Special report in The Economist:
In July 2011 Sebastian Thrun, who among other things is a professor at Stanford, posted a short video on YouTube, announcing that he and a colleague, Peter Norvig, were making their “Introduction to Artificial Intelligence” course available free online. By the time the course began in October, 160,000 people in 190 countries had signed up for it. At the same time Andrew Ng, also a Stanford professor, made one of his courses, on machine learning, available free online, for which 100,000 people enrolled. Both courses ran for ten weeks. Mr Thrun’s was completed by 23,000 people; Mr Ng’s by 13,000.
Such online courses, with short video lectures, discussion boards for students and systems to grade their coursework automatically, became known as Massive Open Online Courses (MOOCs). In 2012 Mr Thrun founded an online-education startup called Udacity, and Mr Ng co-founded another, called Coursera. That same year Harvard University and the Massachusetts Institute of Technology got together to form edX, a non-profit MOOC provider, headed by Anant Agarwal, the head of MIT’s artificial-intelligence laboratory. Some thought that MOOCs would replace traditional university teaching. The initial hype around MOOCs has since died down somewhat (though millions of students have taken online courses of some kind). But the MOOC boom illustrated the enormous potential for delivering education online, in bite-sized chunks.
The fact that Udacity, Coursera and edX all emerged from AI labs highlights the conviction within the AI community that education systems need an overhaul. Mr Thrun says he founded Udacity as an “antidote to the ongoing AI revolution”, which will require workers to acquire new skills throughout their careers. Similarly, Mr Ng thinks that given the potential impact of their work on the labour market, AI researchers “have an ethical responsibility to step up and address the problems we cause”; Coursera, he says, is his contribution. Moreover, AI technology has great potential in education. “Adaptive learning”—software that tailors courses for each student individually, presenting concepts in the order he will find easiest to understand and enabling him to work at his own pace—has seemed to be just around the corner for years. But new machine-learning techniques might at last help it deliver on its promise.