Author Cathy O’Neil argues that the right approach to data is skeptical, not cynical––it understands that, while powerful, data science tools often fail.
Data is nuanced, and “a really excellent skeptic puts the term ‘science’ into ‘data science.'” The big data revolution shouldn’t be dismissed as hype, but current data science tools and models shouldn’t be hailed as the end-all-be-all, either.
OK, perhaps our fire-and-brimstone headline goes a bit overboard. Then again, maybe it is time for a dose of data science atonement, particularly if youre guilty of any of the five deadly sins summarized below.
Not all big-data professionals are guilty of the five deadly sins, of course, which Walker summarized in a phone interview withInformationWeek. So here they are. Do any of these data-science transgressions hit home?