To carry on a conversation that elicits learning is really at the fringes of what technology can do, so many of the interactions have to be couched very carefully. Let’s say the lesson is biology.
“You can’t just freely ask a child to say what a cell is,” says Miller. “You’re hit with all manner of problems with the way she might phrase the answer. Would she just be giving keywords? And can she properly put it all together? So that the interactions have to be very granular.” For example, the program could show them a picture of the cell, and ask them to talk about each part in turn, its name and its function. “It’s about taking apart the watch of the mind and putting it back together step by step.”
Besides evaluating simple right or wrong answers, the tutoring platform can monitor things like response time and speed of keystrokes, to check the child’s attention and engagement, and offer immediate feedback, encouragement, or even a flash of cheek. As Miller phrases it in his own culturally specific way, “You might tell them ‘Brilliant! Spot on!’” Or if they took three or four ‘nudges’ or hints to get the answer, “You didn’t really cover yourself in glory there.”
The first iteration of the platform will be out later this year, an immersive, game-like environment set on a spaceship, where the player interacts with an “onboard” computer who helps them learn about the simulated world around them. Eventually, says Miller, the vision is a platform able to be loaded with any ontology–any large body of knowledge, from 19th century French literature to medical anatomy to architecture–and “teach” that knowledge–or at least, create scenarios where the children can learn it.
Miller, who even in a short conversation comes alive with empathy and passion for the arts, is the first person to admit he’s an odd one to find himself embracing the latest technology to create a computer version of himself. “There’s nothing I love beter than standing in front of 30 kids and holding them in the palm of my hand with the power of communication, and the twinkle in the eye,” he says. “It’s such an extraordinary chemistry, the whole business of teacher to student–making them feel they’ll do better if they try harder.” But, he says, there’s an untapped opportunity to transform the technology that we and our children use all the time into a portal to the love of learning–a tool that students could really have a relationship with. A lot of the magic, of course, is found in the student’s imagination.
“We’re asking a child to trust a machine. We trust technology to answer questions like where should I eat tonight? But to entrust our children to a machine it has to really delicately be achieved and developed. I’m a very passionate, human oriented person, but I think it’s quite fun, and I find myself in a place where I want to use machines to develop another level of humanity to help children learn.”