Perhaps the more troubling question in the rising popularity of machine learning in analytics is whether machine learning will replace the analyst in drawing inferences. William I.B. Beveridge (The Art of Scientific Investigation, 1957) had this to say on that topic:
“… the person who possesses the flair for choosing profitable lines of investigation is able to see further whither the work is leading than are other people, because he has the habit of using his imagination to look far ahead instead of restricting his thinking to established knowledge and the immediate problem.”
IBM Watson uses machine learning and statistical methods to reach its conclusions. And some visualization systems use machine learning to refine visualizations. If inferences lead to action, however, humans must be part of the analytic loop.
Machine learning methods will continue to improve their ability to include extraneous information, to backtrack, and to explore far-fetched hypotheses. But they will never have the imagination that humans possess in any critical domain where we must apply our best judgment. The value of both verbal and visual analytics lies in the computer guiding our decisions, not making them.
So the forecast by some analytic gurus that verbal analytics will replace statistics packages, BI platforms, dashboards, machine learning systems, and every other type of analytic environment is, at best, overheated, and, at worst, ignorant of basic psychology.
Future systems will allow us to speak to the computer in ordinary language and to access data repositories for relevant metadata. But these will not substitute for the immediate impact of an effective visualization and the ability to explore complex data sets through our own eyes.