AI and UX by Gavin Lew & Robert M. Schumacher Jr

Author:Gavin Lew & Robert M. Schumacher Jr.
Language: eng
Format: epub
ISBN: 9781484257753
Publisher: Apress

Data science and imputation

Data science , like AI, has been getting a lot of buzz lately.

Definition

Data science—you might also call it data analytics—is the analysis of large datasets to gather insights.

The potential to uncover insights from a massive amount of data that would be impossible by a human is alluring. AI a lot of the time is spent on the algorithms, but, surprisingly, not a lot of time is spent on data. All too often, data is purchased or obtained from historical archives and the data is spun into AI. There is an eagerness to see what happens when the AI algorithm thinks. So much interest is focused on the algorithm and what it uncovers, but are we spending enough attention on the data that are fed into the machine?

AI has been described as a black box; data goes in and what comes out the other side may show no traceability to the inputs (Figure 3-1).

Figure 3-1Illustration of information entering the black box (i.e., AI process) and insight emerges on the other side

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