Work-in-Progress: What Recent Artificial Intelligence Breakthroughs in the Game of GO Mean for Human Learning and Engineering Education

Abstract

Artificial intelligence, led by the method of deep learning, has generated enormous interest in both professional circle and general public in the last two years thanks to Deepmind’s AlphaGo’s stunning mastery of Go, the most sophisticated board game. While most interest since then has been shown in exploring the applications of AlphaGo’s algorithms in machine learning, it is the potential impact of its learning strategy on human learning that captures our attention. Can AlphaGo’s success, aside from taking advantage of superior computing power, lead to more effective learning for humans? Does AlphaGo’s learning lend support to any of the learning theories? Or does the training data reveal any notable pattern or trajectory that may suggest new perspectives on human cognition? In this work-in-progress paper, we try to make connection between human and machine learning using the technical details revealed by the Deepmind team, and examine what insights can be gained from AlphaGo’s training on human cognitive development and more specifically, engineering education.