Why Knowledge Representation Matters

In CACM:   By Yoav Shoham   via David Geddes.

There is a big difference between the attention artificial intelligence (AI) is currently receiving and that of the 1990s. Twenty years ago, the focus was on logic-based AI, usually under the heading of knowledge representation, or KR, whereas today's focus is on machine learning and statistical algorithms. This shift has served AI well, since machine learning and stats provide effective algorithmic solutions to certain kinds of problems (such as image recognition), in a way that KR never did. However, I contend the pendulum has swung too far, and something valuable has been lost.

Knowledge representation is not a single thing. While I think an argument could be made about KR as a whole, I will be focusing on the "applied philosophy" aspect of it—the logical representation of commonsense notions, with an emphasis on clear semantical underpinnings.
I will make the case for the most part through a personal story. The story starts with a paper I published in 2009 in the Journal of Philosophical Logic, continues with a research project at Stanford and Duke, later with a company called Timeful, and concludes with Timeful being acquired by Google in 2015. The point of the story is there is a direct link between the original journal paper and the ultimate success of the company.  ... " 

Link to a longer article.