Читать книгу Smarter Data Science - Cole Stryker - Страница 32

For organizations that make gut-feel decisions and are apprehensive about pursuing data-driven means, the ability to measure is vital. The ends and means model shown in Chapter 1, “Climbing the AI Ladder,” Figure 1-4 illustrates the necessity to balance what needs to be measured with something that can produce something that is measurable and is aligned to what ultimately needs to be measured.

The use of AI requires an organization to become data-driven, especially when a person is in a decision-making loop. Machine-to-machine communication fosters the ability of a machine to act independently to make decisions based purely on the information at hand. Orchestrating a person into a communication flow allows for decision augmentation and to act as a gatekeeper.

In the 1960s, the euphemism Mad Men was supposedly created by those working in the field of advertising, where—in the United States—the industry was heavily centered around Madison Avenue in New York City (the men of Madison Avenue). Mad Men created messages for the masses. Whether messages were regionally appropriate or whether an advertisement resonated exceptionally well with the discrete needs of each singular individual was not the core focus. Eventually, the gut feel of the Mad Men approach gave way to the focus group–oriented view of the Media Men. In turn, the Media Men have given way to the Math Men. The Math Men are the men and women of data science whose provinces are the hordes of big data and thick data, algorithms, and machine learning that derive insight from data. As the new-collar worker expands into all aspects of corporate work from using model-based outcomes, each decision is going to be based on data. New-collar workers are data-driven and so are their decisions.