Artificial Intelligence for Asset Management and Investment

Chapter 3Design

IMAGINE THAT WE ARE LIVING IN the age of the horse-and-buggy and have set out to automate them. Our one design option could be to design an automated horse. After all, isn't that the most natural way to think about automating what a horse does? Our automated horse will have four mechanical legs and it will trot, canter, and gallop on the road. It will have mechanical levers, and as we pull the levers, the horse will turn or pace. As it turns out, many people did attempt to design mobility solutions by trying to automate the design of a horse¹. Fortunately, we had smarter people who recognized that the idea of automation was not to automate the horse itself, but instead to automate mobility. We automated the function of the horse and not the structure of the horse. Unfortunately, in the AI revolution, many firms are trying to make mechanical horses because they have not figured out that synthetic intelligence allows us to build alternative business models and processes. Design science is the first stage of instituting the industrial-scale enterprise machine learning operation. It is defined as the process of architecting a firm's AI plan that supports the firm's strategy.

WHO IS RESPONSIBLE FOR DESIGN?

The executive leadership of the firm, along with the board, and the data science head are primarily responsible for the design science. We are assuming that this book will help investment firms to create centralized AI and data science departments that will function ...