From BI to AI and From Automation to Augmentation

By succeeding in making machines work in tandem with humans to collect and process data, analyze it, and make decisions, enterprises have benefited from a continuously rising productivity. Over the years, advances in what machines can do have resulted in new tools and methods for analyzing data. These advances have also been accompanied by new waves of excitement and anxiety about automation. Already at the dawn of the computer age, speedy calculations led to new approaches to data analysis such as simulations and Monte Carlo methods. At the same time, the excitement over these "thinking machines" or "giant brains" as they were popularly called at the time, led 26-year-old John Diebold to write a book titled automation, published in 1952.